Hey, I said good morning.

Please start by introducing your professional journey in academia

Yeah. First of all, I would like thank you giving this opportunity.

Say hey, good morning too.

Alright, I appreciate your gratitude. Just a quick intro—could you share your name and what you've been working on in academia lately?

Alright, Dr., just before we get started—could you share your name and a quick overview of your academic background?

And I have completed my education background with.

Computer Science.

Him remember the same satyr umbrella college. And I have completed my history doctorated St. Joseph College. Uh.

Okay, so you’ve got a background in computer science. What’s one foundational concept in computer science that you really enjoy teaching, and why?

Okay, so you completed your doctorate at St. Joseph College and your background is in computer science. What's one foundational concept in computer science that you really enjoy teaching, and why does it stand out to you?

My you know, currently I am working as an Assistant Professor, Department of Computer Science application.

Yazaram University campus and my career is. Experience of assistant professor, Department of Information Technology.

Okay, so you’re currently working as an Assistant Professor in Computer Science Applications. What’s one foundational concept or topic in computer science that you really enjoy teaching, and what is it about that topic that connects for your students?

Alright, Dr., so you've been working as an Assistant Professor in Information Technology and Computer Science Applications. What’s one teaching method or classroom environment you’ve found particularly effective for helping students grasp difficult concepts?

Book chapters undercover, 6 patterns.

Alright, you mentioned you've published research papers, authored books, and contributed to book chapters and patents. When you're teaching a foundational concept in computer science to first-year students, what's your favorite approach to making the material accessible and engaging?

And uh. I am act act like a served as question purpose. Save a model, uh college Pilgrim.

Alright, you mentioned serving as a question setter and being involved in college pilgrimages—those are pretty unique roles. When you're designing a question paper or exam for your students, how do you decide what concepts to emphasize?

Yeah, this is my. Basic. For Fin.

Alright, Dr. Gunishwari, you mentioned your experience as a question setter and serving in unique academic roles. When you're designing a question paper for your students, how do you make sure the questions actually test their understanding, not just rote memorization?

I am fully focused on the subject and always I am going to only the logic way of thinking the questions and it is fully based on the students level of the.

And that questions I'm fully focused on only the how to. Use for the students.

Right, so you base your questions on logic rather than just facts and try to match the student level. Can you give me one concrete example of a logic-based question you’ve set recently that helped students think critically?

Right, so you focus your questions on logical thinking and tailoring them to student levels. Can you give me one concrete example of a logic-based question you've set recently that helped students demonstrate real understanding?

Examples I'm always taking undertook the. Uh, not only the theoretical questions, I'm always chosen the. Uh, like programming level logical creativity, thinking of the real time basic, uh, level postings.

Uh, like, uh. I taken the machine learning subsidy. I am choosing the only the. Uh, real time scenarios based like image causing. Uh, questions and. Are like uh you get the chat security models like this? I am always using the real time scenarios based posting.

Alright, you mentioned you prefer real-time, programming-based questions to get students thinking creatively. When you’re teaching a foundational computer science concept to first-year students, what’s one teaching method you use to help them grasp the basics?

Okay, so you’re drawing from real-world scenarios in machine learning, like image processing and chat security, to get students thinking creatively. Before we wrap this section up, when you teach a brand new concept to first-year students—say, something foundational in computer science—how do you make sure your explanation is clear and accessible for everyone in the class?

I'm always teaching there. Uh, insulate the first basic level of the experimental using the real time scenarios.

Like emails? I am always at the just you think about the your image are. A dog, dog or cats like this is the image Auntie, this is the how to. Uh, how to work?

Alright, you said you use real-time scenarios and experimental methods to teach foundational concepts. How do you handle students who struggle to connect those real-world examples back to the theory—what’s your approach when they’re lost or confused?

Under and I'm always explaining the basic fundamentals of that concept.

Alright, you said you use examples like emails or images—dogs and cats—to help explain concepts. When students still don’t grasp the theory after you give those real-world examples, what’s your next step to help them bridge that gap?

Once that students clear about their topics, then only I will go to. Next level of the. The concept first, I'm always asking the students.

Alright, you break down the basics using examples like emails and images—dogs and cats—to make concepts less abstract. When students still don’t grasp the theory after you give those real-world examples, what’s your next step to help them understand?

Students type knowledge.

Thanks for walking me through how you approach teaching challenging concepts. Now, given your research in image processing and AI, where do you see the most promising, fundable research directions over the next three years? What kinds of grants or funding would you pursue to support those projects?

