Please start by introducing your professional journey in academia

My professional journey in academia spans over 8 years combining both research. And teaching in field of electronics and communication engineering.

My professional journey in academia spans over 8 years combining both research. And teaching in field of electronics and communication engineering. I began my academic career as research. Tolerate Jamia Millia Lamia. Where I pursued my PhD from 2015 to 2020.

My professional journey in academia spans over 8 years combining both research. And teaching in field of electronics and communication engineering. I began my academic career as research. Tolerate Jamia Millia Lamia. Where I pursued my PhD from 2015 to 2020. My research focused ON Semiconductor device simulation, particularly on Tfas best. Nanoelectronic devices. Aimed at low power application.

My professional journey in academia spans over 8 years combining both research. And teaching in field of electronics and communication engineering. I began my academic career as research. Tolerate Jamia Millia Lamia. Where I pursued my PhD from 2015 to 2020. My research focused ON Semiconductor device simulation, particularly on Tfas best. Nanoelectronic devices. Aimed at low power application. During this time I published in reputed generals including IEEE Transactions on Electron Devices. And developed a novel train engineer Tifet structure which later resulted in granted Indian patent.

My professional journey in academia spans over 8 years combining both research. And teaching in field of electronics and communication engineering. I began my academic career as research. Tolerate Jamia Millia Lamia. Where I pursued my PhD from 2015 to 2020. My research focused ON Semiconductor device simulation, particularly on Tfas best. Nanoelectronic devices. Aimed at low power application. During this time I published in reputed generals including IEEE Transactions on Electron Devices. And developed a novel train engineer Tifet structure which later resulted in granted Indian patent. After completing my PhD, I transitioned into full-time teaching.

My professional journey in academia spans over 8 years combining both research. And teaching in field of electronics and communication engineering. I began my academic career as research. Tolerate Jamia Millia Lamia. Where I pursued my PhD from 2015 to 2020. My research focused ON Semiconductor device simulation, particularly on Tfas best. Nanoelectronic devices. Aimed at low power application. During this time I published in reputed generals including IEEE Transactions on Electron Devices. And developed a novel train engineer Tifet structure which later resulted in granted Indian patent. After completing my PhD, I transitioned into full-time teaching. I worked as assistant professor at Mallared at the College of Engineering, Hyderabad. Followed by GMR Institute of Technology, Andhra Pradesh. And currently a Takropolis Institute of Technology and Research, Indore. Throughout my teaching career. However, handled core subjects such as analog and mixed signal VLSI design. Electronic devices and digital systems. I have also contributed to curriculum development by aligning. Courses with industry standards and supervise several undergraduate projects in VLSI design.

Eight years is substantial. Did your research focus more on signal processing, communication systems, or another area within electronics and communication?

Okay, so you started your PhD at Jamia Millia Islamia back in 2015 and wrapped it up in 2020. Was your doctoral research mostly in image processing, embedded systems, or something else within electronics and communication?

Semiconductor device simulation and nanoelectronic devices for low-power applications—so your research was pretty specialized. Did your teaching responsibilities also involve guiding students through lab work in these areas, or was it more theory-focused?

Alright, you mentioned publishing in IEEE Transactions and developing a novel TIFET structure that earned a patent—that's impressive. Did you also supervise any student research projects or lead lab courses during your time at Jamia, or was your teaching more focused on lectures?

So after finishing your PhD, you moved into full-time teaching. Did you find the transition from intensive research to the classroom challenging, or was it a natural shift for you?

Dr., since you've handled both theory and lab courses, which do you find more rewarding—teaching core theoretical concepts or guiding students through hands-on lab experiments?

Thank you.

Alright, you’ve worked across several institutes and handled both theory and practical courses, plus curriculum development. When you’re supervising undergraduate VLSI projects, how do you ensure students actually understand the core design principles instead of just following templates or prior work?

That's a very important, very important concern in VLSI project supervision.

That's a very important, very important concern in VLSI project supervision. Because it's quite easy for a student to rely on existing design without. Truly understanding them. Wait does this I follow a structured multi stage process? 1st I focus on concept validation before implementation I. Ask student to explain the underlying theory. Searches most operation timing constraints or power considerations. Before they begin coding or designing. If they cannot explain the why, I don't allow them to proceed to the how.

That's a very important, very important concern in VLSI project supervision. Because it's quite easy for a student to rely on existing design without. Truly understanding them. Wait does this I follow a structured multi stage process? 1st I focus on concept validation before implementation I. Ask student to explain the underlying theory. Searches most operation timing constraints or power considerations.

That's a very important, very important concern in VLSI project supervision. Because it's quite easy for a student to rely on existing design without. Truly understanding them. Wait does this I follow a structured multi stage process? 1st I focus on concept validation before implementation I. Ask student to explain the underlying theory. Searches most operation timing constraints or power considerations. Before they begin coding or designing. If they cannot explain the why, I don't allow them to proceed to the how. Second, I introduced design from sketch tasks.

That's a very important, very important concern in VLSI project supervision. Because it's quite easy for a student to rely on existing design without. Truly understanding them. Wait does this I follow a structured multi stage process? 1st I focus on concept validation before implementation I. Ask student to explain the underlying theory. Searches most operation timing constraints or power considerations. Before they begin coding or designing. If they cannot explain the why, I don't allow them to proceed to the how. Second, I introduced design from sketch tasks. Instead of giving them complete reference design, I break the project into smaller modules. And ask them to resign each block independently. Example is starting from basic logic blocks before moving to. Configuration. Had had I conduct frequent design reviews and Viber session.

That's a very important, very important concern in VLSI project supervision. Because it's quite easy for a student to rely on existing design without. Truly understanding them. Wait does this I follow a structured multi stage process? 1st I focus on concept validation before implementation I. Ask student to explain the underlying theory. Searches most operation timing constraints or power considerations. Before they begin coding or designing. If they cannot explain the why, I don't allow them to proceed to the how. Second, I introduced design from sketch tasks. Instead of giving them complete reference design, I break the project into smaller modules. And ask them to resign each block independently. Example is starting from basic logic blocks before moving to. Configuration. Had had I conduct frequent design reviews and Viber session. In these task them to justify their design choices.

That's a very important, very important concern in VLSI project supervision. Because it's quite easy for a student to rely on existing design without. Truly understanding them. Wait does this I follow a structured multi stage process? 1st I focus on concept validation before implementation I. Ask student to explain the underlying theory. Searches most operation timing constraints or power considerations. Before they begin coding or designing. If they cannot explain the why, I don't allow them to proceed to the how. Second, I introduced design from sketch tasks. Instead of giving them complete reference design, I break the project into smaller modules. And ask them to resign each block independently. Example is starting from basic logic blocks before moving to. Configuration. Had had I conduct frequent design reviews and Viber session. In these task them to justify their design choices. Such as why they select a particular architecture. How how they optimize delay or power and what trade-offs they consider.

That's a very important, very important concern in VLSI project supervision. Because it's quite easy for a student to rely on existing design without. Truly understanding them. Wait does this I follow a structured multi stage process? 1st I focus on concept validation before implementation I. Ask student to explain the underlying theory. Searches most operation timing constraints or power considerations. Before they begin coding or designing. If they cannot explain the why, I don't allow them to proceed to the how. Second, I introduced design from sketch tasks. Instead of giving them complete reference design, I break the project into smaller modules. And ask them to resign each block independently. Example is starting from basic logic blocks before moving to. Configuration. Had had I conduct frequent design reviews and Viber session. In these task them to justify their design choices. Such as why they select a particular architecture.

You started to mention that's a concern, but didn't get into specifics. Go on — what's your actual process for making sure students grasp the core concepts rather than just copying previous designs?

That's a very important, very important concern in VLSI project supervision. Because it's quite easy for a student to rely on existing design without. Truly understanding them. Wait does this I follow a structured multi stage process? 1st I focus on concept validation before implementation I. Ask student to explain the underlying theory. Searches most operation timing constraints or power considerations. Before they begin coding or designing. If they cannot explain the why, I don't allow them to proceed to the how. Second, I introduced design from sketch tasks. Instead of giving them complete reference design, I break the project into smaller modules. And ask them to resign each block independently. Example is starting from basic logic blocks before moving to. Configuration. Had had I conduct frequent design reviews and Viber session. In these task them to justify their design choices. Such as why they select a particular architecture. How how they optimize delay or power and what trade-offs they consider. 4th I emphasized tool understanding, not just uses. While working with tools like Xilinx Vivado, I ensured the interesting synthesis report. Timing analysis and resource utilization rather than just generating outputs. Finally, I encourage. Them original problem statement on slide. Modification.

That's a very important, very important concern in VLSI project supervision. Because it's quite easy for a student to rely on existing design without. Truly understanding them. Wait does this I follow a structured multi stage process? 1st I focus on concept validation before implementation I. Ask student to explain the underlying theory. Searches most operation timing constraints or power considerations. Before they begin coding or designing. If they cannot explain the why, I don't allow them to proceed to the how. Second, I introduced design from sketch tasks. Instead of giving them complete reference design, I break the project into smaller modules. And ask them to resign each block independently. Example is starting from basic logic blocks before moving to. Configuration. Had had I conduct frequent design reviews and Viber session. In these task them to justify their design choices. Such as why they select a particular architecture. How how they optimize delay or power and what trade-offs they consider. 4th I emphasized tool understanding, not just uses. While working with tools like Xilinx Vivado, I ensured the interesting synthesis report. Timing analysis and resource utilization rather than just generating outputs. Finally, I encourage. Them original problem statement on slide. Modification. In existing design, so a student must think. Critically, rather than replicate. Also use plagiarism check. And require proper documentation. To their design flow.

That's a very important, very important concern in VLSI project supervision. Because it's quite easy for a student to rely on existing design without. Truly understanding them. Wait does this I follow a structured multi stage process? 1st I focus on concept validation before implementation I. Ask student to explain the underlying theory. Searches most operation timing constraints or power considerations. Before they begin coding or designing. If they cannot explain the why, I don't allow them to proceed to the how. Second, I introduced design from sketch tasks. Instead of giving them complete reference design, I break the project into smaller modules. And ask them to resign each block independently. Example is starting from basic logic blocks before moving to. Configuration. Had had I conduct frequent design reviews and Viber session. In these task them to justify their design choices. Such as why they select a particular architecture. How how they optimize delay or power and what trade-offs they consider. 4th I emphasized tool understanding, not just uses. While working with tools like Xilinx Vivado, I ensured the interesting synthesis report. Timing analysis and resource utilization rather than just generating outputs. Finally, I encourage. Them original problem statement on slide. Modification. In existing design, so a student must think. Critically, rather than replicate. Also use plagiarism check. And require proper documentation. To their design flow. This approach ensures that. They by the end of the project, the student not only. Complete their design but also develop a strong. Conceptual and practical understanding. Of village principles.

