Yes. We can begin now.

Please start by introducing your professional journey in academia

OK. My name is Doctor K Viteswar. I competed today to Recline National. Materials. I have. Uh, total six years of racers. And teaching his business. Myco Research. Areas need to fractions is past same.

OK. My name is Doctor K Viteswar. I competed today to Recline National. Materials. I have. Uh, total six years of racers. And teaching his business. Myco Research. Areas need to fractions is past same. Materials. And I have.

OK. My name is Doctor K Viteswar. I competed today to Recline National. Materials. I have. Uh, total six years of racers. And teaching his business. Myco Research. Areas need to fractions is past same. Materials. And I have. Play replay song. Uh. How are nearly more than? Recently I have started.

You mentioned both teaching and research experience. Can you tell me about a foundational topic in mechatronics or smart manufacturing that you particularly enjoy teaching to students?

Alright, so you mentioned your research and teaching experience centers on materials and mechatronics. When you're teaching a foundational concept in that area—say, material properties or smart manufacturing basics—how do you typically introduce it to students who've never encountered it before?

Okay, so you’ve recently started something new but trailed off there. Were you about to tell me how you introduce materials or mechatronics concepts to your students? Go ahead.

Yes Sir. Recently I started working on integrating merchant learning. Materials. So they are. Mechanical properties. Such as SLO. Send immediately without. Collected the data. Up from the literature. And started applying some. Misleading algorithms.

Yes Sir. Recently I started working on integrating merchant learning. Materials. So they are. Mechanical properties. Such as SLO. Send immediately without. Collected the data. Up from the literature. And started applying some. Misleading algorithms. Like linear recruitment? Ah ah, this is entry anam.

Yes Sir. Recently I started working on integrating merchant learning. Materials. So they are. Mechanical properties. Such as SLO. Send immediately without. Collected the data. Up from the literature. And started applying some. Misleading algorithms. Like linear recruitment? Ah ah, this is entry anam. To predict the mechanical. It's mostly mechanical. Strength. Heart. So this is how I integrated. Uh are used Muslim? In the materials. Unmanifesting fee.

Alright, so you’re integrating machine learning with materials research—using data on mechanical properties and applying algorithms to predict or analyze them. When you introduce machine learning concepts to students who only know the basics of materials science, how do you help them connect those two fields?

Alright, so you’re applying machine learning algorithms—like linear regression—to predict mechanical properties based on literature data. When you teach this intersection of machine learning and materials to students, how do you make sure they grasp both the engineering fundamentals and the data-driven approach in the classroom?

Okay, so you used linear regression and machine learning to predict mechanical strength from literature data. When students struggle to grasp how these algorithms actually impact manufacturing decisions, how do you bridge that gap in the classroom?

First of all. The student should have idea on machine learning.

First of all. The student should have idea on machine learning. Otherwise I will I. I will explain uh. Some machine learning algorithm. Show data. From the literature. Also, I will give some hands-on experience.

First of all. The student should have idea on machine learning. Otherwise I will I. I will explain uh. Some machine learning algorithm. Show data. From the literature. Also, I will give some hands-on experience. So I will. I will for example. I will collect some data.

First of all. The student should have idea on machine learning. Otherwise I will I. I will explain uh. Some machine learning algorithm. Show data. From the literature.

First of all. The student should have idea on machine learning. Otherwise I will I. I will explain uh. Some machine learning algorithm. Show data. From the literature. Also, I will give some hands-on experience. So I will. I will for example. I will collect some data. And try to. Help them. Hands on experience. I'll take a problem. It went up in. I will stop.

First of all. The student should have idea on machine learning. Otherwise I will I. I will explain uh. Some machine learning algorithm. Show data. From the literature. Also, I will give some hands-on experience. So I will. I will for example. I will collect some data. And try to. Help them. Hands on experience.

First of all. The student should have idea on machine learning. Otherwise I will I. I will explain uh. Some machine learning algorithm. Show data. From the literature. Also, I will give some hands-on experience. So I will. I will for example. I will collect some data. And try to. Help them. Hands on experience. I'll take a problem. It went up in. I will stop. How to solve the problem by using? On board.

Alright, you emphasized that students need a foundation in machine learning first. Can you give me a concrete example of how you’ve explained the link between material properties and predictive modeling to undergraduates—maybe from a specific lecture or project?

