Hello.

Please start by introducing your professional journey in academia

Hello. Hello. Can you repeat?

Just a quick intro — your name and what you've been working on in academia.

OK, I'm Kumar. And I completed my PhD. In July 2019. After that I have joined uh. An icy boat for the postdoc.

OK, I'm Kumar. And I completed my PhD. In July 2019. After that I have joined uh. An icy boat for the postdoc. My research interest in the soft matter. Especially in. Ioffer the memory. Or some bacteria.

Professor Kumar, you mentioned your trajectory from PhD to postdoc. Stepping into the classroom, what's one foundational physics concept you particularly enjoy teaching to undergraduates?

OK, I'm Kumar. And I completed my PhD. In July 2019. After that I have joined uh. An icy boat for the postdoc. My research interest in the soft matter. Especially in. Ioffer the memory. Or some bacteria. To participate so. Equilibrium and. Equilibrium and non equilibrium. Both sides.

Okay, so your focus is on soft matter and memory in bacteria — that's pretty specialized. When you've taught undergraduates, how do you introduce a complex idea like memory effects in soft matter so it doesn't overwhelm students?

Alright, you mentioned working on both equilibrium and non-equilibrium aspects in soft matter and bacterial systems

Yeah.

You mentioned focusing on soft matter, memory effects, and bacterial systems, and working at ICTS after your PhD. When you introduce a complex idea like memory in soft matter to undergraduates, how do you make that accessible in the classroom?

Yes. Yes.

Alright, you said yes, but I was hoping for a bit more detail. When you're teaching a foundational topic like thermodynamics, what's one analogy or demonstration you find really helps students grasp the concept?

Physical physics are like ensembles. And uh. How the? Copying behaves. We can write the energy and energy. Minimization, uh. All these. And this type of concept. And basically. Courses I am in. Like thermodynamics Electrod.

Physical physics are like ensembles. And uh. How the? Copying behaves. We can write the energy and energy. Minimization, uh. All these. And this type of concept. And basically. Courses I am in. Like thermodynamics Electrod. Also and. Basic mechanics, so. These are the. Set so that this I can teach Yeah.

Okay, you’re relating physical ensembles to thermodynamics, energy minimization

Alright, you mentioned teaching thermodynamics, electrodynamics, and basic mechanics. When students struggle with the idea of energy minimization in physical systems, how do you break that down in a way that actually clicks for them?

OK.

Looking at your publication, “Shape transitions during clathrin-induced endocytosis” in Physical Review E, how has your research there influenced the way you teach undergraduates about biological physics or membrane dynamics?

OK. We have a situation. Then we calculate the energy. Like in the. Done what I am doing. Unless initially the protein. Sikhil in the random. So we calculate some energy like membrane energy.

OK. We have a situation. Then we calculate the energy. Like in the. Done what I am doing. Unless initially the protein. Sikhil in the random. So we calculate some energy like membrane energy. And membrane protein interaction energy. In booking tenants. So after that. We disturbed the system a little bit like. Gene Protein. Orientation of the protein. If we calculated the. And then compare. If the. System is going in the lower. And we will consider then. OK, this is the condition otherwise. In substitution can reject this.

OK. We have a situation. Then we calculate the energy. Like in the. Done what I am doing. Unless initially the protein. Sikhil in the random. So we calculate some energy like membrane energy. And membrane protein interaction energy. In booking tenants. So after that. We disturbed the system a little bit like. Gene Protein. Orientation of the protein. If we calculated the. And then compare. If the. System is going in the lower. And we will consider then. OK, this is the condition otherwise. In substitution can reject this. Or we will consider. And what we have to help?

OK. We have a situation. Then we calculate the energy. Like in the. Done what I am doing. Unless initially the protein. Sikhil in the random. So we calculate some energy like membrane energy. And membrane protein interaction energy. In booking tenants. So after that. We disturbed the system a little bit like. Gene Protein. Orientation of the protein. If we calculated the. And then compare. If the. System is going in the lower. And we will consider then. OK, this is the condition otherwise. In substitution can reject this. Or we will consider. And what we have to help? Yeah. Random system.

So, you're walking students through calculating energy, like membrane energy, starting from a random configuration. In your publication on shape transitions during clathrin-induced endocytosis, how did you translate those advanced research ideas into something accessible for undergraduates in a classroom setting?

So you guide students through calculating energies—membrane, protein interactions—and deciding if the system's moving toward a lower energy or not. When you present this approach, do you ever encounter students who get stuck on why energy minimization even matters in real biological contexts, and if so, how do you address their skepticism?