Okay, so you make students explain the theory behind their designs before they build anything — like timing constraints or power considerations. Can you give me a concrete example of a student project where that approach helped them catch a mistake or rethink their design?

Okay, so you won’t let students start building until they can explain the theory behind their designs, like timing constraints or power considerations. Can you walk me through a specific project where a student had trouble with this and how you helped them overcome it?

Okay, so you make students explain the theory behind their VLSI designs and you mentioned design-from-sketch tasks. Can you walk me through a specific example where a student struggled with this process, and how you helped them move from confusion to real understanding?

Okay, so you break projects into modules and run frequent design reviews. What happens when a student keeps missing the mark during those reviews — do you step in and show them the solution, or do you have another strategy for helping them get unstuck?

Dr, I noticed your highly cited paper in IEEE Transactions on Electron Devices about drain-engineered TFETs. How has your research around nanoelectronics and low-power device design influenced the way you teach core courses, like analog VLSI or digital systems, to undergraduates?

You’re pretty strict about making sure students understand the theory before moving to the hands-on part, and you break things down so they design from scratch. When a student struggles to justify their architecture choices in those review sessions, how do you handle it — do you step in and show them the solution, or do you push them to figure it out themselves?

Right, so you make students justify their design choices in real time, not just copy existing architectures. When you’re running those design review sessions, what’s a concrete example of a student who actually surprised you — maybe with an unexpected solution or a clever trade-off you didn’t anticipate?

Okay so you insist on concept validation and make students defend their design choices, plus you break projects into smaller blocks they build from scratch. Can you give me one concrete example of a student who struggled with this approach — what did you do to help them bridge that gap?

Okay, so you insist on concept validation and make students defend their design choices, plus you break projects into smaller blocks they build from scratch. Can you give me one concrete example of a student who really struggled with this process, and how you helped them turn things around?

Okay, you’re pretty methodical about making sure students aren’t just copying designs—they have to defend their choices and understand the tools, plus you push for original problem statements. Switching gears, Dr, your paper in IEEE Transactions on Electron Devices about drain-engineered TFETs is cited quite a bit. How has your work on nanoelectronics and low-power device design influenced the way you teach undergrad courses, especially the practical labs?

That's a great question because my research directly shapes how I approach teaching, especially in labs.

That's a great question because my research directly shapes how I approach teaching, especially in labs. My work on nanoelectronic devices like defects. Particularly focusing on low power design and leakage reduction has made me. Emphasize why device-level physics matters, even. At the circuit level. So in undergraduate labs I don't. Treat experiment as isolated task. I can connect them back to real research problems. For example, when a student study MOSFET characteristics extend the discussion. To short channel effects, leakage currents and threshold behaviours.

That's a great question because my research directly shapes how I approach teaching, especially in labs. My work on nanoelectronic devices like defects. Particularly focusing on low power design and leakage reduction has made me. Emphasize why device-level physics matters, even. At the circuit level. So in undergraduate labs I don't. Treat experiment as isolated task. I can connect them back to real research problems. For example, when a student study MOSFET characteristics extend the discussion. To short channel effects, leakage currents and threshold behaviours. With Chuck critical in modern. Low power devices. I often relate this concept to TFET. Operations so they see how. Fundamental physics translates into advanced. Design.

That's a great question because my research directly shapes how I approach teaching, especially in labs. My work on nanoelectronic devices like defects. Particularly focusing on low power design and leakage reduction has made me. Emphasize why device-level physics matters, even. At the circuit level. So in undergraduate labs I don't. Treat experiment as isolated task. I can connect them back to real research problems. For example, when a student study MOSFET characteristics extend the discussion. To short channel effects, leakage currents and threshold behaviours. With Chuck critical in modern. Low power devices. I often relate this concept to TFET. Operations so they see how. Fundamental physics translates into advanced. Design. In practical labs, I focus. Analysis. Other than just observation? Instead of simply plotting Ivy curves. I asked a student to interpret. What those curves imply in terms of power consumption, switching efficiency and scalability?

You mentioned your research shapes how you teach labs. So, when you’re running a lab on analog and mixed-signal VLSI design, what’s one way you bring your nanoelectronics work into the practical exercises for students?

That's a great question because my research directly shapes how I approach teaching, especially in labs. My work on nanoelectronic devices like defects. Particularly focusing on low power design and leakage reduction has made me. Emphasize why device-level physics matters, even. At the circuit level. So in undergraduate labs I don't. Treat experiment as isolated task. I can connect them back to real research problems. For example, when a student study MOSFET characteristics extend the discussion. To short channel effects, leakage currents and threshold behaviours. With Chuck critical in modern. Low power devices. I often relate this concept to TFET. Operations so they see how. Fundamental physics translates into advanced. Design. In practical labs, I focus. Analysis. Other than just observation? Instead of simply plotting Ivy curves. I asked a student to interpret. What those curves imply in terms of power consumption, switching efficiency and scalability? Also integrate simulation-based learning where students use. To vary parameters like channel and doping. Or gate material and observe. How device performance changes? By my own research methodology in device simulation.

That's a great question because my research directly shapes how I approach teaching, especially in labs. My work on nanoelectronic devices like defects. Particularly focusing on low power design and leakage reduction has made me. Emphasize why device-level physics matters, even. At the circuit level. So in undergraduate labs I don't. Treat experiment as isolated task. I can connect them back to real research problems. For example, when a student study MOSFET characteristics extend the discussion. To short channel effects, leakage currents and threshold behaviours. With Chuck critical in modern. Low power devices. I often relate this concept to TFET. Operations so they see how. Fundamental physics translates into advanced. Design. In practical labs, I focus. Analysis. Other than just observation? Instead of simply plotting Ivy curves. I asked a student to interpret. What those curves imply in terms of power consumption, switching efficiency and scalability? Also integrate simulation-based learning where students use. To vary parameters like channel and doping. Or gate material and observe. How device performance changes? By my own research methodology in device simulation. Another important aspect is is introducing design tradeoffs only. Based on my research and experience. Encourage students to think. In terms of trade-offs like power versus performance? All leakage versus speed. So they developed on. An engineering mindset rather than a purely academic 1.

That's a great question because my research directly shapes how I approach teaching, especially in labs. My work on nanoelectronic devices like defects. Particularly focusing on low power design and leakage reduction has made me. Emphasize why device-level physics matters, even. At the circuit level. So in undergraduate labs I don't. Treat experiment as isolated task. I can connect them back to real research problems. For example, when a student study MOSFET characteristics extend the discussion. To short channel effects, leakage currents and threshold behaviours. With Chuck critical in modern. Low power devices. I often relate this concept to TFET. Operations so they see how. Fundamental physics translates into advanced. Design. In practical labs, I focus. Analysis. Other than just observation? Instead of simply plotting Ivy curves. I asked a student to interpret. What those curves imply in terms of power consumption, switching efficiency and scalability? Also integrate simulation-based learning where students use. To vary parameters like channel and doping. Or gate material and observe. How device performance changes? By my own research methodology in device simulation. Another important aspect is is introducing design tradeoffs only.

Right, so you don’t treat labs as isolated exercises—you’re connecting MOSFET experiments to real issues like leakage and short channel effects. When you’re teaching digital systems or analog VLSI, how do you handle students who struggle to bridge those device-level concepts to circuit-level design?

Dr, your publication record in device simulation and nanoelectronics is quite strong. Thinking about the next few years, where do you see the most fundable research directions in your area? What kind of grants or industry partnerships would you pursue to sustain your lab’s productivity?

Right, so you’re pushing students to analyze, not just observe, and connecting lab work to real-world device physics. On the funding side—your patent and IEEE publications give you a strong base, but how do you plan to scale your nanoelectronics research into a group that attracts both external grants and industry collaboration over the next three years?

Okay, so you link nanoelectronics research to lab work, pushing students to interpret device behavior and experiment with simulation. Now thinking about research sustainability—your patent and IEEE publications give you a strong base, but institutional funding relies on continued output. Where do you see the most fundable directions for your research over the next few years, and what kinds of grants or industry partnerships would you pursue?

Right, so you’re connecting device-level physics from your nanoelectronics research directly to undergrad labs, making students analyze why behaviors matter for low-power design. Now thinking about sustaining institutional research impact—given your patent and strong publication record, how would you build a research group around TFETs or nanoelectronics at VIT, and what’s the funding landscape like for that area over the next few years?

Alright, you bring your research on TFETs and low-power devices straight into teaching, making students interpret real-world implications instead of just running experiments. Now, thinking institutionally—your publication record and patent suggest strong research potential. Where do you see the most fundable directions in nanoelectronics or VLSI over the next three years, and what types of grants or collaborations would you target to sustain that work?

Over the next three years, I see several high impact and fund. Fundable directions. In an electronic and VLSI especially aligned. For global trends in low power. And emerging computing systems.

Over the next three years, I see several high impact and fund. Fundable directions. In an electronic and VLSI especially aligned. For global trends in low power. And emerging computing systems. One major direction is beyond.

Over the next three years, I see several high impact and fund. Fundable directions. In an electronic and VLSI especially aligned. For global trends in low power. And emerging computing systems. One major direction is beyond. Particularly the effects negative capacity in phase and Jensen intellect junctionless transistors. With the growing demand for energy efficient electronics in IoT. And wearable systems funding agencies are actively. Supporting work that reduces. Consumption at the device level.

Over the next three years, I see several high impact and fund. Fundable directions. In an electronic and VLSI especially aligned. For global trends in low power. And emerging computing systems. One major direction is beyond. Particularly the effects negative capacity in phase and Jensen intellect junctionless transistors. With the growing demand for energy efficient electronics in IoT. And wearable systems funding agencies are actively. Supporting work that reduces. Consumption at the device level. A second promising area is nanoelectronic device for sensing application.

Over the next three years, I see several high impact and fund. Fundable directions. In an electronic and VLSI especially aligned. For global trends in low power. And emerging computing systems. One major direction is beyond. Particularly the effects negative capacity in phase and Jensen intellect junctionless transistors. With the growing demand for energy efficient electronics in IoT. And wearable systems funding agencies are actively. Supporting work that reduces. Consumption at the device level. A second promising area is nanoelectronic device for sensing application. Especially biosensors. My recent work on Tfetbased biosensor aligns well with healthcare and environmental monitoring. Which are priority areas for funding bodies due to their societal impact?

