Please start by introducing your professional journey in academia

Hi this is. Doctor Subhash. I did. I completed. My bachelors in chemistry honors. From what is being called State University. In 2000. 13.

Hi this is. Doctor Subhash. I did. I completed. My bachelors in chemistry honors. From what is being called State University. In 2000. 13. Then I joined. West Bengal State University for my master's degree in chemistry honors. And I completed my Masters in 2015.

Hi this is. Doctor Subhash. I did. I completed. My bachelors in chemistry honors. From what is being called State University. In 2000. 13. Then I joined. West Bengal State University for my master's degree in chemistry honors. And I completed my Masters in 2015. After completing my masters, I joined. Malviya Naster Institute. Of technology. For my. And I did my PhD on the. Domain of computational and theoretical chemistry. And I completed my PhD in 2021. Followed by a joint. Hebrew University of Jerusalem. For my postdoctoral research under the supervision of Professor Noam Agmer. And under the in the Hebrew University.

Hi this is. Doctor Subhash. I did. I completed. My bachelors in chemistry honors. From what is being called State University. In 2000. 13. Then I joined. West Bengal State University for my master's degree in chemistry honors. And I completed my Masters in 2015. After completing my masters, I joined. Malviya Naster Institute. Of technology. For my. And I did my PhD on the. Domain of computational and theoretical chemistry. And I completed my PhD in 2021.

Okay, you did your bachelor's in chemistry honors from Burdwan State University in 2013—go on.

Hi this is. Doctor Subhash. I did. I completed. My bachelors in chemistry honors. From what is being called State University. In 2000. 13. Then I joined. West Bengal State University for my master's degree in chemistry honors. And I completed my Masters in 2015. After completing my masters, I joined. Malviya Naster Institute. Of technology. For my. And I did my PhD on the. Domain of computational and theoretical chemistry. And I completed my PhD in 2021. Followed by a joint. Hebrew University of Jerusalem. For my postdoctoral research under the supervision of Professor Noam Agmer. And under the in the Hebrew University. I was. About 3 1/2 years and I worked on the. Uh. Computational simulation or the biology?

Hi this is. Doctor Subhash. I did. I completed. My bachelors in chemistry honors. From what is being called State University. In 2000. 13. Then I joined. West Bengal State University for my master's degree in chemistry honors. And I completed my Masters in 2015. After completing my masters, I joined. Malviya Naster Institute. Of technology. For my. And I did my PhD on the. Domain of computational and theoretical chemistry. And I completed my PhD in 2021. Followed by a joint. Hebrew University of Jerusalem. For my postdoctoral research under the supervision of Professor Noam Agmer. And under the in the Hebrew University. I was. About 3 1/2 years and I worked on the. Uh. Computational simulation or the biology? And broken transportation. After completing. 1st post journey I. Back to India and a joint. PIA per Mumbai. For my second post-doc under. Supervision of. Doctor Amartya Bose. And after six months of working in the field of machine learner's potential generation. I have joined as the assistant professor in the. Bharat Institute of Technology.

Hi this is. Doctor Subhash. I did. I completed. My bachelors in chemistry honors. From what is being called State University. In 2000. 13. Then I joined. West Bengal State University for my master's degree in chemistry honors. And I completed my Masters in 2015. After completing my masters, I joined. Malviya Naster Institute. Of technology. For my. And I did my PhD on the. Domain of computational and theoretical chemistry. And I completed my PhD in 2021. Followed by a joint. Hebrew University of Jerusalem. For my postdoctoral research under the supervision of Professor Noam Agmer. And under the in the Hebrew University. I was. About 3 1/2 years and I worked on the. Uh. Computational simulation or the biology? And broken transportation. After completing. 1st post journey I. Back to India and a joint. PIA per Mumbai. For my second post-doc under. Supervision of. Doctor Amartya Bose. And after six months of working in the field of machine learner's potential generation. I have joined as the assistant professor in the. Bharat Institute of Technology. And currently I'm working here as Esther. Historian. Chemistry Department.

