Yes, please.

Am I audible?

Please start by introducing

Yes, you’re coming through clearly. Just a quick intro — your name and what you’ve been working on in academia lately.

Myself, doctor Surendra Kumar Yadav and I'm working on. After electronics. Biosensors. I'll go to colleagues and biosensors. And I have done my. PhD from the University of Rome. And I've done my masters from the baby university in.

Myself, doctor Surendra Kumar Yadav and I'm working on. After electronics. Biosensors. I'll go to colleagues and biosensors. And I have done my. PhD from the University of Rome. And I've done my masters from the baby university in. In physics. After that I've uh. Joint University of Delhi. As a assistant professor. And I was teaching there for more than 2 1/2 years.

Myself, doctor Surendra Kumar Yadav and I'm working on. After electronics. Biosensors. I'll go to colleagues and biosensors. And I have done my. PhD from the University of Rome. And I've done my masters from the baby university in. In physics. After that I've uh. Joint University of Delhi. As a assistant professor. And I was teaching there for more than 2 1/2 years. After that I have to. What we have with NU. As a structural fellow. In Norway. Give back to India and I'm working. I look so kidding as a. Have Malgi, postdoctoral fellow in Panama City University.

Myself, doctor Surendra Kumar Yadav and I'm working on. After electronics. Biosensors. I'll go to colleagues and biosensors. And I have done my. PhD from the University of Rome. And I've done my masters from the baby university in. In physics. After that I've uh. Joint University of Delhi. As a assistant professor. And I was teaching there for more than 2 1/2 years. After that I have to. What we have with NU. As a structural fellow. In Norway.

Myself, doctor Surendra Kumar Yadav and I'm working on. After electronics. Biosensors. I'll go to colleagues and biosensors. And I have done my. PhD from the University of Rome. And I've done my masters from the baby university in. In physics. After that I've uh. Joint University of Delhi. As a assistant professor. And I was teaching there for more than 2 1/2 years. After that I have to. What we have with NU. As a structural fellow. In Norway. Give back to India and I'm working.

So you completed your PhD at the University of Rome and your master's at BBAU, and now you're working in electronics and biosensors. Go on.

Alright, so after your master's in physics at BBAU, you joined the University of Delhi as an Assistant Professor and taught there for over two and a half years. Anything else you'd like to add about your academic journey before we move ahead?

Alright, after your time teaching at Delhi, you moved on to a structural fellowship in Norway. Is there anything else you'd like to add about your academic background, or does that cover the main highlights?

Dr. Yadav, you mentioned teaching at Delhi and working in biosensors and electronics. What's one foundational physics concept you enjoy teaching most, and why does it resonate with you or your students?

Okay, so you've recently been a postdoc fellow at Panama City University after returning to India. Earlier you mentioned biosensors and

Sorry, no. I was. Postdoctoral fellow Malviya Poststructural Fellow at Banaras Hindu University.

Thanks for clarifying — so your postdoctoral work was at Banaras Hindu University as a Malviya Fellow. You mentioned your experience teaching at Delhi and your background in physics and biosensors. When you introduce a topic like biosensors to undergraduate students, how do you make such an interdisciplinary area accessible and engaging for them?

It's biosensor is basically a device. That can be used uh, uh. On daily basis to. Monitor Healthcare.

It's biosensor is basically a device. That can be used uh, uh. On daily basis to. Monitor Healthcare. Basically when it's a device which is made-up of. Play film of semiconductor materials or metal oxides or polymers. And then you have to mobilize some biorecognition elements which can. Basically. Attached to the. The stimuli which we. Basically 1-2 cents.

Alright, so you're framing biosensors as practical healthcare tools for students. Can you give me a concrete example of a classroom activity or demonstration you've used to help students grasp how a biosensor actually works?

It's biosensor is basically a device. That can be used uh, uh. On daily basis to. Monitor Healthcare. Basically when it's a device which is made-up of. Play film of semiconductor materials or metal oxides or polymers. And then you have to mobilize some biorecognition elements which can. Basically. Attached to the. The stimuli which we. Basically 1-2 cents. So at. So once you sense. One molecule. It's since you know that. Body flumes have several other molecules as well, so once you sense one. And you fabricate 1 biosolids so that can. Since others took. So that's why you. To have biosensors which can. Just selective. Or which can specifically bind to the one. Molecule which you are best element to sense.

Alright, so you explain biosensors as devices built from thin films and biorecognition elements, connecting it to healthcare monitoring. Can you give me a concrete example of a classroom activity or demonstration you've used to help students grasp how a biosensor actually works in practice?

Alright, so you're framing biosensors as practical healthcare tools for students. Can you give me a concrete example of a classroom activity or demonstration you've used to help students grasp how a biosensor works in practice?

Yes, so biosensor is basically it sends. For example, glucose and cholesterol level monitoring. And that can be sensed easily by. Via sensor which can basically sends. Why can't your bio recognition element which binds with the cholesterol or? And glucose. And then it can tell you. The exact level. Sector mount concentration. Which is present in the day. And a human body.