Over the next three years, I see several high impact and fund. Fundable directions. In an electronic and VLSI especially aligned. For global trends in low power. And emerging computing systems. One major direction is beyond. Particularly the effects negative capacity in phase and Jensen intellect junctionless transistors. With the growing demand for energy efficient electronics in IoT. And wearable systems funding agencies are actively. Supporting work that reduces. Consumption at the device level. A second promising area is nanoelectronic device for sensing application. Especially biosensors. My recent work on Tfetbased biosensor aligns well with healthcare and environmental monitoring.

Over the next three years, I see several high impact and fund. Fundable directions. In an electronic and VLSI especially aligned. For global trends in low power. And emerging computing systems. One major direction is beyond. Particularly the effects negative capacity in phase and Jensen intellect junctionless transistors. With the growing demand for energy efficient electronics in IoT. And wearable systems funding agencies are actively. Supporting work that reduces. Consumption at the device level. A second promising area is nanoelectronic device for sensing application. Especially biosensors. My recent work on Tfetbased biosensor aligns well with healthcare and environmental monitoring. Which are priority areas for funding bodies due to their societal impact? 3rd I see strong opportunity in hardware for AI and age computing.

Over the next three years, I see several high impact and fund. Fundable directions. In an electronic and VLSI especially aligned. For global trends in low power. And emerging computing systems. One major direction is beyond. Particularly the effects negative capacity in phase and Jensen intellect junctionless transistors. With the growing demand for energy efficient electronics in IoT. And wearable systems funding agencies are actively. Supporting work that reduces. Consumption at the device level. A second promising area is nanoelectronic device for sensing application. Especially biosensors. My recent work on Tfetbased biosensor aligns well with healthcare and environmental monitoring. Which are priority areas for funding bodies due to their societal impact? 3rd I see strong opportunity in hardware for AI and age computing. This includes designing low power VLSI architecture and exploring how emerging. Devices can be integrated into numero for. Neuromorphic. Or in memory computing systems.

Over the next three years, I see several high impact and fund. Fundable directions. In an electronic and VLSI especially aligned. For global trends in low power. And emerging computing systems. One major direction is beyond. Particularly the effects negative capacity in phase and Jensen intellect junctionless transistors. With the growing demand for energy efficient electronics in IoT. And wearable systems funding agencies are actively. Supporting work that reduces. Consumption at the device level. A second promising area is nanoelectronic device for sensing application. Especially biosensors. My recent work on Tfetbased biosensor aligns well with healthcare and environmental monitoring. Which are priority areas for funding bodies due to their societal impact? 3rd I see strong opportunity in hardware for AI and age computing. This includes designing low power VLSI architecture and exploring how emerging. Devices can be integrated into numero for. Neuromorphic. Or in memory computing systems. Funding, funding. Respectively in India, I would target agencies like DSP. Sir for core research grant. Mighty for semiconductor and VLSI focused project. AICTE, RPS, and DRD for applied research.

Over the next three years, I see several high impact and fund. Fundable directions. In an electronic and VLSI especially aligned. For global trends in low power. And emerging computing systems. One major direction is beyond. Particularly the effects negative capacity in phase and Jensen intellect junctionless transistors. With the growing demand for energy efficient electronics in IoT. And wearable systems funding agencies are actively. Supporting work that reduces. Consumption at the device level. A second promising area is nanoelectronic device for sensing application. Especially biosensors. My recent work on Tfetbased biosensor aligns well with healthcare and environmental monitoring. Which are priority areas for funding bodies due to their societal impact? 3rd I see strong opportunity in hardware for AI and age computing. This includes designing low power VLSI architecture and exploring how emerging. Devices can be integrated into numero for. Neuromorphic. Or in memory computing systems. Funding, funding. Respectively in India, I would target agencies like DSP. Sir for core research grant. Mighty for semiconductor and VLSI focused project. AICTE, RPS, and DRD for applied research. I I would also explore international collaboration. Through programs like Indo EU and Indo US research initiatives especially.

Over the next three years, I see several high impact and fund. Fundable directions. In an electronic and VLSI especially aligned. For global trends in low power. And emerging computing systems. One major direction is beyond. Particularly the effects negative capacity in phase and Jensen intellect junctionless transistors. With the growing demand for energy efficient electronics in IoT. And wearable systems funding agencies are actively. Supporting work that reduces. Consumption at the device level. A second promising area is nanoelectronic device for sensing application. Especially biosensors. My recent work on Tfetbased biosensor aligns well with healthcare and environmental monitoring. Which are priority areas for funding bodies due to their societal impact? 3rd I see strong opportunity in hardware for AI and age computing. This includes designing low power VLSI architecture and exploring how emerging. Devices can be integrated into numero for. Neuromorphic. Or in memory computing systems. Funding, funding. Respectively in India, I would target agencies like DSP. Sir for core research grant. Mighty for semiconductor and VLSI focused project. AICTE, RPS, and DRD for applied research. I I would also explore international collaboration. Through programs like Indo EU and Indo US research initiatives especially. Where device level innovation can be linked. System level application.

You’re seeing opportunities in low power and computing systems, and you mentioned aligning to global trends. What specific grant agencies or industry partners would you actually approach for funding, and how would you pitch the institutional value of your research to them?

You started to mention beyond-CMOS directions and global trends, but I didn't catch the rest. What specific grant agencies or industry partners would you actually approach for funding, and how would you pitch your research to show institutional impact?

Over the next three years, I see several high impact and fund. Fundable directions. In an electronic and VLSI especially aligned. For global trends in low power. And emerging computing systems. One major direction is beyond. Particularly the effects negative capacity in phase and Jensen intellect junctionless transistors. With the growing demand for energy efficient electronics in IoT. And wearable systems funding agencies are actively. Supporting work that reduces. Consumption at the device level. A second promising area is nanoelectronic device for sensing application. Especially biosensors. My recent work on Tfetbased biosensor aligns well with healthcare and environmental monitoring. Which are priority areas for funding bodies due to their societal impact? 3rd I see strong opportunity in hardware for AI and age computing. This includes designing low power VLSI architecture and exploring how emerging. Devices can be integrated into numero for. Neuromorphic. Or in memory computing systems. Funding, funding. Respectively in India, I would target agencies like DSP. Sir for core research grant. Mighty for semiconductor and VLSI focused project. AICTE, RPS, and DRD for applied research. I I would also explore international collaboration. Through programs like Indo EU and Indo US research initiatives especially. Where device level innovation can be linked. System level application. In terms of collaboration, I would aim to build interdisciplinary teams. Add into industry collaboration. And academic academic partnerships.

Over the next three years, I see several high impact and fund. Fundable directions. In an electronic and VLSI especially aligned. For global trends in low power. And emerging computing systems. One major direction is beyond. Particularly the effects negative capacity in phase and Jensen intellect junctionless transistors. With the growing demand for energy efficient electronics in IoT. And wearable systems funding agencies are actively. Supporting work that reduces. Consumption at the device level. A second promising area is nanoelectronic device for sensing application. Especially biosensors. My recent work on Tfetbased biosensor aligns well with healthcare and environmental monitoring. Which are priority areas for funding bodies due to their societal impact? 3rd I see strong opportunity in hardware for AI and age computing. This includes designing low power VLSI architecture and exploring how emerging. Devices can be integrated into numero for. Neuromorphic. Or in memory computing systems. Funding, funding. Respectively in India, I would target agencies like DSP. Sir for core research grant. Mighty for semiconductor and VLSI focused project. AICTE, RPS, and DRD for applied research. I I would also explore international collaboration. Through programs like Indo EU and Indo US research initiatives especially. Where device level innovation can be linked. System level application. In terms of collaboration, I would aim to build interdisciplinary teams. Add into industry collaboration. And academic academic partnerships. My approach would. To position research at intersection. Of device innovation, circuit design, and. Application domain. Which not only increases funding quotation, but also ensure. Impact.

You mentioned negative capacitance and junctionless transistors, especially for IoT and wearables, and that agencies are funding device-level efficiency. Which grant agencies or industry partners would you actually approach for these projects, and what makes your work attractive to them?

You mentioned nanoelectronic devices for sensing applications as another promising direction. With industry collaboration being vital at VIT University, how would you bridge the gap between academic research and practical industrial needs in these sensing projects?

Alright, you outlined negative capacitance and junctionless transistors for IoT and wearables, plus TFET-based biosensors for healthcare. Which grant agencies or industry partners would you actually approach for funding, and how would you pitch the practical impact of your work to them?

You mentioned negative capacitance FETs and TFET-based biosensors as fundable directions, especially with their relevance to IoT and healthcare. What specific grant agencies or industry partners would you actually approach for funding, and how would you tailor your proposals to match their priorities?

You started to outline opportunities in negative capacitance, junctionless transistors, and TFET-based biosensors for sensing, especially aligned to IoT and healthcare trends. What specific grant agencies or industry partners would you actually approach for funding, and how would you pitch your research to them to make it stand out?

Right, you highlighted nanoelectronic devices for sensing and hardware for AI as promising research directions, especially with societal impact. Thinking about teaching, how would you bridge the gap between academic research and industrial application in your lab courses or student projects at a place like VIT University?

You mentioned targeting agencies like DST, SERB, MeitY, AICTE, and DRDO, and focusing on device-level efficiency, biosensors, and hardware for AI. Let's look at bridging academia and industry: at VIT, that's a big emphasis. How would you connect your research on nanoelectronic devices or VLSI to industrial application, both in teaching and projects?

Alright, you mentioned targeting DST, SERB, MeitY, and AICTE for core and applied research grants, plus international collaborations. But industry engagement is a big deal at VIT. With your focus on energy-efficient nanoelectronics and biosensors, how would you actually bridge the gap between academic research and industrial application in your teaching or lab projects?

You mentioned targeting DST, SERB, MeitY, and AICTE for core and applied research grants, plus international collaborations. But industry engagement is a big deal at VIT. With your focus on energy-efficient nanoelectronics and hardware for AI, how would you bridge the gap between academic research and industrial application in your teaching or projects?

Alright, you outlined targeting DST, SERB, MeitY, and AICTE for research grants and aiming for interdisciplinary teams and industry collaborations. Given VIT University's emphasis on industry collaboration, how would you bridge the gap between academic research and industrial application in both your teaching and research projects?

Okay, you mentioned targeting DST, SERB, MeitY, and AICTE for core and applied research grants, plus international collaborations. But industry engagement is a big deal at VIT. With your focus on energy-efficient electronics and hardware for AI, how would you bridge the gap between academic research and industrial application in your teaching and projects?