Alright, so after your bachelor's, you went on to do your master's in chemistry at West Bengal State University and finished in 2015. Tell me about the next steps in your academic journey after your master's.

Alright, so you completed your PhD in computational and theoretical chemistry at Malviya National Institute of Technology in 2021. Is there anything else from your academic or professional journey you'd like to add before we move forward?

Okay, so after your PhD in computational and theoretical chemistry at Malviya National Institute of Technology, you went on to do postdoctoral research at Hebrew University of Jerusalem under Professor Noam Agmon. Can you describe one foundational chemistry concept that you particularly enjoy teaching to students, and why it resonates with you?

So you spent about three and a half years at Hebrew University working on computational simulation in biology. For your teaching, do you have a favorite foundational concept in chemistry or computational modeling that you find especially rewarding to explain to students?

Alright, so after your postdoc in Jerusalem working on computational biology and proton transport, you did a second postdoc at PIAPER Mumbai focused on machine learning for potential generation, and now you're an assistant professor at Bharat Institute of Technology. Since you’ve taught at the university level, can you describe a foundational chemistry or computational concept you especially enjoy teaching in the classroom, and what makes it meaningful for your students?

Okay, so you’re currently serving as an assistant professor in the Chemistry Department at Bharat Institute of Technology after a series of postdocs focused on computational biology and machine learning for chemistry. When you’re teaching a lab or theory course, what’s one strategy you use to help students grasp complex or abstract topics?

Yeah, during that teaching. Mainly I found that whenever I can. Connect, uh, the. Theoretical problem with the real life problem. They can easily connect. Their importance and all these things.

Yeah, during that teaching. Mainly I found that whenever I can. Connect, uh, the. Theoretical problem with the real life problem. They can easily connect. Their importance and all these things. And most importantly, during the lab, whenever they are performed in the experiments when I'm explaining and they are seeing it in. And visualization it. It helps them they are clarify their understanding. They gained their interest on the Subs.

Right, so you’ve found that connecting theoretical problems to real-life situations helps students see their importance—makes sense. Can you give me a concrete example from one of your recent courses where you used this approach and noticed a change in student understanding or engagement?

Yeah, during that teaching. Mainly I found that whenever I can. Connect, uh, the. Theoretical problem with the real life problem. They can easily connect. Their importance and all these things. And most importantly, during the lab, whenever they are performed in the experiments when I'm explaining and they are seeing it in. And visualization it. It helps them they are clarify their understanding. They gained their interest on the Subs. Text I can. From my side.

That's an interesting point. Could you elaborate a bit more on that?

So you mentioned that visualization during lab sessions helps clarify concepts for your students and keeps them more engaged. I noticed you published a paper in Nature Communications on “Multi-Proton dynamics near membrane-water interface.” How would you break down the core idea of that research for an undergraduate class with only a basic background in chemistry?

Actually. Well, it is a very fundamental. Work in the. Biochemistry Field. Actually. This multiple transportation. In the membrane water interface actually. Play is a crucial role in our. Bioenergetics and energy transistor in piolets.

Actually. Well, it is a very fundamental. Work in the. Biochemistry Field. Actually. This multiple transportation. In the membrane water interface actually. Play is a crucial role in our. Bioenergetics and energy transistor in piolets. And they can, exactly. Anyone without having any more knowledge in chemistry?

Actually. Well, it is a very fundamental. Work in the. Biochemistry Field. Actually. This multiple transportation. In the membrane water interface actually. Play is a crucial role in our. Bioenergetics and energy transistor in piolets. And they can, exactly. Anyone without having any more knowledge in chemistry? They can. They know that. The main energy currency. Of our body is. It and the synthesis of. ATP is mainly. Or there is an important role of this proton transportation in the synthesis of at? From AD. So actually, what happened? When did the proton transportation occurs? From. The proton. Farm to 80% is. This transportation, the mechanism of transportation is actually unclear. And my study actually clarified. I need to clarify.