Professor, looking at your publication “Nanostructured Nickel Oxide Film for Application to Fish Freshness Biosensor” in Applied Physics Letters, how did your research on biosensor selectivity and material design shape the way you teach advanced lab courses or mentor students working on sensor projects?

Yeah, so basically the. This Fister splice sensor is basically sensings and theme. With help of zentine oxidase which is already immobilized on. On the plate for. Which is 7. Metal oxide plate for nickel nanostructure decloxide. Late form and then. You sent sense this sentence. Xanthine with help of xanthine oxid.

Yeah, so basically the. This Fister splice sensor is basically sensings and theme. With help of zentine oxidase which is already immobilized on. On the plate for. Which is 7. Metal oxide plate for nickel nanostructure decloxide. Late form and then. You sent sense this sentence. Xanthine with help of xanthine oxid. And there are other present analytes were there as well. So if you. Basically. Design your nanostructure material which bind with the xanthine oxidation. Xanthine oxidation is very specific. And it cannot bind to the other. It is not really bind with the other. Interference, which can be interfering with your. Molecule if you're the desired molecule, which is which is supposed to bind with the synthene oxidate. So something oxidase only bind with the synthea. And that's. That's how it sends it's. It's actually uh, uh. Define the selectivity of their biosensor.

Yeah, so basically the. This Fister splice sensor is basically sensings and theme. With help of zentine oxidase which is already immobilized on. On the plate for. Which is 7. Metal oxide plate for nickel nanostructure decloxide. Late form and then. You sent sense this sentence. Xanthine with help of xanthine oxid. And there are other present analytes were there as well. So if you. Basically. Design your nanostructure material which bind with the xanthine oxidation. Xanthine oxidation is very specific. And it cannot bind to the other. It is not really bind with the other.

Yeah, so basically the. This Fister splice sensor is basically sensings and theme. With help of zentine oxidase which is already immobilized on. On the plate for. Which is 7. Metal oxide plate for nickel nanostructure decloxide. Late form and then. You sent sense this sentence. Xanthine with help of xanthine oxid. And there are other present analytes were there as well. So if you. Basically. Design your nanostructure material which bind with the xanthine oxidation. Xanthine oxidation is very specific.

Alright, so you immobilized xanthine oxidase on nickel oxide nanostructures for selective sensing. When you supervise student lab projects involving similar enzyme-based biosensors, what’s your approach to guiding them through troubleshooting issues like non-specific binding or sensor drift?

Alright, so you focused on binding xanthine oxidase to nickel oxide for specificity. When mentoring students on sensor projects, how do you help them troubleshoot issues with enzyme immobilization or signal interference during their experiments?

Dr., given your experience in biosensors and semiconductor materials, where do you see the most promising and fundable directions over the next three years? Are there specific grants or funding agencies you’d target to support this research?

You worked with xanthine oxidase to create selectivity using nickel oxide nanostructures. When you mentor students on sensor projects, what’s your approach for troubleshooting issues with enzyme immobilization or false positives in their experiments?

Usually Ave. Immobilized enzymes. Then it's quite possible that enzyme is not bind with your surface.

Usually Ave. Immobilized enzymes. Then it's quite possible that enzyme is not bind with your surface. So you actually check. By cleaning. Washing it with. Buffer solution.

Usually Ave. Immobilized enzymes. Then it's quite possible that enzyme is not bind with your surface. So you actually check. By cleaning. Washing it with. Buffer solution. Which is basically the. Physiological Range. Which is it's 7. PS-7 buffer solution you watched. With the PS-7 buffer solution.

Usually Ave. Immobilized enzymes. Then it's quite possible that enzyme is not bind with your surface. So you actually check. By cleaning. Washing it with. Buffer solution. Which is basically the. Physiological Range. Which is it's 7. PS-7 buffer solution you watched. With the PS-7 buffer solution. And that solution is basically wash out. The extra Sentinel oxidase which is not bind or. Some enzyme which is not bind with the. Nanostructure nucleoxide, which is basically. A hindrance. Or a resistance. To create a signal. Which can be measured, measured or. Which can be detected.

Right, so you’re saying sometimes the enzyme just doesn’t bind well to the surface, which can throw off the sensor. In your view, what are the most promising and fundable directions for your biosensor research over the next three years, and are there specific grants or agencies you’d target for support?

Right, so you check enzyme binding with buffer washes to make sure immobilization actually happened. Dr., given your experience in biosensors and semiconductor materials, where do you see the most promising and fundable directions over the next three years? Are there specific grants or funding agencies you’d pursue for this work?

Right, so you use buffer washes at pH 7 to check enzyme binding and troubleshoot immobilization issues. Now, given your experience in biosensors and semiconductor materials, where do you see the most promising and fundable directions over the next three years? Are there specific grants or funding agencies you're targeting?

Right, so you use physiological buffer washes to remove excess enzyme and ensure proper immobilization. Now, considering your experience in biosensors and semiconductor materials, where do you see the most promising and fundable directions for research over the next three years? Are there specific grants or agencies you'd target?