First of all. The student should have idea on machine learning. Otherwise I will I. I will explain uh. Some machine learning algorithm. Show data. From the literature. Also, I will give some hands-on experience. So I will. I will for example. I will collect some data. And try to. Help them. Hands on experience. I'll take a problem. It went up in. I will stop. How to solve the problem by using? On board. By this I can I can make them. To learn. Learning algorithms in. Mechanical.

Alright, so you use literature data to explain machine learning basics when students lack prior exposure. Looking at your CV, I noticed your publication on "Smart Manufacturing Applications in Materials Science"—how did you adapt the findings from that research for undergraduate teaching, especially for students new to the topic?

Alright, hands-on experience is always valuable. On your CV, I saw your publication about smart manufacturing applications in materials engineering. How did your research in that area influence the way you teach laboratory courses?

Right, so you give students hands-on experience by collecting data and applying machine learning algorithms together. Looking at your publication on smart manufacturing applications in materials engineering, how did your research influence the way you design lab activities or projects for students?

Alright, hands-on experience is always valuable. On your CV, I saw your publication about smart manufacturing applications in materials engineering. How did your research in that area influence the way you design lab exercises for your students?

Alright, you mentioned hands-on machine learning projects with materials data. Looking at your CV, I see you’ve published on smart manufacturing applications in materials engineering. How did your research in that area influence the way you design lab assignments or projects for your students?

Alright, you described guiding students hands-on with literature data and machine learning algorithms to predict material properties. Shifting topics, I noticed you have industry project experience listed on your CV. Can you share how your involvement in those projects has informed the way you design student research assignments or lab work?

Alright, you walk students through machine learning basics and hands-on problem solving with materials data. On your CV, I see you've published research on smart manufacturing applications in materials engineering. How did your work in that area influence the way you teach practical skills in the lab?

Generally for mechanical students. The students do not have. Personal Learning.

Generally for mechanical students. The students do not have. Personal Learning. Background. So here I would like. To establish a Muslim lab.

Generally for mechanical students. The students do not have. Personal Learning. Background. So here I would like. To establish a Muslim lab. For mechanical students. There, uh, there I want to. Uh, them? Train them how to use.

Generally for mechanical students. The students do not have. Personal Learning. Background. So here I would like. To establish a Muslim lab. For mechanical students. There, uh, there I want to. Uh, them? Train them how to use. How to predict? How to collect the data?

Generally for mechanical students. The students do not have. Personal Learning. Background. So here I would like. To establish a Muslim lab. For mechanical students. There, uh, there I want to. Uh, them? Train them how to use. How to predict? How to collect the data? How to clean the data? And then how to? Time the data in. So its entirely a course. It's not a simple thing.

Okay, so for mechanical students who might not have a background in machine learning, you focus on foundational concepts. Now, looking at your thesis work on materials engineering, can you describe a time when you had to explain that research to someone who wasn't a specialist—maybe an undergraduate or a colleague from another field?

Alright, so your goal is to set up a machine learning lab for mechanical students who don’t have much background in that area. Before we wrap this section, I noticed you’ve supervised student projects related to smart vehicle technologies—how did you guide students who struggled with connecting research theory to practical engineering tasks?

Generally for mechanical students. The students do not have. Personal Learning. Background. So here I would like. To establish a Muslim lab. For mechanical students. There, uh, there I want to. Uh, them? Train them how to use. How to predict? How to collect the data? How to clean the data? And then how to? Time the data in. So its entirely a course. It's not a simple thing. They should undergo a course. So far, they need some. Experts who are working in muscle like. OK, they can teach. And then try to solve. Uh, try to integrate. The machine learning in. Mechanical.

You mentioned wanting to establish a machine learning lab for mechanical students—sounds like you’re connecting your smart manufacturing research directly to hands-on teaching. Before we wrap this section, can you give me an example of a student project you supervised that blended these areas, and how you guided the student through the research process?

Dr., given your expertise in materials engineering and smart manufacturing, where do you see the most fundable research directions over the next three years? What specific grants or collaborations would you target to support those efforts?

Okay, so you're treating machine learning in manufacturing as a full course, not just a module. When you set up that lab, what would be your strategy for getting external funding or industry collaboration to sustain it long-term?