My opinion? Healthcare.

You see healthcare as a promising area for research funding—so with your background in image processing and AI, what specific healthcare applications would you target for grants, and how would you demonstrate their impact to a funding agency?

He understands Lee and Abu. Like predict the. And disease also like.

Any kind of the season.

You see healthcare as a promising area for research funding—so with your background in image processing and AI, what specific healthcare applications would you target for grants, and how would you demonstrate their impact to funders?

Not only a healthcare. And also real time such as.

Alright, now let’s talk about teaching. Suppose you had to run a session with 200 students and you weren’t allowed to use slides or traditional lectures. How would you keep everyone engaged and make sure they’re actually learning the material?

Roger oriented. These are so. Fully based on the. Uh, basic fundamentals of the image process.

Alright, you see strong research potential in healthcare and real-time applications using AI and image processing. Let’s switch gears a bit—at VIT, student evaluation processes can be quite diverse. How would you make sure your assessments are fair and accurate, especially when you’re dealing with students who have very different backgrounds and abilities?

Alright, you’re connecting image processing fundamentals to healthcare and real-time use cases. When you introduce these topics to students—especially those who might struggle with abstract concepts—how do you notice if they’re disengaged or lost? What’s your strategy to pull them back in and make sure everyone’s actually participating?

Like healthcare also and. The most powerful and most useful for nowadays.

You mentioned your focus on real-world applications, especially in healthcare and security. Shifting gears a bit—accreditation cycles can be pretty demanding. If you joined our department and found that outcome assessment data was inconsistent across courses, how would you approach fixing that?

What is having more algorithms? Should I keep learning on the? Causing also. A very powerful convention neural network.

Okay, you mentioned algorithms and neural networks, but let's bring it back to the accreditation context—if outcome assessment data is inconsistent, what concrete steps would you actually take to ensure all courses report and assess student outcomes in a standardized, verifiable way?

Machine learning. Deep learning at.

Alright, you mentioned algorithms and neural networks, but let's bring it back to the accreditation context—if outcome assessment data is inconsistent, what concrete steps would you actually take to ensure data quality across all courses?

Transfer learning algorithms. Are used to image processing.

Alright, you’re highlighting machine learning and transfer learning for image processing, but in terms of fixing inconsistent accreditation data, I was hoping for something a bit more concrete. What would you actually do day-to-day—would you set up new rubrics, coordinate with faculty, or maybe audit the existing data yourself?

Possible collect the. Raw data. It's under SO. I will convert. To the. Based on the real.

So, shifting into ethical dilemmas—imagine a student files a formal complaint, claiming your grading was unfair. At the same time, your department head is pressing you to improve pass rates. How would you handle that situation in a way that’s both fair to the student and maintains academic standards?

So. Definitely I will easily manage for them. Student time and my. And also extra. It is our. It is our based on our.

Okay, you’re saying you’d manage your schedule and make time for both students and departmental duties. But let’s say the department head disagrees with your approach—maybe they want you to relax grading or prioritize pass rates. How would you respond if that happened?

Find capability of thinking.

Okay, so you try to balance your schedule and find time for both students and your own work. But let’s say the department head disagrees with your approach—maybe they want you to relax grading standards for the sake of pass rates. What would you do if you were pressured to change grades against your academic judgment?

Sorry. Repeat. Please pardon.

Sure, I'll repeat the question. If your department head asks you to relax grading standards so that more students pass, but you believe that's not academically honest, what would you do if pressured to change grades against your judgment?

Only I. What means? That's only I do it.

Right, moving into industry alignment now. Given your background in multimedia and AI in media, do you have any industry connections or past collaborations that could help students access internships or placement opportunities?

Food so. I give up.

So I only did and I always do. Only for the. What is the actual thing only?

Alright, you mentioned changes happening and feeling pressure. But I need something concrete—have you ever worked directly with an industry partner, like a media company or tech firm, to set up a student internship or collaborative project? If so, which company, and what was your involvement?

Alright, you’re saying you stick to what’s actually fair and accurate, even if there’s pressure for change. But I need something more concrete—have you ever worked directly with an industry partner, maybe a media company or tech firm, to set up a student internship or real-world project? If so, what did that look like?

No, I'm also.

Alright, so you haven’t had a chance yet to work directly with industry partners or set up internships. Have you ever brought a real-world industry problem into your classroom, maybe as a project or case study, to help students see how their learning applies outside academia?

Students knowledge.