Yes. So basically for this research. Basically DST and Indian. An RF which is. Funding Agency. Tell me Funding Agency. Indian government which funding a lot of work on. Biomedical Field. So. That has a very bright potential to. Get or secure many funding. What's there is there are, uh, Bayrek, which is basically funding.

Yes. So basically for this research. Basically DST and Indian. An RF which is. Funding Agency. Tell me Funding Agency. Indian government which funding a lot of work on. Biomedical Field. So. That has a very bright potential to. Get or secure many funding. What's there is there are, uh, Bayrek, which is basically funding. Such kind of research which have potential to. For industrial applications like. And the diagnostic? Uh, devices which can be.

You mentioned earlier that you taught at Delhi University and Banaras Hindu University. Suppose you’re teaching a large theoretical physics class—say, 200 students—and you can’t use slides or a projector. How would you run a session that keeps everyone actively engaged and makes the material accessible?

You mentioned agencies like DST and Bayrak as promising sources for funding, especially for biomedical and industrial diagnostics research. Let’s pivot for a moment—when you’re mentoring students, especially those who might struggle with complex theoretical concepts, how do you check if your teaching methods are actually making the material accessible? What’s your process for assessing whether students really understand?

Yes, so the. The thing is. The material which is basically a metal oxides which are. Uh, most stable ones and. Making. Which can be hands on training. Easily being provided to the students and can be. Fabricated inside the lab. And people. Our students can do it.

Yes, so the. The thing is. The material which is basically a metal oxides which are. Uh, most stable ones and. Making. Which can be hands on training. Easily being provided to the students and can be. Fabricated inside the lab. And people. Our students can do it. And see, being by themselves what is uh. Doing the way which they are doing.

Yes, so the. The thing is. The material which is basically a metal oxides which are. Uh, most stable ones and. Making. Which can be hands on training. Easily being provided to the students and can be. Fabricated inside the lab. And people. Our students can do it. And see, being by themselves what is uh. Doing the way which they are doing. Or other training which they are getting which is not. Suffice so they can. They can basically interact with. The lab colleagues, They can. We can easily make them understand what. What is that problem? With the material or the film? The substrate.

Yes, so the. The thing is. The material which is basically a metal oxides which are. Uh, most stable ones and. Making. Which can be hands on training. Easily being provided to the students and can be. Fabricated inside the lab. And people. Our students can do it. And see, being by themselves what is uh. Doing the way which they are doing. Or other training which they are getting which is not. Suffice so they can. They can basically interact with. The lab colleagues, They can. We can easily make them understand what. What is that problem? With the material or the film? The substrate. Or the the sensing data. That, uh, basically. The discussion that can help.

Yes, so the. The thing is. The material which is basically a metal oxides which are. Uh, most stable ones and. Making. Which can be hands on training. Easily being provided to the students and can be. Fabricated inside the lab. And people. Our students can do it. And see, being by themselves what is uh. Doing the way which they are doing. Or other training which they are getting which is not. Suffice so they can. They can basically interact with. The lab colleagues, They can. We can easily make them understand what. What is that problem? With the material or the film? The substrate. Or the the sensing data. That, uh, basically. The discussion that can help. To dealing with. Situation very easily.

You’re saying you provide hands-on fabrication in the lab, so students actually build the devices themselves. But how do you check if the students really understand the underlying physics and not just the assembly steps? What’s your method for assessing their conceptual grasp?

Alright, so you give students hands-on exposure to fabricating metal oxide sensors, letting them see the process for themselves. But how do you check if they're actually connecting the fabrication steps to the theoretical physics behind it, and not just following the procedure? What kind of assessment or feedback do you use to make sure the concepts stick?

You’re saying you provide hands-on fabrication in the lab, so students actually build the devices themselves. But how do you check if the students really understand the underlying physics and not just the fabrication steps? What’s your process for assessing conceptual mastery?

Okay, shifting gears a bit. 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 make the materials and hands-on work the centerpiece, then encourage students to talk through challenges with each other and with you. When it comes to our institutional responsibilities, 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?

Yes. So the if, if it comes to the institutional responsibility, if we see the. Uh, the data which is uh. Not going well with the accreditations and all. So. We fix it by going with the sea. The train is what is going on in academics and what the. Recreation Council is looking for. To change in in. The Future of the. Make the courses which is. Much more. MMM. Viable for uh. Industrial Application.

Yes. So the if, if it comes to the institutional responsibility, if we see the. Uh, the data which is uh. Not going well with the accreditations and all. So. We fix it by going with the sea. The train is what is going on in academics and what the. Recreation Council is looking for. To change in in. The Future of the. Make the courses which is. Much more. MMM. Viable for uh. Industrial Application. So. So that the people. So that that. Students, basically. Can get employed. For basic aim. Which we can.

So you’re saying you’d look at what the accreditation council expects, track academic trends, and adjust courses for better industry relevance. But what would you do day-to-day to actually fix inconsistent outcome data—like, would you meet with faculty, set up rubrics, audit student work, or something else?