Okay, so you’re saying multiple proton transport at the membrane-water interface is key for bioenergetics and energy transfer in biological systems. If you had to design an undergraduate lab or class activity to help students understand this process—not just memorize it—how would you structure that?

Given your background in computational and theoretical chemistry, where do you see the most fundable research directions over the next three years? Which grants or external funding streams would you prioritize to support your work?

Actually. Well, it is a very fundamental. Work in the. Biochemistry Field. Actually. This multiple transportation. In the membrane water interface actually. Play is a crucial role in our. Bioenergetics and energy transistor in piolets. And they can, exactly. Anyone without having any more knowledge in chemistry? They can. They know that. The main energy currency. Of our body is. It and the synthesis of. ATP is mainly. Or there is an important role of this proton transportation in the synthesis of at? From AD. So actually, what happened? When did the proton transportation occurs? From. The proton. Farm to 80% is. This transportation, the mechanism of transportation is actually unclear. And my study actually clarified. I need to clarify. The mechanism of this transportation of this proton pump. Towards this epic synthesis. Across the. Membrane surface. So. But clearly, uh. Explain the score fundamental mechanism. Using add initiative molecular dynamics method. And will perform a series of simulation. Taking considering how? Fusps are states of a membrane. With a small patch of membrane. And we simulated the transfer of the proteins. From one side to another side there are mechanism that diffusion. Actually. Series of experiments also on the reclusion of this membrane. Depletion of. And the surprise? Whenever proton diffuse is. The elaborate the diffusion rate is little bit higher. Then the proton equation rate. In the pulp. In the previous theoretical studies or attempt. Could not explain with his path. They found that the proton transportations of the. Surface of the membranes. Even 10 times lower. As it got stacked. On the hydrophilic region of the main.

Actually. Well, it is a very fundamental. Work in the. Biochemistry Field. Actually. This multiple transportation. In the membrane water interface actually. Play is a crucial role in our. Bioenergetics and energy transistor in piolets. And they can, exactly. Anyone without having any more knowledge in chemistry? They can. They know that. The main energy currency. Of our body is. It and the synthesis of. ATP is mainly. Or there is an important role of this proton transportation in the synthesis of at? From AD. So actually, what happened? When did the proton transportation occurs? From. The proton. Farm to 80% is. This transportation, the mechanism of transportation is actually unclear. And my study actually clarified. I need to clarify. The mechanism of this transportation of this proton pump. Towards this epic synthesis. Across the. Membrane surface. So. But clearly, uh. Explain the score fundamental mechanism. Using add initiative molecular dynamics method. And will perform a series of simulation. Taking considering how? Fusps are states of a membrane. With a small patch of membrane. And we simulated the transfer of the proteins. From one side to another side there are mechanism that diffusion. Actually. Series of experiments also on the reclusion of this membrane. Depletion of. And the surprise? Whenever proton diffuse is. The elaborate the diffusion rate is little bit higher. Then the proton equation rate. In the pulp. In the previous theoretical studies or attempt. Could not explain with his path. They found that the proton transportations of the. Surface of the membranes. Even 10 times lower. As it got stacked. On the hydrophilic region of the main. We found that when we can introduce more than one protocol. Exactly multi proton.