You are absolutely right. Branding the gap between academic research and industry application is critical. Especially VLSI and semiconductor design. I approach this. At 3 levels.

You are absolutely right. Branding the gap between academic research and industry application is critical. Especially VLSI and semiconductor design. I approach this. At 3 levels. Teaching projects and collaboration.

You are absolutely right. Branding the gap between academic research and industry application is critical. Especially VLSI and semiconductor design. I approach this. At 3 levels. Teaching projects and collaboration. In teaching. Course content with industry workflows.

You are absolutely right. Branding the gap between academic research and industry application is critical. Especially VLSI and semiconductor design. I approach this. At 3 levels. Teaching projects and collaboration. In teaching. Course content with industry workflows. For example, in VLSI courses I don't just cover theory. I introduce into students to complete design flow. Specification. RTL design synthesis.

You are absolutely right. Branding the gap between academic research and industry application is critical. Especially VLSI and semiconductor design. I approach this. At 3 levels. Teaching projects and collaboration. In teaching. Course content with industry workflows. For example, in VLSI courses I don't just cover theory. I introduce into students to complete design flow. Specification. RTL design synthesis. Timing analysis and optimization. I also incorporate Ada tools like. Alex Vivardo. Students gain hands on experience that reflects real industry practices. In student projects, I strongly emphasize problem statement. Inspired by real world application.

You are absolutely right. Branding the gap between academic research and industry application is critical. Especially VLSI and semiconductor design. I approach this. At 3 levels. Teaching projects and collaboration. In teaching. Course content with industry workflows. For example, in VLSI courses I don't just cover theory. I introduce into students to complete design flow. Specification. RTL design synthesis. Timing analysis and optimization. I also incorporate Ada tools like. Alex Vivardo. Students gain hands on experience that reflects real industry practices. In student projects, I strongly emphasize problem statement. Inspired by real world application. For instance, instead of generic design I guide. To work on low power circuits for IoT devices. Sensor interface. Or basic AI accelerators.

You are absolutely right. Branding the gap between academic research and industry application is critical. Especially VLSI and semiconductor design. I approach this. At 3 levels. Teaching projects and collaboration. In teaching. Course content with industry workflows. For example, in VLSI courses I don't just cover theory. I introduce into students to complete design flow. Specification. RTL design synthesis. Timing analysis and optimization. I also incorporate Ada tools like. Alex Vivardo. Students gain hands on experience that reflects real industry practices. In student projects, I strongly emphasize problem statement. Inspired by real world application. For instance, instead of generic design I guide. To work on low power circuits for IoT devices. Sensor interface. Or basic AI accelerators. I also encourage design constraints like power. Area in delay so that. Think like. There's not, just like learners.

You are absolutely right. Branding the gap between academic research and industry application is critical. Especially VLSI and semiconductor design. I approach this. At 3 levels. Teaching projects and collaboration. In teaching. Course content with industry workflows. For example, in VLSI courses I don't just cover theory. I introduce into students to complete design flow. Specification. RTL design synthesis. Timing analysis and optimization. I also incorporate Ada tools like. Alex Vivardo. Students gain hands on experience that reflects real industry practices. In student projects, I strongly emphasize problem statement. Inspired by real world application. For instance, instead of generic design I guide. To work on low power circuits for IoT devices. Sensor interface. Or basic AI accelerators. I also encourage design constraints like power. Area in delay so that. Think like. There's not, just like learners. Also try to. Research into projects. Where feasible.

You started to outline your approach to bridging academics and industry, especially in VLSI and semiconductor design. You said you tackle this at three levels—could you elaborate on what those levels are, and how you apply them in your teaching or research projects?

Alright, you outlined those three levels—teaching, projects, and collaboration—but you didn’t get into the specifics. What’s one concrete way you’ve actually brought an industry partner into your classroom or research, and how did it affect student outcomes?

You are absolutely right. Branding the gap between academic research and industry application is critical. Especially VLSI and semiconductor design. I approach this. At 3 levels. Teaching projects and collaboration. In teaching. Course content with industry workflows. For example, in VLSI courses I don't just cover theory. I introduce into students to complete design flow. Specification. RTL design synthesis. Timing analysis and optimization. I also incorporate Ada tools like. Alex Vivardo. Students gain hands on experience that reflects real industry practices. In student projects, I strongly emphasize problem statement. Inspired by real world application. For instance, instead of generic design I guide. To work on low power circuits for IoT devices. Sensor interface. Or basic AI accelerators. I also encourage design constraints like power. Area in delay so that. Think like. There's not, just like learners. Also try to. Research into projects. Where feasible. For example, concept from my work on Tifet or low power device can be translated. Into simplified design problems helping. Understand how Advanced Research concepts. To practical systems. On the collaboration side, I actively look. Industry sponsored Sponsored projects or internships. Guess lectures in workshop by industry squares. Opportunities for student to work. On live problem statements.

You started outlining those three levels—teaching, projects, and collaboration—but you didn’t get into the specifics. What’s one concrete way you’ve actually brought an industry partner into your classroom or research projects, and how did that change outcomes for your students or your team?

You started laying out how you integrate industry workflows into teaching, especially by bringing the full VLSI design flow into student projects. Before we move on, can you share a specific example where you collaborated with an industry partner—either for a student project, guest lecture, or curriculum input—that led to a measurable benefit for your students or research?

Alright, you really embed industry workflows into your teaching and push students to tackle real-world problems. That covers the applied side. Now, how do you see yourself contributing to VIT’s accreditation processes through curriculum enhancement or quality assurance?

Okay, you’ve handled VLSI and digital systems courses with big student groups and pushed for curriculum aligned with industry. Suppose you’re running a theory class with 200 students and slides aren’t allowed—how would you structure a session that keeps everyone engaged and not just passively listening?

Alright, you really embed industry workflows into your teaching and push students to tackle real-world problems. That covers the applied side. Now, how do you see yourself contributing to VIT’s accreditation processes through curriculum enhancement or quality assurance?

You really make sure students get hands-on with industry tools like Vivado, and you push them to tackle real-world problems instead of just textbook designs. For your lab courses, how do you design evaluation methods that actually assess both technical skill and practical competence, not just memorization or routine lab work?

Alright, you really embed industry workflows into your teaching and push students to tackle real-world problems. That covers the applied side. Now, how do you see yourself contributing to VIT’s accreditation processes through curriculum enhancement and quality assurance initiatives?

I see accreditation not just as compliance requirement. But. There's an opportunity to systematically improve at academic quality and outcomes.

I see accreditation not just as compliance requirement. But. There's an opportunity to systematically improve at academic quality and outcomes. From a curriculum enhancement perspective. I would align courses with the outcome based education. Framework required by bodies like N. Neck. This means clearly defining course outcomes and mapping them to program outcomes.

I see accreditation not just as compliance requirement. But. There's an opportunity to systematically improve at academic quality and outcomes. From a curriculum enhancement perspective. I would align courses with the outcome based education. Framework required by bodies like N. Neck. This means clearly defining course outcomes and mapping them to program outcomes. Ensuring that. Subject to attributes. Meaningfully. Uh, to the overall budget attribute. Based on my. Restructuring the analog and mixed signal VLSI curriculum. I contribute to updating syllably. Charging topics like low power design, semiconductor scaling challenges. Hardware for AI. While maintaining strong fundamental. For quality assurance, follow a data-driven approach.

You see accreditation as a chance to systematically improve academic quality, not just a box-ticking exercise. That’s a good perspective. Earlier, you mentioned frequent design reviews and hands-on industry tools for labs. For your lab courses, how do you design evaluation methods that accurately assess both technical skills and practical competencies, rather than just theoretical knowledge?

I see accreditation not just as compliance requirement. But. There's an opportunity to systematically improve at academic quality and outcomes. From a curriculum enhancement perspective. I would align courses with the outcome based education. Framework required by bodies like N. Neck. This means clearly defining course outcomes and mapping them to program outcomes. Ensuring that. Subject to attributes. Meaningfully. Uh, to the overall budget attribute. Based on my. Restructuring the analog and mixed signal VLSI curriculum. I contribute to updating syllably. Charging topics like low power design, semiconductor scaling challenges. Hardware for AI. While maintaining strong fundamental. For quality assurance, follow a data-driven approach. Continuous assessment tool assignment quizzes labs.

I see accreditation not just as compliance requirement. But. There's an opportunity to systematically improve at academic quality and outcomes. From a curriculum enhancement perspective. I would align courses with the outcome based education. Framework required by bodies like N. Neck. This means clearly defining course outcomes and mapping them to program outcomes. Ensuring that. Subject to attributes. Meaningfully. Uh, to the overall budget attribute. Based on my. Restructuring the analog and mixed signal VLSI curriculum. I contribute to updating syllably. Charging topics like low power design, semiconductor scaling challenges. Hardware for AI. While maintaining strong fundamental. For quality assurance, follow a data-driven approach. Continuous assessment tool assignment quizzes labs. See your attendant analysis, student feedback, and result analysis. Based on implement corrective actions. Such modifying teaching methods, adding tutorial sessions. Or redesigning lab experiments to improve learning outcomes.

Alright, you’re aiming for outcome-based education and clear mapping for accreditation. Earlier you mentioned frequent design reviews and hands-on industry tools for labs. For your lab courses, how do you design evaluation methods that accurately assess both technical and practical competencies, not just theoretical knowledge?

I see accreditation not just as compliance requirement. But. There's an opportunity to systematically improve at academic quality and outcomes. From a curriculum enhancement perspective. I would align courses with the outcome based education. Framework required by bodies like N. Neck. This means clearly defining course outcomes and mapping them to program outcomes. Ensuring that. Subject to attributes. Meaningfully. Uh, to the overall budget attribute. Based on my. Restructuring the analog and mixed signal VLSI curriculum. I contribute to updating syllably. Charging topics like low power design, semiconductor scaling challenges. Hardware for AI. While maintaining strong fundamental. For quality assurance, follow a data-driven approach. Continuous assessment tool assignment quizzes labs. See your attendant analysis, student feedback, and result analysis. Based on implement corrective actions. Such modifying teaching methods, adding tutorial sessions. Or redesigning lab experiments to improve learning outcomes. I can also contribute to preparation. Of accreditation documents. Academic audits and internal. It establishing. Project evolution to ensure transportation.

Alright, so you're not just updating the curriculum—you’re mapping course outcomes to program goals and using your research experience to keep topics current. You mentioned a data-driven approach for quality assurance. What kinds of metrics or evidence do you rely on to assess whether your curriculum changes are actually improving student learning or engagement?