You’re saying you’d focus on what the accreditation council is looking for and adjust courses to help students get employed, but in practice, what would you actually do day-to-day to fix inconsistent assessment data? For example, would you set up new rubrics, run faculty workshops, audit sample grading—what’s your concrete first step?

Yeah, the workshop. Should be a starting point like. What we should do, Uh. To fix these issues if it is not. Going well with the with the data. This education. It's not going well with the accreditation councils. So then we can go for. The much more data which is available or. To to see what is going on, what's happening around the globe. To to to make these courses much more viable. Impact up and update the course we could basically. That can be poor. For the industry. But needs or maybe we can. Collaborate with the industry. And then we. Then we can have a. A joint pro. Joint program we can run. That can. Can be useful for industry as well and. Students. Like the students would be the industry ready can be. And read the choice. Because there is, there is. Yeah, usually it, it happens like academics and. Industries are. Having a little gap. Like what industry needs? An Academy as a. Providing the same. So that we can we can design a course.

Yeah, the workshop. Should be a starting point like. What we should do, Uh. To fix these issues if it is not. Going well with the with the data. This education. It's not going well with the accreditation councils. So then we can go for. The much more data which is available or. To to see what is going on, what's happening around the globe. To to to make these courses much more viable. Impact up and update the course we could basically. That can be poor. For the industry. But needs or maybe we can. Collaborate with the industry. And then we. Then we can have a. A joint pro. Joint program we can run. That can. Can be useful for industry as well and. Students. Like the students would be the industry ready can be. And read the choice.

Yeah, the workshop. Should be a starting point like. What we should do, Uh. To fix these issues if it is not. Going well with the with the data. This education. It's not going well with the accreditation councils. So then we can go for. The much more data which is available or. To to see what is going on, what's happening around the globe.

Yeah, the workshop. Should be a starting point like. What we should do, Uh. To fix these issues if it is not. Going well with the with the data. This education. It's not going well with the accreditation councils. So then we can go for. The much more data which is available or. To to see what is going on, what's happening around the globe. To to to make these courses much more viable. Impact up and update the course we could basically. That can be poor. For the industry. But needs or maybe we can. Collaborate with the industry. And then we. Then we can have a. A joint pro. Joint program we can run. That can. Can be useful for industry as well and. Students. Like the students would be the industry ready can be. And read the choice. Because there is, there is. Yeah, usually it, it happens like academics and. Industries are. Having a little gap. Like what industry needs? An Academy as a. Providing the same. So that we can we can design a course. The curriculum that can be helped. That can help the students to learn. What industry exactly needs? And that that may be the.

Let’s talk about ethical dilemmas for a moment. Suppose a student files a formal complaint, claiming your grading is biased. At the same time, your department head is pressuring you to boost pass rates. How would you handle this situation?

So you’d start with a faculty workshop and look at global trends to update courses, maybe even run joint programs with industry partners. Let’s talk about ethical dilemmas for a moment. Suppose a student files a formal complaint, claiming your grading is biased. At the same time, your department head is pressuring you to boost pass rates. How do you navigate that?

Alright, so you’d start with workshops and industry collaboration to close academic gaps. Let’s talk about ethical dilemmas for a moment. Suppose a student files a formal complaint, claiming your grading is biased. At the same time, your department head is pressuring you to boost pass rates for accreditation. How would you navigate that situation?

Alright, so you’d start by organizing a workshop to get faculty aligned, look at global trends and collaborate with industry to ensure the curriculum and assessment methods actually prepare students for the job market. Let’s talk about ethical tensions for a moment: imagine a student files a formal complaint alleging 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?

And yes, then uh. Yeah, if. This situation arises usually it shouldn't be in. In the academics, it shouldn't be happy. Once. Yeah, if. Some students not happy with the grades. Then we can, uh. You can go for a scrutiny or. Go for other faculty to get a check. Whether it is? It is OK or not?

And yes, then uh. Yeah, if. This situation arises usually it shouldn't be in. In the academics, it shouldn't be happy. Once. Yeah, if. Some students not happy with the grades. Then we can, uh. You can go for a scrutiny or. Go for other faculty to get a check. Whether it is? It is OK or not? And that's true. I think I think it's much better to to have a committee. Which can. And assess the check the. Which is fair or not? And then? Or or maybe we can have a video recording. At the time you are actually. Interviewing a student or. CS are being. And keeping on the basis depends on the. The exam methods whether it is a. Text. I mean, it's a written example. 11 So if it is a written example, then we can go to the committee which can. Fairly. The Sun. Give the grades. And one other left the Department of Obedience. Be the the head of. Committee. And he can. He can. He can lead the team and. Check with whether. Student.

You’d bring in another faculty member for a second opinion when there’s a complaint about grading. And if the department head disagrees with your approach—let’s say they insist you lower your standards to boost pass rates, even after review—how would you respond?