Actually. Well, it is a very fundamental. Work in the. Biochemistry Field. Actually. This multiple transportation. In the membrane water interface actually. Play is a crucial role in our. Bioenergetics and energy transistor in piolets. And they can, exactly. Anyone without having any more knowledge in chemistry? They can. They know that. The main energy currency. Of our body is. It and the synthesis of. ATP is mainly. Or there is an important role of this proton transportation in the synthesis of at? From AD. So actually, what happened? When did the proton transportation occurs? From. The proton. Farm to 80% is. This transportation, the mechanism of transportation is actually unclear. And my study actually clarified. I need to clarify. The mechanism of this transportation of this proton pump. Towards this epic synthesis. Across the. Membrane surface. So. But clearly, uh. Explain the score fundamental mechanism. Using add initiative molecular dynamics method. And will perform a series of simulation. Taking considering how? Fusps are states of a membrane. With a small patch of membrane. And we simulated the transfer of the proteins. From one side to another side there are mechanism that diffusion. Actually. Series of experiments also on the reclusion of this membrane. Depletion of. And the surprise? Whenever proton diffuse is. The elaborate the diffusion rate is little bit higher. Then the proton equation rate. In the pulp. In the previous theoretical studies or attempt. Could not explain with his path. They found that the proton transportations of the. Surface of the membranes. Even 10 times lower. As it got stacked. On the hydrophilic region of the main. We found that when we can introduce more than one protocol. Exactly multi proton. Then the some protons. Saturate this protocol site of membrane. And the X token can diffuse faster. Than the water. And this is. Fundamental idea. Of this and we also found that with a growing. Away from this nameplate, the proton almost. Perhaps like a?

Okay, so your research clarified the mechanism behind proton transport in ATP synthesis, which is a major factor in cellular energy. Given the importance of this work, how would you go about building an interdisciplinary research group around proton transport, and what kinds of external funding or industry partnerships would you seek to make it sustainable?

So you clarified the mechanism of proton transport across the membrane for ATP synthesis using advanced molecular dynamics simulations, and compared your results to prior theoretical and experimental findings. Given the complexity of this work, what would be your strategy for building international academic collaborations to further advance research output and visibility—especially at an institution like VIT that values global partnerships?

So your simulations revealed that introducing multiple protons actually increased the diffusion rate at the membrane interface, which contradicted some earlier theoretical models. Given that, if you were planning to scale up this research into a larger group project at your current institution, what would your strategy be for securing external funding or grants, especially considering the competitive landscape in computational chemistry?

Okay, Dr., let's talk about teaching. Suppose you have to design a new course module in your area—say, computational biochemistry or membrane transport—at VIT, where active learning and industry relevance are emphasized. How would you ensure that the content stays modern, connects with real-world industry trends, and still meets accreditation standards?

Exactly. That is a very good opportunity to me.

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots.

Right, you see it as a real opportunity to design a course that’s both modern and aligned with industry. Walk me through how you’d actually check if your approach is working—what sorts of feedback or assessment would you use to know students are really grasping the material, not just memorizing?

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane.

Right, so you’re thinking about building new course content and making sure students are actually connecting with it, not just sitting through lectures. Let’s shift a bit—accreditation cycles can be pretty demanding. Say you join our department and find that outcome assessment data is inconsistent across courses. How would you approach fixing that?

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus.

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus. But. Beyond this. Actually. The proton transportations or the? Pilot Scale. Computational Biological. Simulations of anticoagulant biochemistry.

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus. But. Beyond this. Actually. The proton transportations or the? Pilot Scale. Computational Biological. Simulations of anticoagulant biochemistry. Against two or three major.

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus. But. Beyond this. Actually. The proton transportations or the? Pilot Scale. Computational Biological. Simulations of anticoagulant biochemistry. Against two or three major. Like past. Space Oceans is actually. You can. Poor screen simulations for a large look. Systems.

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus. But. Beyond this. Actually. The proton transportations or the? Pilot Scale. Computational Biological. Simulations of anticoagulant biochemistry. Against two or three major. Like past. Space Oceans is actually. You can. Poor screen simulations for a large look. Systems. So equity. Size we need to specifically choose. The suitable methods. It's a possible screws paint. Simulation techniques. And followed by we can go to this. Mt simulations using. Conventional post-filled methods.