Alright, you’re aiming to create a machine learning lab for mechanical students and bring in external expertise. But funding can be tough—what’s your plan for making this lab financially sustainable for the department over the next few years?

I don't think establishing a muscle learning lab. Uh is costly. So when is systems only and they should. They should learn some Python.

I don't think establishing a muscle learning lab. Uh is costly. So when is systems only and they should. They should learn some Python. Mathematical bathroom. That's it. That is an. But uh. Mechanical story. The systems are not.

Okay, you’re saying most of the cost comes down to systems and Python training, not expensive hardware. But for external grants or industry support—like from automotive or semiconductor companies—how would you pitch the value of your lab to make it attractive for collaboration?

I don't think establishing a muscle learning lab. Uh is costly. So when is systems only and they should. They should learn some Python. Mathematical bathroom. That's it. That is an. But uh. Mechanical story. The systems are not. Like 30 to 40 systems are uh. Required to establish a. I don't think it is. Normal labs are enough. To continue. Are to establish.

So you’re saying the main expense is just standard computers and Python—not specialized hardware—so you don’t see major financial hurdles. But if you wanted to scale this up and make it a recognized research asset for the university, what’s your strategy for attracting external grants or industry partnerships to support and expand the lab?

You’re saying normal labs with standard computers and Python are enough for mechanical students, so high costs aren’t a concern. But if you wanted to attract industry partners or external funding—like from smart vehicle or semiconductor manufacturers—what kind of research would you focus on to make that lab stand out?

Here regarding external funding. I would like to integrate machine learning. Particularly in additive manufacturing. To predict to improve the mechanical properties.

Here regarding external funding. I would like to integrate machine learning. Particularly in additive manufacturing. To predict to improve the mechanical properties. And also to. And also to find the defect detection in the. Because suffers from. So if they can predict defects, we can. By using image. So that is my core area applying machine learning in. I don't have material.

Alright, so you’d focus on additive manufacturing and machine learning to improve mechanical properties. If you had to mentor a student group working on smart vehicle technologies, what would be your method for structuring their research so it stays rigorous and relevant in a fast-changing field?

So you’d apply machine learning to defect detection in additive manufacturing, using image data—that makes sense for industry relevance. If you were mentoring students on a research project in smart vehicle technologies, how would you structure their process to keep it methodical given how fast the field evolves?

Alright, so you’d apply machine learning for defect detection and mechanical property prediction in additive manufacturing — that’s definitely relevant for industry. Given your background, how would you ensure a structured and methodical approach to student mentorship for research projects in rapidly evolving fields like smart vehicle technologies?

I'm so sorry I don't have much knowledge. My manufacturing. So I'm particular I'm good at. That's interesting.

I'm so sorry I don't have much knowledge. My manufacturing. So I'm particular I'm good at. That's interesting. And also sanguine. Patients in particular.

Okay, shifting gears—Dr., you’ve taught materials and machine learning to students with little background in either. Suppose you couldn’t use slides and had a class of 200 mechanical engineering students. How would you run a session that keeps them actively engaged and helps them wrestle with the concepts, not just listen passively?

Okay, you said you’re more comfortable with materials and additive manufacturing than smart vehicles. For your research students in materials, how do you actually measure whether your mentorship is helping them become independent problem solvers, not just following instructions?

Yes, by by. Giving practical problems to them.

Yes, by by. Giving practical problems to them. And also I will sign them independently. First I will give you a project. I will let them to do on their own.

Okay, so you measure your mentorship by giving students practical problems and seeing how they handle them. What do you do if a student just follows your instructions without thinking critically or trying alternate solutions—how do you encourage more independent problem-solving?

Right, so you give them practical problems and let them work independently. If a student just follows your instructions without thinking critically or trying their own approach, how do you encourage them to step outside their comfort zone?

First of all, I I I asked them to visit some industry related. Industry. So I have one. Hyderabad.

First of all, I I I asked them to visit some industry related. Industry. So I have one. Hyderabad. Startup. They work on muscle and wing. First I will. I will, uh. Find them there.

First of all, I I I asked them to visit some industry related. Industry. So I have one. Hyderabad. Startup. They work on muscle and wing. First I will. I will, uh. Find them there. And ask them to acquire some. Knowledge on. Particularly machine learning. And then I will after, after three to four months, I, I will.