And yes, then uh. Yeah, if. This situation arises usually it shouldn't be in. In the academics, it shouldn't be happy. Once. Yeah, if. Some students not happy with the grades. Then we can, uh. You can go for a scrutiny or. Go for other faculty to get a check. Whether it is? It is OK or not? And that's true. I think I think it's much better to to have a committee. Which can. And assess the check the. Which is fair or not? And then? Or or maybe we can have a video recording. At the time you are actually. Interviewing a student or. CS are being. And keeping on the basis depends on the. The exam methods whether it is a. Text. I mean, it's a written example. 11 So if it is a written example, then we can go to the committee which can. Fairly. The Sun. Give the grades. And one other left the Department of Obedience. Be the the head of. Committee. And he can. He can. He can lead the team and. Check with whether. Student. Because sometimes the students are actually ill. Feeling just such teams?

And yes, then uh. Yeah, if. This situation arises usually it shouldn't be in. In the academics, it shouldn't be happy. Once. Yeah, if. Some students not happy with the grades. Then we can, uh. You can go for a scrutiny or. Go for other faculty to get a check. Whether it is? It is OK or not? And that's true. I think I think it's much better to to have a committee. Which can. And assess the check the. Which is fair or not? And then? Or or maybe we can have a video recording. At the time you are actually. Interviewing a student or. CS are being. And keeping on the basis depends on the. The exam methods whether it is a. Text. I mean, it's a written example. 11 So if it is a written example, then we can go to the committee which can. Fairly. The Sun. Give the grades. And one other left the Department of Obedience. Be the the head of. Committee. And he can. He can. He can lead the team and. Check with whether. Student. Because sometimes the students are actually ill. Feeling just such teams? We should act responsibly and. Shift more to the. Suddenly the assignment could be the choice like. You can just add that. The ability by other means as well. Would be another choice.

Sounds like you'd set up a committee to review the grading and maybe use recordings for transparency, then have the department head lead the process. If the department head pushed back and insisted you lower your standards to meet pass rate targets, how would you respond?

So you’d bring in a committee for impartial review and maybe use recordings for transparency, with the department head leading the process. If the department head pushed back and insisted you raise grades regardless of committee findings, what would you do next?

You’d bring in other faculty for a second opinion or set up a committee, maybe use recordings for transparency, and let the department head lead the process. But what if the department head insists you raise grades even if the committee finds your grading was fair and rigorous—how would you respond then?

The if if department had insist to raise the grade. Then maybe we could. Other other way to? To evaluate the. The candidate or the student? What they have learned. There are just not, just not the one way to. To evaluate what? The students have learned and. And being examined by just one way so we can. Would find other ways to. To John. Learning. Ability to learn how they are learning and how they are they are. Actually, uh. Grasping and responding. Like. Some some people are good and. In writing. Can text better? We, some people are. Go then in vocal so that we can. Take that example Vocal and that's how. We can judge their ability. That's what they've asked me. What they?

The if if department had insist to raise the grade. Then maybe we could. Other other way to? To evaluate the. The candidate or the student?

The if if department had insist to raise the grade. Then maybe we could. Other other way to? To evaluate the. The candidate or the student? What they have learned. There are just not, just not the one way to. To evaluate what? The students have learned and. And being examined by just one way so we can. Would find other ways to. To John. Learning.

The if if department had insist to raise the grade. Then maybe we could. Other other way to? To evaluate the. The candidate or the student? What they have learned. There are just not, just not the one way to. To evaluate what? The students have learned and. And being examined by just one way so we can. Would find other ways to. To John. Learning. Ability to learn how they are learning and how they are they are. Actually, uh. Grasping and responding. Like. Some some people are good and. In writing. Can text better? We, some people are. Go then in vocal so that we can. Take that example Vocal and that's how. We can judge their ability. That's what they've asked me. What they? Again, they are responding.

The if if department had insist to raise the grade. Then maybe we could. Other other way to? To evaluate the. The candidate or the student? What they have learned. There are just not, just not the one way to. To evaluate what? The students have learned and. And being examined by just one way so we can. Would find other ways to. To John. Learning. Ability to learn how they are learning and how they are they are. Actually, uh. Grasping and responding. Like. Some some people are good and. In writing. Can text better? We, some people are. Go then in vocal so that we can. Take that example Vocal and that's how. We can judge their ability. That's what they've asked me. What they? Again, they are responding. That training can help.

The if if department had insist to raise the grade. Then maybe we could. Other other way to? To evaluate the. The candidate or the student? What they have learned. There are just not, just not the one way to. To evaluate what? The students have learned and. And being examined by just one way so we can. Would find other ways to. To John. Learning. Ability to learn how they are learning and how they are they are. Actually, uh. Grasping and responding.

The if if department had insist to raise the grade. Then maybe we could. Other other way to? To evaluate the. The candidate or the student? What they have learned. There are just not, just not the one way to. To evaluate what? The students have learned and. And being examined by just one way so we can. Would find other ways to. To John. Learning. Ability to learn how they are learning and how they are they are. Actually, uh. Grasping and responding. Like. Some some people are good and. In writing.