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus. But. Beyond this. Actually. The proton transportations or the? Pilot Scale. Computational Biological. Simulations of anticoagulant biochemistry. Against two or three major. Like past. Space Oceans is actually. You can. Poor screen simulations for a large look. Systems. So equity. Size we need to specifically choose. The suitable methods. It's a possible screws paint. Simulation techniques. And followed by we can go to this. Mt simulations using. Conventional post-filled methods. For with considering all. All. But. For this one we need to consider. A moderately small size. Deep chemical reactions where? Bond breaking. And what for me? Is important for that kind of assistance we need.

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus. But. Beyond this. Actually. The proton transportations or the? Pilot Scale. Computational Biological. Simulations of anticoagulant biochemistry. Against two or three major. Like past. Space Oceans is actually. You can. Poor screen simulations for a large look. Systems. So equity. Size we need to specifically choose. The suitable methods. It's a possible screws paint. Simulation techniques. And followed by we can go to this. Mt simulations using. Conventional post-filled methods. For with considering all. All. But. For this one we need to consider. A moderately small size. Deep chemical reactions where? Bond breaking. And what for me? Is important for that kind of assistance we need. Uh, all the liquid from uh. Calculations like app initial, molecular economics or. And so past. We can start with the coarse grained molecular dynamics modeling. Followed by this. Possibility based. The method coastal based. Matter simulation method. MD simulation method.

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus. But. Beyond this. Actually. The proton transportations or the? Pilot Scale. Computational Biological. Simulations of anticoagulant biochemistry. Against two or three major. Like past. Space Oceans is actually. You can. Poor screen simulations for a large look. Systems. So equity. Size we need to specifically choose. The suitable methods. It's a possible screws paint. Simulation techniques. And followed by we can go to this. Mt simulations using. Conventional post-filled methods. For with considering all. All. But. For this one we need to consider. A moderately small size. Deep chemical reactions where? Bond breaking. And what for me? Is important for that kind of assistance we need. Uh, all the liquid from uh. Calculations like app initial, molecular economics or. And so past. We can start with the coarse grained molecular dynamics modeling. Followed by this. Possibility based. The method coastal based. Matter simulation method. MD simulation method. Then we can start. Pause brief introductions to AB initial multiplayer dynamics. On the focused on BOND. T identity, that kind of things.

Alright, you’re clearly thinking about integrating modern computational tools and industry developments into your curriculum. Let’s say you join our department and discover that outcome assessment data—like student learning outcomes or course evaluations—is inconsistent across different courses. How would you approach fixing that to make sure we’re meeting accreditation standards?

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus. But. Beyond this. Actually. The proton transportations or the? Pilot Scale. Computational Biological. Simulations of anticoagulant biochemistry. Against two or three major. Like past. Space Oceans is actually. You can. Poor screen simulations for a large look. Systems. So equity. Size we need to specifically choose. The suitable methods. It's a possible screws paint. Simulation techniques. And followed by we can go to this. Mt simulations using. Conventional post-filled methods. For with considering all. All. But. For this one we need to consider. A moderately small size. Deep chemical reactions where? Bond breaking. And what for me? Is important for that kind of assistance we need. Uh, all the liquid from uh. Calculations like app initial, molecular economics or. And so past. We can start with the coarse grained molecular dynamics modeling. Followed by this. Possibility based. The method coastal based. Matter simulation method. MD simulation method. Then we can start. Pause brief introductions to AB initial multiplayer dynamics. On the focused on BOND. T identity, that kind of things. Then as this method starts. Are free, very uh. The demand in computational demanding and. Very expensive computationally. Send it. SM empirical methods like DMTB plus. A few methods. This kind of things we can introduce in our syllabus.