First of all, I I I asked them to visit some industry related. Industry. So I have one. Hyderabad. Startup. They work on muscle and wing. First I will. I will, uh. Find them there. And ask them to acquire some. Knowledge on. Particularly machine learning. And then I will after, after three to four months, I, I will. Assigned some parallel. Industry-related path.

First of all, I I I asked them to visit some industry related. Industry. So I have one. Hyderabad. Startup. They work on muscle and wing. First I will. I will, uh. Find them there. And ask them to acquire some. Knowledge on. Particularly machine learning. And then I will after, after three to four months, I, I will. Assigned some parallel. Industry-related path. Uh, so and then I will evaluate them. Continues.

Alright, you mentioned taking students to industry sites, like one in Hyderabad, to expose them to real-world challenges. That’s useful. Looking ahead, if you were asked to design a hands-on laboratory session for a Mechatronics course with students who have very little programming experience, how would you make sure everyone actually participates and learns?

Alright, you connect students to startups for real-world exposure so they learn to solve practical problems. Thinking about your lab courses—if you couldn’t use slides or standard lectures, how would you design a hands-on session for 200 students in materials engineering that keeps everyone actively engaged?

Alright, you connect students to industry partners like the Hyderabad startup so they get exposure and then check in after a few months. When you bring them back, how do you actually evaluate whether they’ve gained new skills from that experience—do you use project deliverables, presentations, or something else?

Okay, you put students in touch with industry partners so they gain real-world knowledge before tackling projects. When they return, how do you actually evaluate whether their industry experience has made them better at independent research, instead of just following instructions?

Alright, so you actually send students out to industry, like the Hyderabad startup, to give them a broader perspective, and then assign them parallel industry-related projects afterwards. When you bring them back, how do you evaluate whether that industry experience has translated into stronger research or more creative problem-solving in their academic work?

Uh, it it depends upon the. The project they have. So done. And also. And also I will ask them to. Try to publish that work in. International Journals.

Uh, it it depends upon the. The project they have. So done. And also. And also I will ask them to. Try to publish that work in. International Journals. That anyway, for Navy students, they may not have that. But I will. I will push them to. Puppies that work in international song. So since I have much knowledge. Publishing Papers. So. So I will guide them. To publish that. And also I will. Constantly. They were and. Provide some inputs. Whenever they.

You said you encourage students to publish their work in international journals as a way to measure their progress. That’s a strong benchmark. I want to pivot a bit—suppose you had to teach a course in Mechatronics or Smart Vehicle Technologies, and you couldn’t use slides or traditional lectures. With 200 students in the room, how would you design a session that keeps everyone actively engaged with the material?

You said you push your students to publish their work, even if they’re new to research. That’s ambitious. If you had to teach a course in Mechatronics or Smart Vehicle Technologies, how would you combine theoretical concepts with hands-on lab sessions to make sure students get both the academic foundation and real practical skills?

Health, engineering and manufacturing background.

Health, engineering and manufacturing background. So I don't have much dollars. I'm a smart. Vehicle Manifest.

Accreditation cycles can be demanding — if you joined our department and noticed that outcome assessment data was inconsistent across courses, how would you approach fixing that?

Alright, you’ve got a strong foundation in materials and manufacturing, but not much in smart vehicles. I want to switch gears a bit—accreditation cycles can be a real challenge. If you joined our department and noticed that outcome assessment data was inconsistent across courses, how would you approach fixing that?

Sorry, I didn't understand the question. Can you please?

Sure, let me repeat the question for you. Accreditation cycles can be demanding — if you joined our department and noticed that outcome assessment data was inconsistent across courses, how would you approach fixing that?

Outcome assessment data is not fixed. Then we can, We can. Into some ETS. Technology areas like AMS. Uh, no Mechanical.

Outcome assessment data is not fixed. Then we can, We can. Into some ETS. Technology areas like AMS. Uh, no Mechanical. In such a weekend, weekend. I can fix the. A rosary we can include. Some new emerging. Technology areas like. Energy resources. Renewable energy success.

Outcome assessment data is not fixed. Then we can, We can. Into some ETS. Technology areas like AMS. Uh, no Mechanical. In such a weekend, weekend. I can fix the. A rosary we can include. Some new emerging. Technology areas like. Energy resources. Renewable energy success. That's right.