The if if department had insist to raise the grade. Then maybe we could. Other other way to? To evaluate the. The candidate or the student? What they have learned. There are just not, just not the one way to. To evaluate what? The students have learned and. And being examined by just one way so we can. Would find other ways to. To John. Learning. Ability to learn how they are learning and how they are they are. Actually, uh. Grasping and responding. Like. Some some people are good and. In writing. Can text better? We, some people are. Go then in vocal so that we can. Take that example Vocal and that's how. We can judge their ability. That's what they've asked me. What they? Again, they are responding. That training can help. Even students like. If they are not. The writing.

The if if department had insist to raise the grade. Then maybe we could. Other other way to? To evaluate the. The candidate or the student? What they have learned. There are just not, just not the one way to. To evaluate what? The students have learned and. And being examined by just one way so we can. Would find other ways to. To John. Learning. Ability to learn how they are learning and how they are they are. Actually, uh. Grasping and responding. Like. Some some people are good and. In writing. Can text better? We, some people are. Go then in vocal so that we can. Take that example Vocal and that's how. We can judge their ability. That's what they've asked me. What they? Again, they are responding. That training can help. Even students like. If they are not. The writing. Then we can go. Examine. Agree.

Given your expertise in biosensors and semiconductor materials, do you have connections to industry or companies that could help students with internships or placements? If so, how would you leverage those relationships to benefit students here?

Alright, let's shift gears and dig into some specific skills for this role. Starting with theoretical physics—imagine you're guiding a student who's stuck on a tricky quantum mechanics concept, maybe tunneling or superposition. What's your practical approach to help them break through and actually understand it?

So you’d look for other ways to evaluate student learning if pressured to raise grades, not just stick to written exams. Let’s switch gears and talk about machine learning—imagine you’re mentoring a student who’s building a classification model for biosensor data, but the accuracy is stuck at 70 percent. What’s the first troubleshooting step you’d recommend?

So you’d try alternative ways to evaluate student learning, not just rely on written exams, if pressured to raise grades. Switching gears—let’s talk about machine learning. Imagine you’re mentoring a student who wants to build a classification model for biosensor data, but their accuracy is plateauing. What’s the first troubleshooting step you’d recommend?

So you'd try alternative ways to judge student learning—like oral exams or assignments—if the department head pushed for higher grades, to be fair to different strengths. Switching gears, when you're mentoring a student applying machine learning to semiconductor device data—say, predicting leakage currents from fabrication parameters—what's your advice for avoiding overfitting and making sure their model will actually generalize to new devices?

Okay, so you'd try oral exams or alternative formats to judge student learning if pressured to raise grades, since some students are stronger in different modes. Switching gears, let's talk about quantum computation—imagine you're teaching a class where students are struggling with the concept of qubit entanglement. How do you help them bridge the gap from textbook theory to actually applying it in a lab or simulation?

Alright, so you'd try alternative ways to judge student learning—like oral exams or assignments—if the department head pushed for higher grades, to be fair to different strengths. Switching gears, when you're mentoring a student on a machine learning project for biosensor signal analysis, how do you help them decide between a supervised and unsupervised approach?

Alright, so you’d try alternative ways to judge student learning—like oral exams or assignments—if the department head pushed for higher grades, to be fair to different strengths. Switching gears, when you're working on quantum computation projects, how do you approach debugging when an algorithm gives unexpected results? What's your first move?

Alright, you'd try alternative ways to judge student learning—like oral exams or assignments—if the department head pushed for higher grades, to be fair to different strengths. Switching gears, let's talk about machine learning. Imagine you're mentoring a student working on a biosensor project that uses machine learning for signal classification. They're getting inconsistent results. What are the first two things you'd advise them to check?

Yeah, if you're considering biosensor and machine learning. So machine learning is basically based on the data. Which is available to the machine and then. That's how machine is processing. The data and give the results. So if. The first thing is. The data which? They have. First they have to calculate it manually. Like the? Biosensor parameters are right or not.

Yeah, if you're considering biosensor and machine learning. So machine learning is basically based on the data. Which is available to the machine and then. That's how machine is processing. The data and give the results. So if. The first thing is. The data which? They have. First they have to calculate it manually. Like the? Biosensor parameters are right or not. If they. They are out in the right place. And the and the. And the check is going with the small small modules. Segment they they can they can fragment the data. Like the first. Cyclic voltammetry data. For example, they take. Google for check whether the cycle did. Voltammetry data machine is giving the right results. It's violating the the reasons or. Far away from the convergence to. Right sensing parameters.