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus. But. Beyond this. Actually. The proton transportations or the? Pilot Scale. Computational Biological. Simulations of anticoagulant biochemistry. Against two or three major. Like past. Space Oceans is actually. You can. Poor screen simulations for a large look. Systems. So equity. Size we need to specifically choose. The suitable methods. It's a possible screws paint. Simulation techniques. And followed by we can go to this. Mt simulations using. Conventional post-filled methods. For with considering all. All. But. For this one we need to consider. A moderately small size. Deep chemical reactions where? Bond breaking. And what for me? Is important for that kind of assistance we need. Uh, all the liquid from uh. Calculations like app initial, molecular economics or. And so past. We can start with the coarse grained molecular dynamics modeling. Followed by this. Possibility based. The method coastal based. Matter simulation method. MD simulation method. Then we can start. Pause brief introductions to AB initial multiplayer dynamics. On the focused on BOND. T identity, that kind of things. Then as this method starts. Are free, very uh. The demand in computational demanding and. Very expensive computationally. Send it. SM empirical methods like DMTB plus. A few methods.

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus. But. Beyond this. Actually. The proton transportations or the? Pilot Scale. Computational Biological. Simulations of anticoagulant biochemistry. Against two or three major. Like past. Space Oceans is actually. You can. Poor screen simulations for a large look. Systems. So equity. Size we need to specifically choose. The suitable methods. It's a possible screws paint. Simulation techniques. And followed by we can go to this. Mt simulations using. Conventional post-filled methods. For with considering all. All. But. For this one we need to consider. A moderately small size. Deep chemical reactions where? Bond breaking. And what for me? Is important for that kind of assistance we need. Uh, all the liquid from uh. Calculations like app initial, molecular economics or. And so past. We can start with the coarse grained molecular dynamics modeling. Followed by this. Possibility based. The method coastal based. Matter simulation method. MD simulation method. Then we can start. Pause brief introductions to AB initial multiplayer dynamics. On the focused on BOND. T identity, that kind of things. Then as this method starts. Are free, very uh. The demand in computational demanding and. Very expensive computationally. Send it. SM empirical methods like DMTB plus. A few methods. This kind of things we can introduce in our syllabus. Then at the last we can introduce. The building of this machine, that field. From the edge gathering. The information is how we can build the. Machine learning based post field which can help. To simulate long range simulations with having. A high number of. Like this kind of thing so. This would be a stepwise breakdown. First, we can start with. Force print simulations. Complex and. Large size biological systems. Then we can break. Commit to the Postscript based MTC. Moderately. Large size biological systems.

Alright, so you’d start by grounding the course in advanced simulation techniques and making sure it’s systematic, but you’ve also mentioned the importance of connecting to current industry trends. Can you give a concrete example of how you would check if your new module actually aligns with accreditation requirements—like, would you consult industry partners, use outcome data, or something else?

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus. But. Beyond this. Actually. The proton transportations or the? Pilot Scale. Computational Biological. Simulations of anticoagulant biochemistry. Against two or three major. Like past. Space Oceans is actually. You can. Poor screen simulations for a large look. Systems. So equity. Size we need to specifically choose. The suitable methods. It's a possible screws paint. Simulation techniques. And followed by we can go to this. Mt simulations using. Conventional post-filled methods. For with considering all. All. But. For this one we need to consider. A moderately small size. Deep chemical reactions where? Bond breaking. And what for me? Is important for that kind of assistance we need. Uh, all the liquid from uh. Calculations like app initial, molecular economics or. And so past. We can start with the coarse grained molecular dynamics modeling. Followed by this. Possibility based. The method coastal based. Matter simulation method. MD simulation method. Then we can start. Pause brief introductions to AB initial multiplayer dynamics. On the focused on BOND. T identity, that kind of things. Then as this method starts. Are free, very uh. The demand in computational demanding and. Very expensive computationally. Send it. SM empirical methods like DMTB plus. A few methods. This kind of things we can introduce in our syllabus. Then at the last we can introduce. The building of this machine, that field. From the edge gathering. The information is how we can build the. Machine learning based post field which can help. To simulate long range simulations with having. A high number of. Like this kind of thing so. This would be a stepwise breakdown. First, we can start with. Force print simulations. Complex and. Large size biological systems. Then we can break. Commit to the Postscript based MTC. Moderately. Large size biological systems. And then for AI MD or UMT. For this small particular system, but. Which are uh. Uh, chemically active or bond breaking and formations going on?