Okay, you support your students toward internships and focus on building their knowledge. Can you tell me about your experience with student evaluation—how do you make sure your grading is accurate and fair when you have students with very different abilities?

But different. Human, uh, waste. It is a huge. A huge host data setup.

You mentioned a huge host data setup and motivating students, but I need more detail. When you're evaluating students with very different backgrounds—maybe some are strong in AI concepts, others more in multimedia—how do you make sure your grading process is fair for everyone?

Applications and. Applications.

Analyzing the feedback trend.

You mentioned a huge host data setup and motivating students, but I need more detail. When you're evaluating students with very different backgrounds—maybe some are strong in AI concepts, others more in multimedia—how do you adjust your grading process to make sure it's fair for everyone?

So I'm always I can assist in evaluating students. The different subject, uh.

You mentioned analyzing feedback trends, which shows you're trying to learn from student responses. Shifting gears a bit—are you familiar with accreditation processes in universities, like NAAC or NBA, [interrupted]

You were saying you're always ready to assist with evaluating students in different subjects. But on accreditation—do you have any direct experience with processes like NAAC or NBA, or have you been involved in quality assurance or preparing reports for institutional audits?

St. time that. I'm also I'm talking working with the. NAAC Committee.

Alright, so you’ve actually worked with the NAAC committee during your time at the college. Can you give me one concrete example of something you contributed—maybe a document you prepared, a process you helped set up, or a specific improvement you helped implement for the accreditation cycle?

Yeah, yes, I.

During my PhD time also I did.

Alright, you mentioned you've worked with the NAAC committee and have experience with quality assurance, like preparing documents for KSC and NAAC. Can you give me one concrete example of a report or process you contributed to during your time on the NAAC committee?

Alright, you said you worked with the NAAC committee and contributed during your PhD as well. Can you walk me through one specific task you handled for NAAC—maybe a report you drafted, a criterion you helped document, or a process you improved?

Yeah, I am help to the accommodation.

Alright, so you've supported accommodation and worked with NAAC, but let's change gears for a moment. Given your experience with student projects in AI and multimedia, do you have any industry connections—maybe companies or partners—that could help students secure internships or placements?

Students, Yeah.

I have ex.

Alright, you've mentioned experience with student projects and some industry engagement. Let's dive into a few core skills for this role. First, tell me about a time you applied multimedia or artificial intelligence techniques in a real project—what tools or frameworks did you use, and what was the outcome?

Alright, you said you have experience with students and industry. Can you give me one concrete example of a student project in multimedia or AI where you leveraged an industry connection to help your student get an internship, placement, or real-world exposure?

Yes, undermine. Under my guide.

Okay, you mentioned guiding students and working with industry during projects. Shifting to teaching—can you tell me about a theory course and a lab course you've taught, and how you make sure students really understand the material in both settings?

Yeah, I'm always check this to. CS levels and. So I am easily I.

Okay, so you check different CS levels, but I need a bit more detail. For your lab course, what's one hands-on activity or experiment you use to make sure students grasp the core concept, and how do you evaluate whether they actually understood it?

We like, uh, always.

Who is the?

Alright, sounds like you always try to keep things active in the lab. Can you give me a real example—maybe a multimedia lab session—where you saw a student struggling with a concept and you changed your approach to help them get it?

You were about to give an example of what you do in the lab when a student struggles—can you finish that thought? How do you adapt your teaching on the spot to help them understand?

Always like the.

You seem to be struggling to find an example. No worries, let's switch topics. When it comes to evaluating students—say you have to design an exam for a multimedia theory course—how do you make sure your questions test both understanding and practical application, not just memorization?

So first. 1st I known that that you. And teach the student. I want to this list. So, students. The following e-mail.

So you use videos and demonstrations to help students understand, but I need to hear about your communication style. When you explain a complex concept—say in artificial intelligence or multimedia—how do you break it down so that students from different backgrounds can follow along?

Always rapid adoption.

Many organ, that is. Broken traditional educational.

Rapid adoption's important, but I'm looking for more specifics. Say you're explaining convolutional neural networks to students with little math background—how would you break down the key idea so everyone gets it, regardless of their prior experience?

Rapid adoption's important, but I'm looking for more specifics. Say you're explaining convolutional neural networks to students with little math background—how would you break down the key idea so everyone can follow?

Broken state refers to the, declined to the.

You mentioned breaking traditional educational models and memory-related deep learning, but let's pivot. For guiding student research, what's your approach when a student proposes an ambitious multimedia project that exceeds your lab's current resources—how do you help them navigate constraints and still produce meaningful results?