Alright, you’re aiming for outcome-based education and clear mapping for accreditation. Earlier you mentioned frequent design reviews and hands-on industry tools for labs. For your lab courses, how do you design evaluation methods that actually assess whether students understand the theory and can apply it practically, not just complete the task?

Okay, accreditation cycles can be demanding. If you joined our department and found that outcome assessment data was inconsistent across courses, how would you approach fixing that?

Okay, so you're not just updating the curriculum—you’re mapping course outcomes to program goals and using your research experience to keep topics current. You mentioned a data-driven approach for quality assurance, like using attendance, quizzes, and feedback to drive improvements. If you found that outcome assessment data was inconsistent across courses, what would be your practical first steps to fix that?

That's a very practical challenge.

That's a very practical challenge. And it often happens when multiple faculty members interpret OB process differently. My my first step would be to standardize the framework.

That's a very practical challenge. And it often happens when multiple faculty members interpret OB process differently. My my first step would be to standardize the framework. I would work with the department to create a common template for. Cop mapping. Assessment Methods. Rubrics for assignment. In exams, this is ensure everyone is measuring outcomes in a consistent way.

You’re right, outcome assessment inconsistencies can undermine accreditation efforts. Given your emphasis on data-driven methods, what’s your practical approach for standardizing assessment tools or rubrics across courses so the data’s actually comparable?

That's a very practical challenge. And it often happens when multiple faculty members interpret OB process differently. My my first step would be to standardize the framework. I would work with the department to create a common template for. Cop mapping. Assessment Methods. Rubrics for assignment. In exams, this is ensure everyone is measuring outcomes in a consistent way. Second, I would focus on faculty alignment and training. Even 1 is small workshops or internal meetings can help ensure that all faculty understand. How to define? Terrible growth outcomes. How to design questions? That actually map to those. How to calculate attendant correctly? I would implement A centralized data collection system. Even if a simple shared spreadsheet or institutional ERP. This avoids variation in calculation methods in. 4th I would conduct a SIM. Simple audit of a few code. But by reviewing question papers, evaluation schemes. An attainment calculations. We can identify where inconsistency. Questions occurring whether in mapping? Assessment, design or data interpretation? Finally, I would introduce the continuous. Improvement loop.

That's a very practical challenge. And it often happens when multiple faculty members interpret OB process differently. My my first step would be to standardize the framework. I would work with the department to create a common template for. Cop mapping. Assessment Methods. Rubrics for assignment. In exams, this is ensure everyone is measuring outcomes in a consistent way. Second, I would focus on faculty alignment and training. Even 1 is small workshops or internal meetings can help ensure that all faculty understand. How to define? Terrible growth outcomes. How to design questions? That actually map to those. How to calculate attendant correctly? I would implement A centralized data collection system. Even if a simple shared spreadsheet or institutional ERP. This avoids variation in calculation methods in. 4th I would conduct a SIM. Simple audit of a few code. But by reviewing question papers, evaluation schemes. An attainment calculations. We can identify where inconsistency. Questions occurring whether in mapping? Assessment, design or data interpretation? Finally, I would introduce the continuous. Improvement loop. Identifying the gap in the attainment. Suggest corrective action. Extra tutorials. Device level. Reevaluate in the next cycle.

Dr, let’s consider an ethical scenario. Imagine a student formally complains that your grading is biased, but at the same time your department head is pressuring you to raise pass rates. How would you handle that situation to balance fairness, academic standards, and institutional expectations?

Right, so you'd start by standardizing rubrics and assessment templates so everyone is measuring outcomes in the same way. But what if your department head disagreed with your approach and insisted on sticking with the current inconsistent methods—how would you handle that situation?

Right, you’d start with a standardized template for rubrics and assessment methods, and get faculty aligned on how to use them. But suppose your department head disagrees and insists on keeping things flexible, saying strict templates stifle academic freedom. How would you handle that pushback while still ensuring consistent quality?

Right, you'd start with standardizing assessment methods and rubrics, plus faculty training and audits to catch inconsistencies. Let me shift gears to an ethical scenario. Imagine a student files a formal complaint alleging your grading is biased, while your department head is pressuring you to improve pass rates. How would you navigate that?

That's a census. Sensitive situation.

That's a census. Sensitive situation. I would handle it with a focus on fairness, transparency, and academic integrity. First, regarding the allegation of. My immediate step would be to review the evaluation process objectively.

That's a census. Sensitive situation. I would handle it with a focus on fairness, transparency, and academic integrity. First, regarding the allegation of. My immediate step would be to review the evaluation process objectively. Since I I use predefined Rubik's and documented markings.

That's fair, it is a pretty sensitive situation. So if you had to decide between sticking to your grading standards and the department head's request for higher pass rates, what would you actually do?

That's a census. Sensitive situation. I would handle it with a focus on fairness, transparency, and academic integrity. First, regarding the allegation of. My immediate step would be to review the evaluation process objectively. Since I I use predefined Rubik's and documented markings. Present the students evaluated answer slip.

That's a census. Sensitive situation. I would handle it with a focus on fairness, transparency, and academic integrity. First, regarding the allegation of. My immediate step would be to review the evaluation process objectively. Since I I use predefined Rubik's and documented markings. Present the students evaluated answer slip. The marking. Used.

That's a census. Sensitive situation. I would handle it with a focus on fairness, transparency, and academic integrity. First, regarding the allegation of. My immediate step would be to review the evaluation process objectively. Since I I use predefined Rubik's and documented markings. Present the students evaluated answer slip. The marking. Used. Comparison with other student script.

That's a census. Sensitive situation. I would handle it with a focus on fairness, transparency, and academic integrity. First, regarding the allegation of. My immediate step would be to review the evaluation process objectively. Since I I use predefined Rubik's and documented markings. Present the students evaluated answer slip. The marking. Used. Comparison with other student script. Anonymous if needed. If if required I would be open a third party evaluation or moderation. Because transparent. Is the best way to address such concerns.

That's a census. Sensitive situation. I would handle it with a focus on fairness, transparency, and academic integrity. First, regarding the allegation of. My immediate step would be to review the evaluation process objectively. Since I I use predefined Rubik's and documented markings. Present the students evaluated answer slip. The marking. Used. Comparison with other student script. Anonymous if needed. If if required I would be open a third party evaluation or moderation. Because transparent. Is the best way to address such concerns. If any genuine error is found, I would correctly. It promptly. 2nd about the pressure to improve the pass rates.

That's a census. Sensitive situation. I would handle it with a focus on fairness, transparency, and academic integrity. First, regarding the allegation of. My immediate step would be to review the evaluation process objectively. Since I I use predefined Rubik's and documented markings. Present the students evaluated answer slip. The marking. Used. Comparison with other student script. Anonymous if needed. If if required I would be open a third party evaluation or moderation.

That's a census. Sensitive situation. I would handle it with a focus on fairness, transparency, and academic integrity. First, regarding the allegation of. My immediate step would be to review the evaluation process objectively. Since I I use predefined Rubik's and documented markings. Present the students evaluated answer slip. The marking. Used. Comparison with other student script. Anonymous if needed.

Alright, so your focus is on fairness and transparency, starting by reviewing your own evaluation process. And if the department head disagreed with your approach and insisted you change your grading to boost pass rates, what would you actually do?

That's a census. Sensitive situation. I would handle it with a focus on fairness, transparency, and academic integrity. First, regarding the allegation of. My immediate step would be to review the evaluation process objectively. Since I I use predefined Rubik's and documented markings. Present the students evaluated answer slip. The marking. Used. Comparison with other student script. Anonymous if needed. If if required I would be open a third party evaluation or moderation. Because transparent. Is the best way to address such concerns. If any genuine error is found, I would correctly. It promptly. 2nd about the pressure to improve the pass rates. I would respectfully maintain the standard. Cannot be compromised. However, improving results does not. Necessarily. Main lowering quality. Instead I will focus. Providing remedial classes or doubt clearing session. Offering additional assignment or reassessment opportunities as per. Identifying learning gaps only through continuous assessment. I would also communicate this case. With the department. That my approach to improve student performance. 3rd Turning not by inflating rates.

Alright, you start by reviewing your process and rely on predefined rubrics and documented marking to ensure fairness. But suppose your department head disagreed with your approach and insisted you change your grading to boost pass rates — what would you actually do?

Alright, you rely on documented marking and rubrics for transparency when handling grading complaints. If your department head disagreed with your approach and insisted you change your grading to boost pass rates, what would you actually do?

You rely on predefined rubrics and documented marking to keep things transparent, and you'd review the evaluation process with the student. But if your department head disagreed and insisted you change your grading to boost pass rates, what would you actually do?

You rely on documented marking and rubrics for transparency when handling grading complaints. Suppose your department head disagreed and insisted you change your grading to boost pass rates—what would you actually do in that situation?

You rely on documented rubrics and anonymized scripts to show fairness, which makes sense. If your department head disagreed and insisted you change your grading to boost pass rates, what would you actually do?

Alright, you rely on documented rubrics and anonymized scripts to show fairness, and you're open to moderation if needed. But if your department head disagreed with your approach and insisted you change your grading to boost pass rates, what would you actually do?

You rely on documented rubrics and anonymized scripts to show fairness, and you're open to moderation if needed. Now, if the department head disagreed with your approach and insisted you change your grading to boost pass rates, what would you actually do?

Alright, so you’d use a common template for rubrics and assessment, then train faculty and audit results to tighten consistency. Earlier, you mentioned incorporating tools like Vivado and guiding industry-inspired student projects. Can you give a concrete example—maybe a company, a partnership, or a specific project—where your industry connections directly led to internships or placements for your students?

Alright, you’re pretty active about aligning your teaching and projects with real industry needs—students get hands-on with tools and tackle practical problems. Earlier you mentioned bringing in guest lectures and industry-sponsored projects. Can you name specific companies or partners you've collaborated with, or any concrete plans you’d pursue at VIT to build those connections for student internships or placements?

So far, most of my industry interaction has been. Indirect rather than formal MOU based collaboration. For example, I aligned my teaching and labs. The industry in this is standard tools like. Xilinx Vivo. And design flows used in companies such as Intel, Qualcomm in Texas Instruments. So did it in students attend on relevant. As at the institutional level. I have participated in inviting US lectures and teaching. Technical session typically. Throw alumni or professional networks. So this. Were not always formal long term party partnerships.