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus. But. Beyond this. Actually. The proton transportations or the? Pilot Scale. Computational Biological. Simulations of anticoagulant biochemistry. Against two or three major. Like past. Space Oceans is actually. You can. Poor screen simulations for a large look. Systems. So equity. Size we need to specifically choose. The suitable methods. It's a possible screws paint. Simulation techniques. And followed by we can go to this. Mt simulations using. Conventional post-filled methods. For with considering all. All. But. For this one we need to consider. A moderately small size. Deep chemical reactions where? Bond breaking. And what for me? Is important for that kind of assistance we need. Uh, all the liquid from uh. Calculations like app initial, molecular economics or. And so past. We can start with the coarse grained molecular dynamics modeling. Followed by this. Possibility based. The method coastal based. Matter simulation method. MD simulation method. Then we can start. Pause brief introductions to AB initial multiplayer dynamics. On the focused on BOND. T identity, that kind of things. Then as this method starts. Are free, very uh. The demand in computational demanding and. Very expensive computationally. Send it. SM empirical methods like DMTB plus. A few methods. This kind of things we can introduce in our syllabus. Then at the last we can introduce. The building of this machine, that field. From the edge gathering. The information is how we can build the. Machine learning based post field which can help. To simulate long range simulations with having. A high number of. Like this kind of thing so. This would be a stepwise breakdown. First, we can start with. Force print simulations. Complex and. Large size biological systems. Then we can break. Commit to the Postscript based MTC. Moderately. Large size biological systems. And then for AI MD or UMT. For this small particular system, but. Which are uh. Uh, chemically active or bond breaking and formations going on? And and this kind of things need to be, uh. A study under aimed or. Electronic structure calculations like the optic calculations.

Alright, so you’d focus on a systematic breakdown—grounding the course in advanced simulation techniques, connecting to the latest industry shifts, and going further than typical electives. Beyond curriculum design, if you were guiding interdisciplinary postgraduate research—say, in areas like Genetic Counselling or Food Science and Technology, which are key to VIT’s mission—how would you help students bridge gaps between their core field and those adjacent domains?

Alright, so you’d focus on breaking the course into major modules, integrating advanced simulation techniques and connecting with the rise of machine learning and quantum computing as relevant industry trends. Let’s shift a bit — accreditation cycles can be pretty demanding. If you joined our department and discovered that outcome assessment data was inconsistent across courses, how would you approach fixing that?

You brought up integrating machine learning and quantum computing trends, and building beyond typical electives—so, imagine you join our department and notice that outcome assessment data is inconsistent across courses, which could impact accreditation. How would you go about addressing that issue day-to-day?