Writing, uh.

You've mentioned breaking traditional models and memory in deep learning, but let's get specific. When a student comes to you with an ambitious multimedia or AI research idea that's maybe not fully formed, how do you guide them to turn that into a structured, publishable project?

The theoretical knowledge.

You referenced theoretical knowledge, but I need more detail. When you’re guiding a student to turn that theory into a real research project—what’s your process for helping them pick methods, set milestones, and actually get results they can publish?

Students at the end only next level. Going to the. When they are fully understanding the theoretical knowledge.

Then only they are fully understand that. Practical knowledge.

You referenced students gaining theoretical knowledge, but let’s switch gears. For industry projects or consultancy, can you share an example of how you’ve collaborated with a company or external partner—what was your role, and how did you make sure the academic work translated to real-world impact?

First time you did that theoretical knowledge. On next level is the only. I practical now.

Alright, so you believe students need strong theoretical knowledge before they can really apply things in practice. Let me switch gears—when you work with industry partners or consult on a multimedia or AI project, can you share an example where your academic approach added value, maybe by solving a practical challenge that the company couldn’t handle on its own?

Alright, so you believe students need strong theoretical knowledge before they can really apply things in practice. Let me switch gears—when you work with industry partners or consult on a multimedia or AI project, what's your approach to making sure academic research actually solves a real business problem?

On the data collection. The Ethical. Uh, contact and integrity under review under reporting.

And the final is. They finalized the feedback.

Alright, you brought up ethics and integrity in data collection for industry projects. Say your team is under pressure from a client to deliver results quickly—how do you make sure your research stays rigorous and ethical, even when there's a tight deadline?

Alright, you brought up ethics and integrity in data collection for industry projects. Say your team is under pressure from a client to deliver results quickly—how do you make sure your research stays academically rigorous and ethically sound, even if the client wants shortcuts?

Yeah, the city projects. Diverted Vasel.

On digital twins for their real-time monitoring.

Alright, I need to shift gears. When you teach theory and lab courses—let's say you're running a practical lab on multimedia processing—how do you make sure students actually understand what's happening under the hood, not just follow the steps?

You mentioned digital twins for real-time monitoring in industry projects. When you're guiding students on projects like that, how do you help them connect the technical work—like simulation or modeling—to the real-world impact the industry partner cares about?

The operational if. So these are the included. They are not limited to using the conducting.

You mentioned digital twins and real-time monitoring in industry projects. When you're guiding students on projects like that, how do you help them connect the technical work—like simulation or modeling—to actual industry needs and outcomes?

Connections, cleaning and analyzing.

Process administrations under gaining the.

You mentioned connections, cleaning, and analyzing data as part of effective management. When it comes to evaluating students—say during lab exams or project presentations—how do you ensure your assessment is objective and fair, especially if students are working with very different media or AI tools?

Right, [interrupted]

So I am always. Uh, collect the method. St. is the automated. So like using? IoT and digital training. Uh, is there replica? Unique products.

A digital service and the forms under direct observations. Monitoring. And data scoping. So these are all the.

Okay, so you’re automating data collection with IoT and digital twins to create replicas of unique products. When you teach students about these technologies in a lab setting, how do you make sure they understand not just the tools, but the reasons behind using digital twins and automation in real-world scenarios?

Best practice and analysis of the planning data and.

Okay, you’re using digital tools and automated data collection with IoT and digital twins for monitoring and creating replicas. When you’re guiding students on a multimedia project that involves these technologies, how do you help them break down the problem so their approach is structured and their results are measurable?

Okay, so you focus on best practices and planning for data analysis. When you're evaluating students during exams or practicals, what criteria do you use to determine if they've truly mastered both the theory and the hands-on skills required for multimedia or AI projects?

There are always like. Nowadays, uh, NLP is the most powerful.

Alright, you've got best practices for planning and analysis. When you're guiding student research projects, especially in multimedia or AI, how do you help students choose a topic that's both academically rigorous and relevant to current industry needs?

I am all. Please focus.

What is the students now?

Alright, you mentioned digital services, direct observations, and data scoping as part of your methods. Let's shift a bit—when you're guiding student projects or research, how do you help students choose a topic that's both academically rigorous and relevant to current industry needs, especially in multimedia or AI?

Alright, you mentioned best practices in planning and data analysis. Let's switch topics—when you're guiding student research projects, especially in multimedia or AI, how do you help students choose a topic that's both academically rigorous and relevant to current industry needs?

So it is fully the students. All of the base.