Yeah, if you're considering biosensor and machine learning. So machine learning is basically based on the data. Which is available to the machine and then. That's how machine is processing. The data and give the results. So if. The first thing is. The data which? They have. First they have to calculate it manually. Like the? Biosensor parameters are right or not. If they. They are out in the right place. And the and the. And the check is going with the small small modules. Segment they they can they can fragment the data. Like the first. Cyclic voltammetry data. For example, they take. Google for check whether the cycle did. Voltammetry data machine is giving the right results. It's violating the the reasons or. Far away from the convergence to. Right sensing parameters. And that's how they can go with the one step by step checking and then we can. Right solution. If the machine is violating a. Or going away from the the. And. And the convergence of the. Of the particular earth. Data or particular set of data. Which umm. Which should be. Which should be outcome of the sensing device.

So you'd have them manually check biosensor parameters first to make sure the data's valid before feeding it to the model. Now, what about quantum computation—imagine a student is struggling to understand the difference between classical and quantum error correction in a practical context. How would you explain the real-world impact of that difference?

Alright, so you'd have them manually check each biosensor parameter and break down the data to see if the machine learning model is getting valid input, like with cyclic voltammetry. Now, on quantum computation—imagine a student is stuck understanding superposition in quantum circuits, and their simulation results aren't matching theory. What's your go-to way to help them bridge that gap?

Alright, you’d have them check biosensor parameters and break down the data to make sure the machine learning results are valid. Now, thinking about quantum computation—imagine a student is struggling to understand how superposition actually impacts measurement outcomes in a quantum circuit. How would you explain that to them in a way that helps them make the leap from textbook theory to real lab intuition?

Yeah. So the quantum computation is basically considered so many. Theoretical assumptions. And the computer limitations of course is there so. The Computational. Umm, the authority which they, uh, they are considering. If it is, uh. Really far away from the real.

Yeah. So the quantum computation is basically considered so many. Theoretical assumptions. And the computer limitations of course is there so. The Computational. Umm, the authority which they, uh, they are considering. If it is, uh. Really far away from the real. Real situation. Then we are theory never going to converge with experimental data. And of course, they had to. They had to see the. The percentage deviation. Of course there. Percent deviation from the real data or the. The real data which they got from the device. The sensing parameters. Which is away from the theoretical. Calculations. Then they must have to find. The right corrections which need to include in the computational quantum computational. Algorithm. And then only this correction will leads to. The right reasons for example. If I give you an example then. The fluorescence data. Usually what happens is. Like after a certain concentration. Fluorescence. Is start reabsorbing the. That the analyte is start reabsorbing the. Fluorescent signal. So they they start giving you. False results are they? They are not converging to the lead. The near fit of the calibration, So what? People. We used to do this. They do like IFE correction. They usually they. The most? Deviat data has. It meets the most everyday data, has absorbed the most of the way. Uh, reabsorb the fluorescent light. And that's. That correction needs to be. Incorporated to get the right calibration program. And that's. And then you can go and converge to the. To the computational data and the real data. And that's how they can. I think that that could be the way to. To lead the corrections should be included if it is not. We need to build it. In all your theoretical assumptions, which is? Little away from the rats. From the real. System real devices.

Yeah. So the quantum computation is basically considered so many. Theoretical assumptions. And the computer limitations of course is there so. The Computational. Umm, the authority which they, uh, they are considering. If it is, uh. Really far away from the real. Real situation. Then we are theory never going to converge with experimental data. And of course, they had to. They had to see the. The percentage deviation. Of course there. Percent deviation from the real data or the. The real data which they got from the device. The sensing parameters. Which is away from the theoretical. Calculations. Then they must have to find. The right corrections which need to include in the computational quantum computational. Algorithm. And then only this correction will leads to. The right reasons for example. If I give you an example then. The fluorescence data. Usually what happens is. Like after a certain concentration. Fluorescence. Is start reabsorbing the. That the analyte is start reabsorbing the. Fluorescent signal. So they they start giving you. False results are they? They are not converging to the lead. The near fit of the calibration, So what? People. We used to do this. They do like IFE correction. They usually they. The most? Deviat data has. It meets the most everyday data, has absorbed the most of the way. Uh, reabsorb the fluorescent light. And that's. That correction needs to be. Incorporated to get the right calibration program.

You pointed out that quantum computation has theoretical limits and students often struggle with the gap between theory and practice. Let’s shift gears—thinking about industry projects or consultancy, can you walk me through a specific collaboration you’ve had with a company or external lab? What was your role, and how did you handle conflicting priorities between academic rigor and business needs?

You brought up the importance of correcting for real-world deviations in quantum experiments—like using IFE corrections for fluorescence reabsorption. Now, thinking about research publications: say you’ve submitted a paper and reviewers challenge the experimental reproducibility of your quantum sensor results. What steps do you take to address that criticism before resubmitting?

So you’d advise them to look for percentage deviations between theoretical and real data, and add corrections to their quantum algorithms, like you did with fluorescence and IFE adjustments. Thinking about industry projects or consultancy—have you ever worked with a company on a physics-related project? If so, what was your role, and what was the hardest technical or organizational challenge you faced?

Umm, sorry I haven't worked with the. Industry. Mostly worked in the Academy. The teaching. It's difficult for me to do. Do you speculate what does actually the most challenging thing in?