So far, most of my industry interaction has been. Indirect rather than formal MOU based collaboration. For example, I aligned my teaching and labs. The industry in this is standard tools like. Xilinx Vivo. And design flows used in companies such as Intel, Qualcomm in Texas Instruments. So did it in students attend on relevant. As at the institutional level. I have participated in inviting US lectures and teaching. Technical session typically. Throw alumni or professional networks. So this. Were not always formal long term party partnerships. At VIT, however, I would take a more structured and proactive approach. First, I would target Ed and semiconductor companies like Cadence. Design systems and synopsis for toolbased workshop certification. And possible academic licenses. Second, I would try to step. This is industry supported mini projects and internships. Especially with companies working in embedded system, we. By design and semiconductor. And I would leverage alumni. Which are particularly strong at institute. VIT. Bring in mentorship, internship and placement. Ref. For 4th I would. Joint researchers. Projects where industry. Problem like. Of our design challenges. Cancer interface can be. Converted into Student. Or funded systems. So while my past. Operation have been more academic and tool oriented. My plan at VIT is to build formal output. Driven Partnership. Debt directly support Internet. Skill development placements.

Right, so your industry connections so far have mostly come through alumni and professional networks, plus you’ve matched your teaching to workflows used at places like Intel and Qualcomm. If you were at VIT, what concrete steps would you take to turn those informal connections into formal partnerships or placement pipelines for students?

The statistics in scenario in. This meaningful industry exposure.

The statistics in scenario in. This meaningful industry exposure. Doesn't have to wait for formal MO us. If formal parties. Partnerships or not? Immediately available. I would fo. From creating. Like experiences within the academic environment. First, I would design for. Process around actual industry. Using tools examining a student would go through. The complete cycle artist design, simulations, synthesis, timing analysis. And optimization so. They understand how real chip design flow works.

Alright, you’re saying meaningful industry exposure is key. Since you’ve matched your labs to what companies like Intel and TI use, but haven’t had formal partnerships yet, what’s one concrete step you’d take right away at VIT—before any MOUs—to make sure students got firsthand experience with current industry tools or workflows?

The statistics in scenario in. This meaningful industry exposure. Doesn't have to wait for formal MO us. If formal parties. Partnerships or not? Immediately available. I would fo. From creating. Like experiences within the academic environment. First, I would design for. Process around actual industry. Using tools examining a student would go through. The complete cycle artist design, simulations, synthesis, timing analysis. And optimization so. They understand how real chip design flow works. Second, I would. Publicly up. Open industry. There's many companies. Intel Texas Instruments. And NVIDIA Public. Design guides.

The statistics in scenario in. This meaningful industry exposure. Doesn't have to wait for formal MO us. If formal parties. Partnerships or not? Immediately available. I would fo. From creating. Like experiences within the academic environment. First, I would design for. Process around actual industry. Using tools examining a student would go through. The complete cycle artist design, simulations, synthesis, timing analysis. And optimization so. They understand how real chip design flow works. Second, I would. Publicly up. Open industry. There's many companies. Intel Texas Instruments. And NVIDIA Public. Design guides. Application note. And training materials. I integrate these into assignments and case studies so student work on gel stick problem statements.

The statistics in scenario in. This meaningful industry exposure. Doesn't have to wait for formal MO us. If formal parties. Partnerships or not? Immediately available. I would fo. From creating. Like experiences within the academic environment. First, I would design for. Process around actual industry. Using tools examining a student would go through. The complete cycle artist design, simulations, synthesis, timing analysis. And optimization so. They understand how real chip design flow works. Second, I would. Publicly up. Open industry. There's many companies. Intel Texas Instruments. And NVIDIA Public. Design guides. Application note. And training materials. I integrate these into assignments and case studies so student work on gel stick problem statements. That I would implement project bets learning with constants.

The statistics in scenario in. This meaningful industry exposure. Doesn't have to wait for formal MO us. If formal parties. Partnerships or not? Immediately available. I would fo. From creating. Like experiences within the academic environment. First, I would design for. Process around actual industry. Using tools examining a student would go through. The complete cycle artist design, simulations, synthesis, timing analysis. And optimization so. They understand how real chip design flow works. Second, I would. Publicly up. Open industry. There's many companies. Intel Texas Instruments. And NVIDIA Public. Design guides. Application note. And training materials. I integrate these into assignments and case studies so student work on gel stick problem statements. That I would implement project bets learning with constants. Instead of project. I would define problem with specification signal. To industry power delay. And cause constraints.

The statistics in scenario in. This meaningful industry exposure. Doesn't have to wait for formal MO us. If formal parties. Partnerships or not? Immediately available. I would fo. From creating. Like experiences within the academic environment. First, I would design for. Process around actual industry. Using tools examining a student would go through. The complete cycle artist design, simulations, synthesis, timing analysis. And optimization so. They understand how real chip design flow works. Second, I would. Publicly up. Open industry. There's many companies. Intel Texas Instruments. And NVIDIA Public. Design guides. Application note. And training materials. I integrate these into assignments and case studies so student work on gel stick problem statements. That I would implement project bets learning with constants. Instead of project. I would define problem with specification signal. To industry power delay. And cause constraints. So a student learn trade-offs and optimization.

The statistics in scenario in. This meaningful industry exposure. Doesn't have to wait for formal MO us. If formal parties. Partnerships or not? Immediately available. I would fo. From creating. Like experiences within the academic environment. First, I would design for. Process around actual industry. Using tools examining a student would go through. The complete cycle artist design, simulations, synthesis, timing analysis. And optimization so. They understand how real chip design flow works. Second, I would. Publicly up. Open industry. There's many companies. Intel Texas Instruments. And NVIDIA Public. Design guides. Application note. And training materials. I integrate these into assignments and case studies so student work on gel stick problem statements. That I would implement project bets learning with constants. Instead of project. I would define problem with specification signal. To industry power delay. And cause constraints. So a student learn trade-offs and optimization. For organized industry. Informal industry interactions. Invite Ting alumni for virtual talks. Post. Jobs in encouraging participation in hecatons and design contents.

The statistics in scenario in. This meaningful industry exposure. Doesn't have to wait for formal MO us. If formal parties. Partnerships or not? Immediately available. I would fo. From creating. Like experiences within the academic environment. First, I would design for. Process around actual industry. Using tools examining a student would go through. The complete cycle artist design, simulations, synthesis, timing analysis. And optimization so. They understand how real chip design flow works. Second, I would. Publicly up. Open industry. There's many companies. Intel Texas Instruments. And NVIDIA Public. Design guides. Application note. And training materials. I integrate these into assignments and case studies so student work on gel stick problem statements. That I would implement project bets learning with constants. Instead of project. I would define problem with specification signal. To industry power delay. And cause constraints. So a student learn trade-offs and optimization. For organized industry. Informal industry interactions. Invite Ting alumni for virtual talks. Post. Jobs in encouraging participation in hecatons and design contents. Please provide valuable exposure.

The statistics in scenario in. This meaningful industry exposure. Doesn't have to wait for formal MO us. If formal parties. Partnerships or not? Immediately available. I would fo. From creating. Like experiences within the academic environment. First, I would design for. Process around actual industry. Using tools examining a student would go through. The complete cycle artist design, simulations, synthesis, timing analysis. And optimization so. They understand how real chip design flow works. Second, I would. Publicly up. Open industry. There's many companies. Intel Texas Instruments. And NVIDIA Public. Design guides. Application note. And training materials. I integrate these into assignments and case studies so student work on gel stick problem statements. That I would implement project bets learning with constants. Instead of project. I would define problem with specification signal. To industry power delay. And cause constraints. So a student learn trade-offs and optimization. For organized industry. Informal industry interactions. Invite Ting alumni for virtual talks. Post. Jobs in encouraging participation in hecatons and design contents. Please provide valuable exposure. For fifth, I would encourage students to build a strong perform. GitHub project. Design reports and documented. Simulations. So they can demonstrate their skill during placements.

The statistics in scenario in. This meaningful industry exposure. Doesn't have to wait for formal MO us. If formal parties. Partnerships or not? Immediately available. I would fo. From creating. Like experiences within the academic environment. First, I would design for. Process around actual industry. Using tools examining a student would go through. The complete cycle artist design, simulations, synthesis, timing analysis. And optimization so. They understand how real chip design flow works. Second, I would. Publicly up. Open industry. There's many companies. Intel Texas Instruments. And NVIDIA Public. Design guides. Application note. And training materials. I integrate these into assignments and case studies so student work on gel stick problem statements. That I would implement project bets learning with constants. Instead of project. I would define problem with specification signal. To industry power delay. And cause constraints. So a student learn trade-offs and optimization. For organized industry. Informal industry interactions. Invite Ting alumni for virtual talks. Post. Jobs in encouraging participation in hecatons and design contents. Please provide valuable exposure. For fifth, I would encourage students to build a strong perform. GitHub project. Design reports and documented. Simulations. So they can demonstrate their skill during placements. Finally. Would align evaluation with skill bets outcomes. Not just. Is ensuring students graduate with the. Competencies. That match industry expectations.

Okay, so you’d simulate the industry workflow in your courses, even without formal partnerships, so students get hands-on with tools and processes they’ll see on the job. And you mentioned using real chip design flows like synthesis and timing analysis. If you had to prioritize—what’s one skill or tool you’d make absolutely mandatory for VLSI students to master before graduation, and why?

Okay, Dr, now I’d like to verify some key skills for this role. Let’s start with image processing. Say you’re teaching a lab where students are using MATLAB to implement edge detection. If their results are noisy or inconsistent, how would you guide them to diagnose and improve their output?

You said you’d use open industry resources like application notes and training guides from Intel, TI, and Nvidia, plus simulate real design flows so students get hands-on even without formal partnerships. That’s pretty resourceful. Now, switching to embedded and communication—if a student is designing a wireless sensor node for an IoT project, what would you tell them is the most critical challenge in ensuring reliable communication, and how would you have them address it?

Right, so even without formal MOUs, you’d use real industry design flows and integrate public resources like application notes into assignments. Let’s switch to embedded and communication skills. Suppose a student is struggling to debug an SPI interface between a microcontroller and a sensor—what’s your step-by-step approach to helping them find the root cause?

Right, so you're implementing realistic design flows and using open industry resources to keep students current, even without formal partnerships. Let's switch to teaching and academic skills. When you're introducing a tough concept in class—say, device scaling challenges—how do you make sure students actually grasp it, especially those struggling with the fundamentals?

You said you'd set up assignments and project-based learning around real industry specs, using tools and public resources—so students see actual workflows and constraints. Let’s switch to image processing. If you’re teaching a lab where students use MATLAB for edge detection and their results are noisy or inconsistent, what specific steps do you have them take to diagnose and resolve the issue?