Alright, you've talked a lot about digital tools and automation. When you're teaching theory and lab courses, how do you structure a lesson so students grasp both the technical concepts and understand how to actually apply them in a real-world multimedia or AI scenario?

Scenario or like. Digital tool and. The experimental to SP.

Alright, you’re emphasizing direct observation and monitoring in your teaching. When it comes to guiding student projects or research, especially in multimedia or AI, how do you help students choose a topic that’s both academically rigorous and practically relevant?

Enabling into multimedia product. From ideas. Radiation.

Normal human intervention. Such as real-time scenarios.

Alright, you mentioned enabling multimedia products from ideas and experimentation. Switching gears now—when you guide student projects or research, especially in multimedia or AI, how do you help students choose a topic that's both academically rigorous and relevant to current industry trends?

You mentioned real-time scenarios and human intervention in digital tools. When it comes to evaluating students during exams or practicals, how do you make sure your assessment captures both their technical understanding and their ability to apply multimedia or AI concepts in practice?

How AAA generating? Thousands of. On devices creating the. 3D employment.

And the auditing video port. Like. A list of the one or two examples. Fully automated AI video factory.

Alright, you mentioned creating thousands of devices and 3D employment—sounds like you're working with some pretty advanced tech. Switching topics a bit, when you're guiding student projects or research, especially in multimedia or AI, how do you help students choose a project that's both original and feasible given their skill level and resources?

Alright, you mentioned automated AI video factories as an example. Can you give me a concrete scenario where you evaluated students' work on a multimedia or AI project—what specific criteria or rubric did you use to make your assessment fair and comprehensive?

I is useful for that. Content marketing and hyper personalized and the funeral like. So these are all the real time scenarios. Undercorporate. On the game.

You mentioned AI-driven video factories and hyper-personalized content—sounds like you’re quite familiar with automation in multimedia. Switching gears, when you’re tasked with evaluating student exams or practicals, how do you ensure fairness and consistency, especially when grading hands-on projects versus written theory?

These are all the right. Image design. Voice over.

You mentioned image design and voice-over as examples — sounds like you're using multimedia automation pretty broadly. When you're teaching lab courses, how do you make sure students actually understand the technical process behind creating these automated multimedia products, not just the end result?

It is. It is very most.

Alright, you mentioned image design and voice-over in multimedia automation. When you're guiding student projects or research in multimedia or AI, what's your approach to helping students choose the right technologies or methods for their problem, especially if they’re struggling to decide between different tools or frameworks?

Yeah, yeah.

Alright, you've described a lot of real-world applications and automation. When you’re evaluating students—either through exams or practical assessments—how do you make sure your grading is consistent and objective, especially for complex multimedia or AI projects where outcomes can vary so much?

In today, rapidly avoiding the educational landscape, so. Educational technology encompasses students diverse. Day of digital stud. Resource designed in. Teaching practice.

Student teaching projects and. Student learning outcomes.

You brought up voice-over and image design as practical examples. When you’re teaching both theory and lab classes, how do you make sure your students not only understand the concepts but can apply them hands-on—especially when you’re dealing with advanced multimedia or AI tools?

You brought up student learning outcomes and teaching practice with digital tools. When it comes to evaluating students—either through exams or practical assessments—how do you make sure your grading is consistent and fair, especially if projects are very diverse or highly technical?

So first, the integrating of educational technology represents the more than simply digital. Uh, traditional material are adding the computer to classroom when implemented with the pedagogy. Purpose and the thoughtful planning in digital learning pool.

Transfer of educational experience. By providing the intermediate feedback, adapting to individual learning needs.

You brought up content marketing and hyper-personalized media. When you’re evaluating students—either through exams or practical assessments—how do you make sure your grading is consistent and fair, especially when projects involve creative or technical elements that aren’t always easy to measure objectively?

Uh, visually think the complex concept.

Alright, you talked about adapting to individual learning needs and giving feedback. When it comes to evaluating students—either through exams or practical assessments—how do you make sure your grading is consistent and fair, especially with projects that use a lot of multimedia or AI elements?

So these are all the I will help the students.

Alright, you brought up image design and voice-over in the context of automation. When you're communicating complex multimedia or AI concepts to students, how do you make sure your explanations are structured and clear enough for everyone to understand—even for those who might not have a strong technical background?

You talked about helping students visualize complex concepts and adapt learning to their needs. When it comes to evaluating students—either through exams or practical assessments—how do you make sure your grading is consistent and fair, especially if you have a large group with diverse abilities?