Umm, sorry I haven't worked with the. Industry. Mostly worked in the Academy. The teaching. It's difficult for me to do. Do you speculate what does actually the most challenging thing in? History. If it's going with the. Physics projects and industries.

No problem, Dr., thanks for being clear about your background. Let’s switch to research publications—imagine you’ve submitted a paper on a novel biosensor to a top physics journal, but you get reviewer feedback saying your statistical analysis isn’t robust enough. What’s your first step to address that critique?

No worries, Dr., thanks for being clear about your background. Let’s switch to research publications—imagine you’ve submitted a paper on a novel biosensor to a top physics journal, but you get reviewers saying your statistical analysis isn’t robust enough. How would you address that criticism before resubmitting?

Yeah, it's very usually comments from. Reasonable comment from the top tier journals. And it is basically uh. Pushing the authenticity of the Bible. So, uh. If it is not suffice, then we consider the. The reviewers comment and then, uh. Reanalyze the data. And do all the statistics again. And then we submit. With the fresh results which came out.

Yeah, it's very usually comments from. Reasonable comment from the top tier journals. And it is basically uh. Pushing the authenticity of the Bible. So, uh. If it is not suffice, then we consider the. The reviewers comment and then, uh. Reanalyze the data. And do all the statistics again. And then we submit. With the fresh results which came out. The the statistics which have been included as per the recommendation of the. Uh, reviewer. If it is, if it is going. Going well with the with the structure of the paper, sometimes it. Go away with the. And with the scope of work. Then we can say it's It's a. Aware of the scope of the worker. This particular paper. Otherwise, we can we can usually do the. We should usually do the. Expert has suggested. Still taking this test. Symphony submitted with the. Or the corrected data which had been recommended.

You said you’d take the reviewer comments seriously, redo the statistical analysis, and resubmit with updated results. Let’s circle back—since semiconductor device physics is central to a lot of interdisciplinary research, can you describe a scenario where material defects in a thin film directly affected device performance, and how you’d diagnose and correct that in the lab?

You said you’d take reviewer feedback seriously, redo the stats, and resubmit with corrections unless it’s outside your scope—that tracks. Since semiconductor device physics is central to a lot of interdisciplinary research, suppose you’re tasked with teaching a lab course on fabrication of metal oxide semiconductors. What would be your approach for structuring the lab sessions, especially for students who’ve never done hands-on device fabrication before?

Yeah. So first I would start with the theory session. 1st I give a brief theory. Uh. Classic this and I give them a flavor about. The semiconductor device physics, how it works? And what is semiconductor device?

Yeah. So first I would start with the theory session. 1st I give a brief theory. Uh. Classic this and I give them a flavor about. The semiconductor device physics, how it works? And what is semiconductor device? Devices are. Made for so the motivation once they get the motivation. Like what? They are going to fabricate.

Yeah. So first I would start with the theory session. 1st I give a brief theory. Uh. Classic this and I give them a flavor about. The semiconductor device physics, how it works? And what is semiconductor device? Devices are. Made for so the motivation once they get the motivation. Like what? They are going to fabricate. And then and then we then we can start with the with the. The general semiconductor which is being used, for example metal oxide nanostructures. Which is the. Which could be the first step. Or maybe the synthesis of the? Semiconductor. Could be a choice. Be the starting point.

Yeah. So first I would start with the theory session. 1st I give a brief theory. Uh. Classic this and I give them a flavor about. The semiconductor device physics, how it works? And what is semiconductor device? Devices are. Made for so the motivation once they get the motivation. Like what? They are going to fabricate. And then and then we then we can start with the with the. The general semiconductor which is being used, for example metal oxide nanostructures. Which is the. Which could be the first step. Or maybe the synthesis of the? Semiconductor. Could be a choice. Be the starting point. It depends on the background. If the if the student are more interested in device fabrication or no. I'm interested in the. In creating of nanostructures or. Depending on their interest, we can. Push them to in. The projects in which they are. Much more, much more enthusiastic to do.

Okay, so you'd start lab sessions with a theory overview to give students a foundation before moving to hands-on work. For students who are nervous or completely new, what's your strategy to make sure they actually get comfortable handling the fabrication steps themselves and don't just watch someone else do it?

Okay, so you’d kick things off with a theory session to motivate them—what about the actual hands-on part? How would you handle students who are nervous or completely new to working in a clean room or with semiconductor fabrication tools?

You mentioned starting with the motivation and theory behind semiconductor device physics, then moving to practical synthesis with metal oxides. Can you walk me through one specific technical challenge students might encounter during the fabrication process, and how you’d help them solve it?

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

Uh, yeah. So this producer was basically the assistant professor, uh, research. So would I. When I get a pH D students.

Uh, yeah. So this producer was basically the assistant professor, uh, research. So would I. When I get a pH D students. Pursue No, no thanks.

Alright, yes—Assistant Professors are typically eligible to supervise PhD students, though it may depend on departmental policy and available funding. You’d be able to mentor doctoral candidates and guide their research once you’re established within the department. Anything else you’d like to ask about the position or the team?