You’d use industry guides, application notes, and case studies from companies like Intel or Nvidia, plus organize alumni talks and hackathons so students get exposure even without formal MOUs. Okay, let’s switch to your ability to teach theory and lab courses. When a student struggles to connect theoretical concepts to their lab results—say, they can’t explain why their filter design doesn’t match expected frequency response—how do you help them bridge that gap?

Alright, you’d use real chip design cycles and public application notes to create industry-like assignments, plus alumni talks and hackathons for exposure. Let’s talk about student evaluation and exam responsibilities. When you’re designing a practical exam for a VLSI or embedded lab, how do you ensure the assessment actually measures both conceptual understanding and hands-on skill, not just rote memorization?

You talked about students building portfolios with GitHub projects and documented simulations, plus using industry guides and hackathons. Let’s switch gears—when you’re teaching image processing, what’s your go-to strategy for helping students grasp the practical challenges of implementing algorithms on real hardware, not just in simulation?

You said you'd use public industry design guides and application notes for assignments, plus alumni talks and hackathons, so students get real-world exposure even without formal partnerships. Let's switch gears—when you're teaching image processing, what’s one hands-on lab experiment you use to help students understand noise reduction, and how do you make sure they actually grasp the underlying algorithm?

Of the hands on lab experiment for teaching noise reduction. Image denoising you. Different filtering techniques. Particularly comparing mean, Gaussian and median filters.

Of the hands on lab experiment for teaching noise reduction. Image denoising you. Different filtering techniques. Particularly comparing mean, Gaussian and median filters. In the lab, I would give students a. Grace image and then ask them to intentionally add different types of noise. For example, salt and pepper. Send box then using. A tool like Matlab or Python open. The apply.

Of the hands on lab experiment for teaching noise reduction. Image denoising you. Different filtering techniques. Particularly comparing mean, Gaussian and median filters. In the lab, I would give students a. Grace image and then ask them to intentionally add different types of noise. For example, salt and pepper. Send box then using. A tool like Matlab or Python open. The apply. Mean filter Gaussian filter meet DN filter.

Of the hands on lab experiment for teaching noise reduction. Image denoising you. Different filtering techniques. Particularly comparing mean, Gaussian and median filters. In the lab, I would give students a. Grace image and then ask them to intentionally add different types of noise. For example, salt and pepper. Send box then using. A tool like Matlab or Python open. The apply. Mean filter Gaussian filter meet DN filter. The key part is not just applying filters, but comparing their effectiveness.

Of the hands on lab experiment for teaching noise reduction. Image denoising you. Different filtering techniques. Particularly comparing mean, Gaussian and median filters. In the lab, I would give students a. Grace image and then ask them to intentionally add different types of noise. For example, salt and pepper. Send box then using. A tool like Matlab or Python open. The apply. Mean filter Gaussian filter meet DN filter. The key part is not just applying filters, but comparing their effectiveness. For instance. To observe that median filtering works better. For salt, salt and pepper noise. While Gaussian filtering is more. 00 noise. To ensure they truly understand the underlying algorithm. I do a few things.

Of the hands on lab experiment for teaching noise reduction. Image denoising you. Different filtering techniques. Particularly comparing mean, Gaussian and median filters. In the lab, I would give students a. Grace image and then ask them to intentionally add different types of noise. For example, salt and pepper. Send box then using. A tool like Matlab or Python open. The apply. Mean filter Gaussian filter meet DN filter. The key part is not just applying filters, but comparing their effectiveness. For instance. To observe that median filtering works better. For salt, salt and pepper noise. While Gaussian filtering is more. 00 noise. To ensure they truly understand the underlying algorithm. I do a few things. 1st I ask. Them to manually compute filtering on a small matrix. Like 3 by 3.

Of the hands on lab experiment for teaching noise reduction. Image denoising you. Different filtering techniques. Particularly comparing mean, Gaussian and median filters. In the lab, I would give students a. Grace image and then ask them to intentionally add different types of noise. For example, salt and pepper. Send box then using. A tool like Matlab or Python open. The apply. Mean filter Gaussian filter meet DN filter. The key part is not just applying filters, but comparing their effectiveness. For instance. To observe that median filtering works better. For salt, salt and pepper noise. While Gaussian filtering is more. 00 noise. To ensure they truly understand the underlying algorithm. I do a few things. 1st I ask. Them to manually compute filtering on a small matrix. Like 3 by 3. This helps them understand how convolution works. Then treating it as. Second, I analyze.

Of the hands on lab experiment for teaching noise reduction. Image denoising you. Different filtering techniques. Particularly comparing mean, Gaussian and median filters. In the lab, I would give students a. Grace image and then ask them to intentionally add different types of noise. For example, salt and pepper. Send box then using. A tool like Matlab or Python open. The apply. Mean filter Gaussian filter meet DN filter. The key part is not just applying filters, but comparing their effectiveness. For instance. To observe that median filtering works better. For salt, salt and pepper noise. While Gaussian filtering is more. 00 noise. To ensure they truly understand the underlying algorithm. I do a few things. 1st I ask. Them to manually compute filtering on a small matrix. Like 3 by 3. This helps them understand how convolution works. Then treating it as. Second, I analyze. In best reporting. Where they must explain. Why a particular filter performed better? What happens to edge the tails?

You mentioned teaching noise reduction by comparing mean, Gaussian, and median filters. When students run those experiments, how do you check if they actually understand why the median filter works better for salt-and-pepper noise, versus just seeing smoother images?

Of the hands on lab experiment for teaching noise reduction. Image denoising you. Different filtering techniques. Particularly comparing mean, Gaussian and median filters. In the lab, I would give students a. Grace image and then ask them to intentionally add different types of noise. For example, salt and pepper. Send box then using. A tool like Matlab or Python open. The apply. Mean filter Gaussian filter meet DN filter. The key part is not just applying filters, but comparing their effectiveness. For instance. To observe that median filtering works better. For salt, salt and pepper noise. While Gaussian filtering is more. 00 noise. To ensure they truly understand the underlying algorithm. I do a few things. 1st I ask. Them to manually compute filtering on a small matrix. Like 3 by 3. This helps them understand how convolution works. Then treating it as. Second, I analyze. In best reporting. Where they must explain. Why a particular filter performed better? What happens to edge the tails? That trade between noise reduction and image blurring. Ryan introduced quantitative evaluations such as. Calculating metrics like me. Square peak signal to noise ratio. So they can objectively compare results. Five. Finally, I include a short. Vaibhav, our discussion where? As conceptual questions. Why does? The median filtering. Which is better and? What is? For kernel size.

Okay, so you have students add salt and pepper or Gaussian noise, then run mean, Gaussian, and median filters in Matlab or Python. When they finish, how do you check if students actually understand why the median filter works better for salt and pepper noise compared to the others?

You mentioned students working through real chip design flow and integrating published guides into assignments, plus building portfolios for skill-based outcomes. Switching topics—when you’re guiding student projects, how do you balance letting them experiment versus steering them toward publishable research or practical deliverables?

Alright, so you have students add noise and compare mean, Gaussian, and median filters using Matlab or Python, and you make sure they evaluate effectiveness. Now, shifting to embedded systems and communication—when you’re teaching a lab on UART or SPI interfacing, what’s a common mistake students make, and how do you get them to actually troubleshoot it instead of just guessing?

Right, so you’ve got students working with industry-standard tools and real chip design flows, plus using public guides and alumni for exposure. Now, shifting to embedded systems and communication—when you’re teaching embedded topics, how do you make sure students understand both the hardware and software interface, especially when you’re running lab sessions?

Right, so you have them manually compute filtering on a small matrix to make the algorithm concrete. Now for embedded and communication: when you teach microcontroller interfacing, what's one specific lab or project that helps students understand real-world communication protocols like SPI or I2C?

Alright, you’d pull from industry guides and case studies, set up project-based learning with real constraints, and bring in alumni talks—even without formal MOUs, students would still get relevant exposure. Now, when you’re teaching embedded systems and communication, what’s a concrete lab experiment you use to help students understand microcontroller interfacing, and how do you make sure they actually get the data flow and protocol details?

You mentioned integrating industry guides and alumni talks, plus project-based learning with real constraints, so students get meaningful exposure even without formal partnerships. Switching to embedded and communication—when you're teaching microcontroller interfacing, what's one specific experiment or project you assign that helps students bridge theory and hands-on skills?

Alright, you’d make sure students get industry exposure by using real chip design flows, published guides, alumni talks, and hackathons, plus aligning evaluation with skill-based competencies. Switching topics, when you’re teaching embedded and communication systems, what’s one lab experiment you use to demonstrate UART or SPI interfacing, and how do you make sure students actually understand the signal-level details—not just code?

A very creative experiment. Web experiment I used. You are interfacing between microcontroller and PC. Or between two microcontrollers. In this. Exploit Student user controller. Already know, you know. Similar. And established serial communication with PC.

A very creative experiment. Web experiment I used. You are interfacing between microcontroller and PC. Or between two microcontrollers. In this. Exploit Student user controller. Already know, you know. Similar. And established serial communication with PC. With the URT. They write a simple program to transmit and receive data.

A very creative experiment. Web experiment I used. You are interfacing between microcontroller and PC. Or between two microcontrollers. In this. Exploit Student user controller. Already know, you know. Similar. And established serial communication with PC. With the URT. They write a simple program to transmit and receive data. Such a sending sensor will. And. To the output on a serial monitor. To extend this, I sometimes set up microcontroller to microcontroller communication with. One connect as a transmitter and other act as a. This makes the communication process more complete. Now to ensure. They understand signal level details and not just word. I focus on a few key aspects.

A very creative experiment. Web experiment I used. You are interfacing between microcontroller and PC. Or between two microcontrollers. In this. Exploit Student user controller. Already know, you know. Similar. And established serial communication with PC. With the URT. They write a simple program to transmit and receive data. Such a sending sensor will. And. To the output on a serial monitor.

A very creative experiment. Web experiment I used. You are interfacing between microcontroller and PC. Or between two microcontrollers. In this. Exploit Student user controller. Already know, you know. Similar. And established serial communication with PC. With the URT. They write a simple program to transmit and receive data. Such a sending sensor will. And. To the output on a serial monitor. To extend this, I sometimes set up microcontroller to microcontroller communication with. One connect as a transmitter and other act as a. This makes the communication process more complete. Now to ensure. They understand signal level details and not just word. I focus on a few key aspects. First, make them study the. Frameature. Is start with. Database parity and stopbit and ask them to relate.