Let’s try something a bit different, Professor. Imagine a student files a formal complaint saying your grading is biased, but at the same time your department head is pressuring you to increase pass rates. How would you handle that situation and make sure you stay true to your academic standards?

Okay, you’d look at outcome data and bring in new technology areas like renewable energy if needed. Let’s try something a bit different, Professor. Imagine a student files a formal complaint saying your grading is biased, but at the same time your department head is pressuring you to increase pass rates. How do you handle that situation?

You said you'd fix inconsistent outcome data by adding new technology areas like renewable energy. Let's try something a bit different, Professor. Imagine a student files a formal complaint saying your grading is biased, but at the same time your department head is pressuring you to increase pass rates. How would you navigate that situation?

First of all, I will I will consider the student complaint. I tried to improve my. My teaching. OK, I try to improve from my side. Try to give my best to the students so that automatically the cost percentage payment. That is what I believe is fine.

First of all, I will I will consider the student complaint. I tried to improve my. My teaching.

Alright, you’d take the student’s complaint seriously and try to improve your teaching. But let’s say the department head insists you raise pass rates, even if it means changing your grading standards. How would you respond if you feel that could compromise academic integrity?

Hmm, that's a tough spot — your focus is on improving teaching, not lowering standards. Let me shift to something more industry-focused now. Given your background in additive manufacturing and materials, do you have any connections with industry partners that could help students access internships or placement opportunities?

Yes, as I told you, my friend has a start up in Hyderabad. Set Li blocks. Famously. 3-D20.

Yes, as I told you, my friend has a start up in Hyderabad. Set Li blocks. Famously. 3-D20. And also their works are. The IoT. Pause. So uh. I send my students there. And I asked them to acquire some. Tactical alerts.

Yes, as I told you, my friend has a start up in Hyderabad. Set Li blocks. Famously. 3-D20. And also their works are. The IoT. Pause. So uh. I send my students there. And I asked them to acquire some. Tactical alerts. From the start. And and also he seems he he's my friend. I asked them. Uh, uh, internship opportunities to my. Students. So there. Easily they can get interesting. Uh, from the company. And then students live. Get.

Alright, so your main industry contact is that Hyderabad startup working with 3D printing. Can you give me a concrete example of a time you helped a student secure an internship or a hands-on project with that partner, and what your involvement was?

Alright, you’ve actually helped students get hands-on experience through that Hyderabad startup, and exposed them to IoT and 3D printing tech. Can you walk me through how you structured their internship or project work there — did you set clear goals, check in on progress, or leave it more open-ended?

Okay, so your students get internships at the Hyderabad startup through your connections, and they get exposed to 3D printing and IoT there. Switching topics, when you evaluate students—for example, during exams or project reviews—how do you make sure your grading is consistent and fair, especially if you’re handling both theory and lab courses?

I will evaluate. 1st I follow university norms. Otherwise if it. The chances given to. Roxanne, uh. I will pick some. Is it picks some marks?

I will evaluate. 1st I follow university norms. Otherwise if it. The chances given to. Roxanne, uh. I will pick some. Is it picks some marks? Generally UH-90 to 95. They have eaten. 85 to 90 or 8280.

I will evaluate. 1st I follow university norms. Otherwise if it. The chances given to. Roxanne, uh. I will pick some. Is it picks some marks? Generally UH-90 to 95. They have eaten. 85 to 90 or 8280. OK 75 to 80 like I will fix. And also. Based on their performance. I will call Aarti. Marks and poetry.

You mentioned you follow university norms for evaluation, but can you give me a concrete example of how you actually grade a lab or theory exam—like, what specific steps do you take from collecting the answer sheets to assigning final marks?

Alright, you follow university norms and assign marks within certain ranges. But say you’re grading a lab report and you find two students with almost identical results, but one explains their process clearly and the other just lists numbers. How do you decide their grades?

Alright, so you use university norms for assigning grades, but you also adjust based on performance bands. When you’re actually teaching—whether it’s theory or lab—how do you make sure your explanations are structured so that students at different levels can all follow along and stay engaged?

In my teachings, uh. Most of my explanations are. Related to. I tease them with uh. I take real time. Real time example. To the theory. Yeah, I can. Uh. Engage them, uh. Long time ang. Make sure.