Alright, so you’re walking students through the process: calculating energies, making small changes, checking if the system moves to lower energy, and deciding whether to accept or reject based on that. When you taught this approach, did you ever notice students struggling with the acceptance-rejection part—how did you clarify that for them in class?

You’ve connected your research in non-equilibrium soft matter with your teaching. Now, given your expertise, where do you see the most fundable research directions over the next few years? What specific grants or funding sources would you target to build a sustainable research group?

Oh, for, especially in. Is like I will write some proposal in TPT. NRFNSM also.

Oh, for, especially in. Is like I will write some proposal in TPT. NRFNSM also. Enrf. And. Many. So. For my future disaster.

Right, you’ve got experience structuring research proposals and thinking about group sustainability. Shifting to teaching—say you’re running a large introductory physics class, and you can’t use slides. How would you keep 200 students engaged and ensure they’re actually learning, not just passively listening?

Oh, for, especially in. Is like I will write some proposal in TPT. NRFNSM also. Enrf. And. Many. So. For my future disaster. Future research. You're not hearing properly, actually.

Oh, for, especially in. Is like I will write some proposal in TPT. NRFNSM also. Enrf. And. Many. So. For my future disaster. Future research. You're not hearing properly, actually. Writing spellings every time.

Kumar, you mentioned you'd write proposals for TPT, NRF, and NSM. When you design an interdisciplinary research project—say, combining machine learning and physics—how do you align the project with VIT University's aim to promote both innovation and research excellence?

You mentioned writing proposals for TPT, NRF, NSM, and others. When you design an interdisciplinary research project—say, combining machine learning and physics—how do you align the project with VIT University's emphasis on innovation and practical outcomes?

Okay, you mentioned TPT, NRF, and NSM as possible funding sources, and raised concerns about spelling and technical clarity. Let’s shift focus. Suppose you wanted to integrate quantum computation into an undergraduate curriculum, given VIT’s emphasis on emerging technologies. How would you make that accessible to students who may not have a strong math background?

OK, so. Computing, computing. We will arrange some. Or we will create. Is for and. Teach how the student can. Take in the easiest Yeah, so. Like, uh. When the vehicle. To kill particular. So where the party? Inside the. And applying the. On the walls. The inner of the Yeah, so. Like, uh. When the vehicle. To kill particular. So where the party? Inside the. And applying the. On the walls. The inner of the. Ford is applying. In shopping inside of that particle.

OK, so. Computing, computing. We will arrange some. Or we will create.

Alright, you started to say you'd arrange or create something for teaching quantum computing, but didn't finish your thought. Can you walk me through one hands-on activity or demonstration you'd use to help undergraduates actually engage with quantum computation concepts?

Yeah, so. Like, uh. When the vehicle. To kill particular. So where the party? Inside the. And applying the. On the walls. The inner of the. Ford is applying. In shopping inside of that particle. This particular particular. The. OK, so first we will decide. Finally, I will teach you how this. ******* controlling the. And how?

Yeah, so. Like, uh. When the vehicle. To kill particular. So where the party? Inside the. And applying the. On the walls. The inner of the. Ford is applying. In shopping inside of that particle. This particular particular. The. OK, so first we will decide. Finally, I will teach you how this. ******* controlling the. And how? And deforming the. Surface of OK. What is your question? Can you repeat?

Okay, so you were describing a scenario like a particle in a box, with forces acting on the walls, to help students visualize quantum behavior. How do you check if the students actually understand the concept after your demonstration, especially if they're hesitant to speak up in class?

Imagine this scenario, Professor: a student formally complains that your grading is biased, but at the same time your department head is urging you to raise pass rates. How would you navigate that situation, balancing fairness with institutional pressure?

Of course. Here’s that question again: Can you walk me through one hands-on activity or demonstration you’d use to help undergraduates grasp quantum superposition or entanglement, especially if they’re not confident in their math skills?

OK, so I have I have told you about the. Activity and. Computing. I'm not. Very much, uh. Familiar with this? So I cannot tell like about comf Yeah, yes.

OK, so I have I have told you about the. Activity and. Computing. I'm not. Very much, uh. Familiar with this?

Alright, you said you're not very familiar with quantum computing demonstrations for undergrads.

Understood. Let’s move to a scenario that comes up often in academia. Suppose a colleague approaches you to co-author a research paper, but you notice some of their data looks questionable. What steps would you take in that situation?

1st we will discuss. Why and try to recreate that data from my side and then compare?

1st we will discuss. Why and try to recreate that data from my side and then compare? And we will discuss again. Then come to the. Certain points so that. Both we can agree at that data, then we will. For lower direction.