A very creative experiment. Web experiment I used. You are interfacing between microcontroller and PC. Or between two microcontrollers. In this. Exploit Student user controller. Already know, you know. Similar. And established serial communication with PC. With the URT. They write a simple program to transmit and receive data. Such a sending sensor will. And. To the output on a serial monitor. To extend this, I sometimes set up microcontroller to microcontroller communication with. One connect as a transmitter and other act as a. This makes the communication process more complete. Now to ensure. They understand signal level details and not just word. I focus on a few key aspects. First, make them study the. Frameature. Is start with. Database parity and stopbit and ask them to relate. To what is. Actually being transmitted.

A very creative experiment. Web experiment I used. You are interfacing between microcontroller and PC. Or between two microcontrollers. In this. Exploit Student user controller. Already know, you know. Similar. And established serial communication with PC. With the URT. They write a simple program to transmit and receive data. Such a sending sensor will. And. To the output on a serial monitor. To extend this, I sometimes set up microcontroller to microcontroller communication with. One connect as a transmitter and other act as a. This makes the communication process more complete. Now to ensure. They understand signal level details and not just word. I focus on a few key aspects. First, make them study the. Frameature. Is start with. Database parity and stopbit and ask them to relate. To what is. Actually being transmitted. Second, I use instruments like a logic analyzer or. So a student can. 30% national.

You had students work through the full design cycle—simulation, synthesis, timing analysis—so they see how chip design really happens. For research publications, can you walk me through one paper you published in a reputed journal, and explain how you structured the study to ensure clarity and impact for reviewers?

A very creative experiment. Web experiment I used. You are interfacing between microcontroller and PC. Or between two microcontrollers. In this. Exploit Student user controller. Already know, you know. Similar. And established serial communication with PC. With the URT. They write a simple program to transmit and receive data. Such a sending sensor will. And. To the output on a serial monitor. To extend this, I sometimes set up microcontroller to microcontroller communication with. One connect as a transmitter and other act as a. This makes the communication process more complete. Now to ensure. They understand signal level details and not just word. I focus on a few key aspects. First, make them study the. Frameature. Is start with. Database parity and stopbit and ask them to relate. To what is. Actually being transmitted. Second, I use instruments like a logic analyzer or. So a student can. 30% national. They can see how bits are transmitted over time, which has. Connected. Theory with actual.

You set up UART interfacing between microcontrollers and PCs, and make students write their own transmit and receive programs. That covers the coding—but how do you get them to actually visualize the signal-level communication? Do you bring in logic analyzers or oscilloscopes, or do you rely on simulation?

You set up UART interfacing and have students code the transmit and receive routines—so they get practical exposure. But how do you make sure they actually visualize the signal-level details? Do you have them use an oscilloscope, logic analyzer, or some other method to see what's happening on the lines?

You set up UART communication between microcontrollers and PCs, and get students coding transmit and receive routines. To make sure they understand the signal-level details, what do you do—do you have them look at waveforms with an oscilloscope, or do you use logic analyzers, or something else?

You make students document their projects and simulations so they can show off their skills for placements, even without formal MOUs. Now, let’s talk about research publications. Walk me through a paper you published in a reputed journal—what was the main research question, and what was the toughest part about getting it accepted?

You said you'd bring in real chip design flows, public guides, and alumni talks to keep things practical even without formal MOUs. Now, shifting gears—when it comes to guiding student research projects, what approach do you use to help students move from a basic idea to a publishable paper, especially if they're struggling to define a clear research question?

You set up UART experiments where students use logic analyzers to see the actual bits and frame structure—that’s how they really connect code to the signal level. Now, thinking about teaching theory and lab courses, what’s one way you handle students who struggle with lab concepts but do well in written exams?

You have students use a logic analyzer to visualize bit transmission and frame structure—so they really connect theory to the physical signals. Now, when teaching theory and lab courses, how do you handle students who struggle with the math behind signal processing or device modeling? What’s your approach to make sure they don’t just memorize formulas, but actually understand the reasoning?

That's a common challenge, especially in a subject like signal processing.

That's a common challenge, especially in a subject like signal processing. Or device modeling, where the math can feel abstract.

That's a common challenge, especially in a subject like signal processing. Or device modeling, where the math can feel abstract. My approach is to connect the mathematics. To physical intuition.

You talked about creating realistic lab experiences and using industry-standard tools so students get practical exposure even without formal MOUs. Now, for student evaluation and exam responsibilities, walk me through how you handle designing and grading a lab-based exam to make sure it's fair and accurately assesses both practical skills and conceptual understanding.

You make students manually apply filters and analyze results, plus you have them explain trade-offs and calculate metrics like mean square error. That's solid for image processing. Now, for research publications in reputed journals, walk me through a paper you've published—what was your main contribution, and how did you ensure it met the standards of a top-tier journal?

You connect math to physical intuition so students don’t just memorize formulas for signal processing or device modeling. Now, thinking about guiding student research projects—what’s your strategy for helping students frame a research question that’s novel enough for publication in a reputed journal, but still achievable with undergraduate resources?

You connect the math to physical intuition so students don’t just memorize formulas for signal processing or device modeling. Now, thinking about guiding student research projects—what’s your strategy for helping undergraduates pick research topics that are both achievable and meaningful, given limited lab resources?

That's an important aspect. Of mentoring, especially at undergraduate level where time background and. Unlimited. Triggered to balance. Pretty learning value and relevance.

That's an important aspect. Of mentoring, especially at undergraduate level where time background and. Unlimited. Triggered to balance. Pretty learning value and relevance. 1st I start by understanding. Strength and interest.

That's an important aspect. Of mentoring, especially at undergraduate level where time background and. Unlimited. Triggered to balance. Pretty learning value and relevance. 1st I start by understanding. Strength and interest. Whether they are more inclined toward coding? Circuit design or theory?

Alright, you’re careful about balancing learning value and relevance in undergraduate mentoring, so students don’t just pick topics that are too ambitious or shallow. Now, for student evaluation and exam responsibilities—how do you handle cases where grading criteria need to be clarified or updated mid-semester, especially if students are already working on assignments?

That's an important aspect. Of mentoring, especially at undergraduate level where time background and. Unlimited. Triggered to balance. Pretty learning value and relevance. 1st I start by understanding. Strength and interest. Whether they are more inclined toward coding? Circuit design or theory? This helps in narrowing down topics. That they can realistically handle. The second is the problem.

That's an important aspect. Of mentoring, especially at undergraduate level where time background and. Unlimited. Triggered to balance. Pretty learning value and relevance. 1st I start by understanding. Strength and interest. Whether they are more inclined toward coding? Circuit design or theory? This helps in narrowing down topics. That they can realistically handle. The second is the problem. Is instead of. Very very bored. Cutting edge topics directly.

Alright, so you start by understanding each student's strengths and interests, and you balance learning value with what's practical given limited lab resources. Now, when it comes to exam responsibilities, how do you ensure your evaluation process is fair and transparent, especially for subjective questions or project assessments?

Alright, so you start by figuring out each student's strengths and interests, and tailor their research topics so they're practical given limited resources. Now, when it comes to exam responsibilities, how do you ensure your question papers and evaluation methods are fair, challenging, and aligned with the course outcomes—not just focused on rote recall?

Alright, you tailor topics to match student strengths and keep them realistic for the resources on hand. Now, for student evaluation and exam-related responsibilities—when you’re setting or grading exams, how do you make sure your questions really test conceptual understanding, not just rote memorization?

Alright, you start by figuring out each student's strengths and interests, and tailor their research topics so they're practical given limited resources. Now, when it comes to exam responsibilities—how do you ensure your question papers actually test both conceptual understanding and applied skills, rather than just rote memorization?

That's critical responsibility and. I designed questions.

That's critical responsibility and. I designed questions. Deliberately. Roknabai domne togna.

That's critical responsibility and. I designed questions. Deliberately. Roknabai domne togna. Dominic.

You were saying you design questions thoughtfully for exams. Let's shift to your research publications. Can you share one paper you published in a reputed journal, and what makes its contribution stand out in your field?

Mm-hmm.

You were saying you design questions deliberately to avoid rote memorization. Can you give one example of a question from your exam papers that tests applied skills in image processing, and explain how you check if students really understand the answer?

Certain here is. Application based question. I typically ask in pro. Sing Question. Agree. Scale images corrupted with salt and pepper noise. You are. Mean filter, Gaussian filter and median filter. Which field do you choose and why?

Certain here is. Application based question. I typically ask in pro. Sing Question. Agree. Scale images corrupted with salt and pepper noise. You are. Mean filter, Gaussian filter and median filter. Which field do you choose and why? Explain what? Will happen to the edges other. Two filters are used. If the kernel site. Increase How will it affect noise removal and. Quality.

Alright, we're wrapping up. Is there anything you'd like to ask about the role or the team before we finish?

Alright, you gave an example where students have to decide which filter to use with salt and pepper noise, explain edge effects, and discuss kernel size. Before we wrap up, Dr., is there anything you'd like to ask about the role or the team?

Yes, absolutely.

Yes, absolutely. I do have few question.

Yes, absolutely. I do have few question. First I'd like like to understand the. Ecosystem within the department.

Of course, Dr. Go ahead—what would you like to know about the role or the team?

Yes, absolutely. I do have few question. First I'd like like to understand the. Ecosystem within the department. Are there active risk? Semiconductor device. Or embedded systems. And how? Establishing encouragement faculty. 2nd. I'm interested. Interested. In knowing about funding and support for research proposal. Does business provide seat funding or support for applying that to agencies like DSD or Curb?

Yes, absolutely. I do have few question. First I'd like like to understand the. Ecosystem within the department. Are there active risk? Semiconductor device. Or embedded systems. And how? Establishing encouragement faculty. 2nd. I'm interested. Interested. In knowing about funding and support for research proposal.

Mm-hmm.

You want a sense of the department ecosystem. At VIT, the department is known for a strong mix of research activity and industry engagement—faculty collaborate across specializations and there are regular seminars, workshops, and student-led clubs that promote both academic and applied learning. There's also a solid alumni network that’s pretty active in mentoring and placements. Anything else you'd like to know about the role or the team, Dr.?

You’re interested in the department’s research ecosystem, especially around semiconductor devices and embedded systems, plus you want to know about funding and support for research proposals. VIT’s department has active groups working on embedded systems, VLSI design, and semiconductor device modeling—faculty regularly collaborate on interdisciplinary projects, and there’s encouragement for joint research and outreach with industry. As for funding, there’s institutional seed grants available for new proposals, plus support for applying to national agencies like DST and SERB. Faculty are expected to pursue external grants, and there’s guidance for proposal writing and partnerships. Any other questions, Dr., or should we wrap up?