Alright, you use real-time examples to help students grasp theory and keep them engaged. When you’re teaching, how do you check if your students actually understand the material—do you use in-class quizzes, oral questioning, or something else?

Alright, you actually get your students internships and exposure to IoT and 3D printing at that Hyderabad startup. Let’s talk about research publications — can you walk me through how you help your students turn their project work into papers for reputed journals, especially if they’re new to publishing?

Yes, if you see my publication record, I have. More publications on manufacturing materials, particularly frictionless processing. Where I use efficiency to. Through the dynamic mechanical property. I just very very important properly.

Yes, if you see my publication record, I have. More publications on manufacturing materials, particularly frictionless processing. Where I use efficiency to. Through the dynamic mechanical property. I just very very important properly. Movie Pass Special Aerospace. I guess see, I don't, I don't want to see. Field OK. Later, I shifted my research to muscle learning. If you saw my. Uh, I have a place to. 3300 donors. I have mentioned very few in Doctor. Resume. So recently I have started. Integrating machine learning in market.

Yes, if you see my publication record, I have. More publications on manufacturing materials, particularly frictionless processing. Where I use efficiency to. Through the dynamic mechanical property. I just very very important properly. Movie Pass Special Aerospace. I guess see, I don't, I don't want to see. Field OK. Later, I shifted my research to muscle learning. If you saw my. Uh, I have a place to. 3300 donors. I have mentioned very few in Doctor. Resume. So recently I have started. Integrating machine learning in market. OK, so. And also I. Also integrating muscle. Addictive testing.

You mentioned you have strong publications in manufacturing materials, especially frictionless processing and dynamic mechanical properties. But for industry projects or consultancy, have you actually worked hands-on with companies—maybe helping them solve a manufacturing challenge or optimize a process?

Yes, if you see my publication record, I have. More publications on manufacturing materials, particularly frictionless processing. Where I use efficiency to. Through the dynamic mechanical property. I just very very important properly. Movie Pass Special Aerospace. I guess see, I don't, I don't want to see. Field OK. Later, I shifted my research to muscle learning. If you saw my. Uh, I have a place to. 3300 donors. I have mentioned very few in Doctor. Resume. So recently I have started. Integrating machine learning in market. OK, so. And also I. Also integrating muscle. Addictive testing. Here my major. Research area is. Improve the mechanical properties of. Like cricket? Fleximum Sleep fasting.

Yes, if you see my publication record, I have. More publications on manufacturing materials, particularly frictionless processing. Where I use efficiency to. Through the dynamic mechanical property. I just very very important properly. Movie Pass Special Aerospace. I guess see, I don't, I don't want to see. Field OK. Later, I shifted my research to muscle learning. If you saw my. Uh, I have a place to. 3300 donors. I have mentioned very few in Doctor. Resume. So recently I have started. Integrating machine learning in market. OK, so. And also I. Also integrating muscle. Addictive testing. Here my major. Research area is. Improve the mechanical properties of. Like cricket? Fleximum Sleep fasting. Short painting so this. These are the new areas where. UH students. Encouraged. So that. The chance of. Publishing Papers. In these areas like. Integrating person learning in. Materials. Unmanifested is It is a new emerging area where students can easily. And also I'm there. To support him.

You mentioned you’ve got over thirty publications in manufacturing materials, and you’re starting to integrate machine learning into that work. For industry projects or consultancy—have you actually led any student teams on live projects with external clients or companies, where the outcome directly impacted industry stakeholders?

You mentioned frictionless processing and dynamic mechanical properties in your publications, and now you're integrating machine learning and additive testing. For industry projects or consultancy—have you actually led any collaborations where your research directly impacted how a company improved their manufacturing process or product?

You mentioned integrating machine learning into your materials research, and your students get exposure to industry technology like 3D printing and IoT. But when it comes to industry projects or consultancy, have you actually led a project where your students had to deliver something directly to a company or solve a real-world manufacturing problem?

Okay, so you’re integrating machine learning with materials research and guiding students toward publishing in emerging areas. When you’re involved in industry projects or consultancy—have you actually led a project for a company, or worked as a technical consultant? If so, what was your role and what kind of impact did your work have?

Actually I have uh. Apply for research funding.

Actually I have uh. Apply for research funding. Yesterday, I said.