1st we will discuss. Why and try to recreate that data from my side and then compare? And we will discuss again. Then come to the. Certain points so that. Both we can agree at that data, then we will. For lower direction. Forward directory.

Okay, so you’d talk with your colleague and try to independently recreate the data to compare results. But what if your colleague insists their data is valid and wants to submit the paper as-is—how would you handle that situation?

Now, let's discuss how you connect your research to real-world opportunities for students. Given your background in soft matter and computational modeling, do you have any industry contacts or collaborations that could help students with internships or placements, especially in emerging areas like semiconductor physics or applied machine learning?

Alright, you mentioned you’re not very familiar with quantum computing demos for undergrads, so let’s try something more aligned with your experience. Given your background in soft matter and computational modeling, do you have any industry contacts or collaborations that could help students access internships or real-world projects? If so, can you name one company, lab, or partnership you’ve worked with directly?

We have collaboration.

You mentioned you have collaboration. Can you give me one concrete example — which company or industry partner you've worked with, and how that might translate into internship or project opportunities for students?

We have collaboration. Uh, in university. Yeah, but not in. Entry level.

You said there are collaborations at the university level, but not specifically with industry for entry-level roles. Can you give me one concrete example—what company or industry partner have you worked with, and how might that translate into an internship or project opportunity for students?

OK, so those. The king, uh. Like direct delivery. Situation. Contracts for some disease. So this. These are helpful this type.

OK, so those. The king, uh. Like direct delivery. Situation. Contracts for some disease. So this. These are helpful this type. Also we prepare some model. How the outside particle come into the cell? All these. But I do not have any direction. Any direct connection? With some interesting.

You mentioned contracts related to disease and some direct delivery situations, but you didn't get into specifics. Let's shift gears. In your experience with theoretical physics, have you ever needed to choose between two competing models to explain experimental results? How did you make that decision?

You mentioned preparing models around particle

Yeah.

You confirmed you don’t have direct industry connections, but you’ve worked on models for particle entry into cells. Let’s shift. In semiconductor device physics, suppose you’re mentoring a student who’s struggling to understand why scaling down MOSFETs leads to short-channel effects. How would you explain the core issue to them in a way they’d actually grasp?

OK, four mosquito actually I have already told you. I prefer to teach Sharma. And uh. Electrodynamics. Uh, currently I'm not prepared like. Electronics.

OK, four mosquito actually I have already told you. I prefer to teach Sharma. And uh. Electrodynamics. Uh, currently I'm not prepared like. Electronics. All. So in this section. I cannot. But he will ask questions around electrodynamics.

Alright, you said you're more comfortable teaching mathematical physics and electrodynamics, not electronics or semiconductor devices. Let's talk about your teaching methods for those subjects—how do you help students struggling with the math-heavy parts of electrodynamics to actually build intuition and not just memorize equations?

Alright, so you’re more comfortable with mathematical physics and electrodynamics, not electronics or semiconductors. Let’s go with that—imagine a student says they just can’t visualize how Maxwell’s equations lead to electromagnetic waves. What’s your go-to way of making that concept click for them?

OK, that's. Uh, like I will discuss first. All Maxwell fishing. And uh. I will give a. Clear example how Wi-Fi? Guards are travelling.

OK, that's. Uh, like I will discuss first. All Maxwell fishing. And uh. I will give a. Clear example how Wi-Fi? Guards are travelling. And how much education is supporting?

OK, that's. Uh, like I will discuss first. All Maxwell fishing. And uh. I will give a. Clear example how Wi-Fi? Guards are travelling. And how much education is supporting? Without Snell and all. So that people are. Get the Wi-Fi. How I I will tell. The Wi-Fi wave. With the antenna. How it is receiving by the?

OK, that's. Uh, like I will discuss first. All Maxwell fishing. And uh. I will give a. Clear example how Wi-Fi? Guards are travelling. And how much education is supporting? Without Snell and all. So that people are. Get the Wi-Fi. How I I will tell. The Wi-Fi wave. With the antenna. How it is receiving by the? Get more clear. Kept about the Max.

So you'd start with all of Maxwell's equations, then use a clear example like how Wi-Fi signals travel to make the idea concrete. If a student still seems lost after that, is there a physical demo or visualization—something hands-on or graphical—you turn to next?

OK, that's. Uh, like I will discuss first. All Maxwell fishing. And uh. I will give a. Clear example how Wi-Fi? Guards are travelling. And how much education is supporting? Without Snell and all. So that people are. Get the Wi-Fi. How I I will tell. The Wi-Fi wave. With the antenna. How it is receiving by the? Get more clear. Kept about the Max. In the current. The previous and. Google how it is travel.

Okay, so you’d start by laying out all of Maxwell’s equations and then use something tangible like Wi-Fi signals to link the math to everyday experience. If a student still looks confused after that, is there a physical demonstration, simulation, or analogy you’d fall back on to help them finally visualize electromagnetic waves?

Alright, so you’d connect the math to something tangible, like Wi-Fi signals and antennas, to help students see how electromagnetic waves actually show up in real life. Let’s switch gears. For machine learning—imagine you’re advising a student who’s training a model, but they keep running into overfitting. What’s the first practical step you’d want them to try, and why?

So you’d use something relatable, like Wi-Fi signals and antennas, to make Maxwell’s equations real for students. Switching topics—when it comes to machine learning, if you were assigning a final project for an undergraduate physics course, what kind of problem would you choose to help students see both the potential and the limits of machine learning in physics?

Right, you’d start with the math and bridge to a Wi-Fi antenna example, connecting the equations to something students see every day. Switching tracks—for machine learning, suppose you’re advising a student choosing between a linear regression model and a random forest for predicting exam scores. What factors would you have them consider before picking one?

It depends. On the student. Which concept he takes? The and he. P. Is ready, then I will tell the some fast concept.

It depends. On the student. Which concept he takes? The and he.

It depends. On the student. Which concept he takes? The and he. P. Is ready, then I will tell the some fast concept. If he is he? Are clearer than the first thing. I will go.

Okay, so you factor in the student's comfort with the model, but what about the data itself—are there specific characteristics or patterns in the exam scores that would make you lean toward linear regression or random forest?

You focused on the student's comfort with concepts, but let's make it concrete—if the exam score data has clear linear trends with little noise, would you still suggest random forest, or is there a reason you'd lean strongly toward linear regression?

You emphasized considering the student's grasp of concepts when choosing between models. Let's shift—your resume mentions research publications. Can you describe a paper you published that you feel had real impact, and what made it significant in your field?

So 2 years back I have published a paper. Uh is very good. Because it is very colored. A lower problem.

Okay, you said it addressed a low-level problem and was well-received. Can you walk me through what made the problem challenging and what your main contribution was in that publication?

So 2 years back I have published a paper. Uh is very good. Because it is very colored. A lower problem. The real world problem. So when like. Some biological processes like. Processes signaling. Neuronal. So in this example. Cell membrane. And part in this activity. Take the part in these acts. So proved A crucial role in the membrane morally.

So 2 years back I have published a paper. Uh is very good. Because it is very colored. A lower problem. The real world problem. So when like. Some biological processes like. Processes signaling. Neuronal. So in this example. Cell membrane. And part in this activity. Take the part in these acts. So proved A crucial role in the membrane morally. First, protein bound to the surface. Uh, and then try to. OK. So. So previously it has been. Theoretically. Many people are taking one type of. But like the three meters? Endocytosis. 50 different fifty types of. What things are involved?

So 2 years back I have published a paper. Uh is very good. Because it is very colored. A lower problem. The real world problem. So when like. Some biological processes like. Processes signaling. Neuronal. So in this example. Cell membrane. And part in this activity. Take the part in these acts. So proved A crucial role in the membrane morally. First, protein bound to the surface. Uh, and then try to. OK. So. So previously it has been. Theoretically. Many people are taking one type of. But like the three meters? Endocytosis. 50 different fifty types of. What things are involved? We have developed a model. Where we have. Will my memory modeling?

So 2 years back I have published a paper. Uh is very good. Because it is very colored. A lower problem. The real world problem. So when like. Some biological processes like. Processes signaling. Neuronal. So in this example. Cell membrane. And part in this activity. Take the part in these acts. So proved A crucial role in the membrane morally. First, protein bound to the surface. Uh, and then try to. OK. So. So previously it has been. Theoretically. Many people are taking one type of. But like the three meters? Endocytosis. 50 different fifty types of. What things are involved? We have developed a model. Where we have. Will my memory modeling? Multiple of. Those different. Mending affinity. Different curvature. Showing the heavier and. Deforming.

Okay, so your publication focused on the role of cell membranes in biological signaling and tackled a real-world problem related to neuronal processes. What was one experimental or computational technique you used in that work that set your approach apart from previous studies?

Okay, so your paper tackled how different proteins interact with cell membranes in biological signaling, especially around endocytosis, and you highlighted that earlier models were too simplistic. What was one experimental or computational technique you used in this work that pushed the field forward?

You explained that your paper developed a new model for how proteins interact with cell membranes during key biological processes like signaling and endocytosis, and you addressed previous oversimplifications in the field. What was one specific challenge you faced in validating your model, and how did you address it?

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

Not now.