Actually I have uh. Apply for research funding. Yesterday, I said. So. So I'm trying to do.

Alright, so you've applied for research funding but haven't led an industry project directly yet. Let's talk about structured teaching—when you explain a complex topic, like dynamic mechanical properties or additive manufacturing, what's your approach to keeping your explanations clear and engaging for students who might not have much background?

Mm-hmm.

Actually I have uh. Apply for research funding. Yesterday, I said. So. So I'm trying to do. Written a project research project. Integratively active. That's sorry, integrating machine learning, Additive manufacturing.

Actually I have uh. Apply for research funding. Yesterday, I said. So. So I'm trying to do. Written a project research project. Integratively active. That's sorry, integrating machine learning, Additive manufacturing. Mechanical Popper. Also for defect detection processes generally. Adizu Manufacturing. Effects. So I would like to integrate questionnaire. It defects some. Image pass actually that. So I would like to do all my work. So part of work is done. After planning. This uh subcategories itself. Scanning electron microscope. Tests are going on. Collaboration Here I would like to say. One thing, Uh Here I would like to say. One thing, Uh. I have enough knowledge. Uh, teaching and research experience. Total six years of research experience.

Actually I have uh. Apply for research funding. Yesterday, I said. So. So I'm trying to do. Written a project research project. Integratively active. That's sorry, integrating machine learning, Additive manufacturing. Mechanical Popper. Also for defect detection processes generally. Adizu Manufacturing. Effects. So I would like to integrate questionnaire.

Actually I have uh. Apply for research funding. Yesterday, I said. So. So I'm trying to do. Written a project research project. Integratively active. That's sorry, integrating machine learning, Additive manufacturing. Mechanical Popper. Also for defect detection processes generally. Adizu Manufacturing. Effects. So I would like to integrate questionnaire. It defects some.

Alright, you've applied for research funding but haven't led an industry project directly yet. Let's talk about structured teaching—when you explain a complex topic, like dynamic mechanical properties, what steps do you take to make sure your students understand the material clearly and don't get lost?

Actually I have uh. Apply for research funding. Yesterday, I said. So. So I'm trying to do. Written a project research project. Integratively active. That's sorry, integrating machine learning, Additive manufacturing. Mechanical Popper. Also for defect detection processes generally. Adizu Manufacturing. Effects. So I would like to integrate questionnaire. It defects some. Image pass actually that. So I would like to do all my work. So part of work is done.

Alright, so you’re working on integrating machine learning with additive manufacturing, and you’ve applied for research funding but haven’t led a full industry project yet. When you’re teaching a complex topic like dynamic mechanical properties, how do you structure your explanation so students with different backgrounds all understand the material?

Alright, so you’ve applied for research funding and you’re working on integrating machine learning with additive manufacturing for defect detection, but you haven’t actually led an industry project yet. When you explain something complex—like the dynamic mechanical properties of friction stir processed materials—how do you break that down for students so it’s clear and approachable, especially for those who might be struggling?

Alright, you’re applying for research funding to integrate machine learning with additive manufacturing for defect detection, but haven’t actually led an industry project yet. Let me ask about your teaching style one more time — when you explain a complex topic, like dynamic mechanical properties or defect detection, what’s your process for structuring the lesson so students can follow along and actually grasp the material?

Alright, Dr., we’re at the end of our conversation. Is there anything you’d like to ask about the Assistant Professor (Research) role or the team?

Here I would like to say. One thing, Uh. I have enough knowledge. Uh, teaching and research experience. Total six years of research experience. Highly reputed international slide. OK, Ajanla, Partition science and technology.

You've got six years of research and teaching experience, and clearly a lot of exposure to emerging areas. Is there anything specifically you'd like to know about the Assistant Professor (Research) role or the department before we wrap up?

Here I would like to say. One thing, Uh. I have enough knowledge. Uh, teaching and research experience. Total six years of research experience. Highly reputed international slide. OK, Ajanla, Partition science and technology. Recently we have. Recently. Last month, Uh, scientific. So these are all. Applying. Materials are past. So the chances given. I would like to. More on integrating machine learning in. Heroes.

You’ve got six years of research and teaching experience, and clearly a lot of exposure to emerging areas. Is there anything specifically you'd like to know about the Assistant Professor (Research) role or the department before we wrap up?