Exactly. That is a very good opportunity to me. To build a. Computational. Or new course like computational biochemistry. Important transportation in pilots. So actually. I would. It would be fast, I would recommend as we are now. In the era of. Machine learning. Simulations and all these things, very advanced simulation techniques. Earth came out and also. We are going. Maybe in the next few years we can have this. Quantum computers on all these things. But left these things. If iota. Have this opportunity to build a. New course on the basis of computational biochemistry or preferred transportation of membrane. First I would like. Breakdown is systematically. In the first case. As I already said, there is a. Elective course. Computational Simulations. Or molecular dynamics simulations process. Already in the electric force of this pit syllabus. But. Beyond this. Actually. The proton transportations or the? Pilot Scale. Computational Biological. Simulations of anticoagulant biochemistry. Against two or three major. Like past. Space Oceans is actually. You can. Poor screen simulations for a large look. Systems. So equity. Size we need to specifically choose. The suitable methods. It's a possible screws paint. Simulation techniques. And followed by we can go to this. Mt simulations using. Conventional post-filled methods. For with considering all. All. But. For this one we need to consider. A moderately small size. Deep chemical reactions where? Bond breaking. And what for me? Is important for that kind of assistance we need. Uh, all the liquid from uh. Calculations like app initial, molecular economics or. And so past. We can start with the coarse grained molecular dynamics modeling. Followed by this. Possibility based. The method coastal based. Matter simulation method. MD simulation method. Then we can start. Pause brief introductions to AB initial multiplayer dynamics. On the focused on BOND. T identity, that kind of things. Then as this method starts. Are free, very uh. The demand in computational demanding and. Very expensive computationally. Send it. SM empirical methods like DMTB plus. A few methods. This kind of things we can introduce in our syllabus. Then at the last we can introduce. The building of this machine, that field. From the edge gathering. The information is how we can build the. Machine learning based post field which can help. To simulate long range simulations with having. A high number of. Like this kind of thing so. This would be a stepwise breakdown. First, we can start with. Force print simulations. Complex and. Large size biological systems. Then we can break. Commit to the Postscript based MTC. Moderately. Large size biological systems. And then for AI MD or UMT. For this small particular system, but. Which are uh. Uh, chemically active or bond breaking and formations going on? And and this kind of things need to be, uh. A study under aimed or. Electronic structure calculations like the optic calculations. Followed by weekend. Go to this. Let's learn this potential generation which may. Uh, take time, but. We can. Put it in our syllabus using some. Already available codes like. TMT mess. Kind of package.

Alright, so you’d break down the course into core simulation methods, address the evolution of industry techniques like machine learning and quantum computing, and make sure your approach goes beyond standard electives. When it comes to meeting accreditation requirements—say, mapping learning outcomes to national or international standards—what’s your process for ensuring the course content and assessments consistently align with those benchmarks year after year?

Alright, so you’d build the module by systematically integrating advanced simulations, adapting to rapid changes in the field, and making sure the teaching methods match what’s current in industry. If you joined our department and found that outcome assessment data was inconsistent across courses, how would you approach fixing that?

Alright, so you’d break the module into layers—starting with coarse-grained simulations, moving through classical MD, and including quantum mechanical approaches, all while keeping pace with emerging trends like machine learning. But let’s say you join the department and, during an accreditation cycle, you discover outcome assessment data is inconsistent across faculty in your area. What concrete steps would you take to fix that?

Alright, so you’d break the course into methods like coarse-grained simulations, classical molecular dynamics, and ab initio techniques, making sure students see how these approaches fit evolving industry needs. Now, let’s say you join our department and realize the outcome assessment data for those modules is inconsistent—how would you go about bringing that data in line with accreditation standards?

Alright, you emphasized adapting the course to cutting-edge simulation methods and computational demands as the field evolves. Now, say you join and discover our department’s outcome assessment data is inconsistent across courses—maybe rubrics aren’t standardized, or reporting is uneven. How would you go about fixing that in a way that meets both internal review and external accreditation standards?

You talked through how you’d structure the course using modern simulation methods and even integrate emerging computational techniques, which shows a solid awareness of keeping curriculum current. But at VIT, there’s also a strong expectation that faculty help guide interdisciplinary research—especially in areas like Genetic Counselling or Food Science and Technology, where computational skills meet practical application. How would you mentor postgraduate or PhD students working on interdisciplinary projects in these fields?

Alright, so you'd structure the module stepwise, starting with coarse-grained simulations, moving through classical MD, and then on to ab initio and machine learning methods—making sure students see both the computational depth and the connection to industry. Now, accreditation cycles can be pretty demanding. If you joined our department and found that outcome assessment data was inconsistent across courses, what would be your first steps to address and standardize that?

Alright, so you’d build the module stepwise, moving from coarse-grained simulations up through ab initio and machine learning-driven methods—making sure students see both the computational advances and how they connect to real research and industry. Now, accreditation cycles can be pretty demanding. If you joined and discovered our department’s outcome assessment data was inconsistent across courses, what would be your approach to fixing that?

Alright, you laid out a thoughtful structure for the course—connecting simulation methods, scaling to different system sizes, and even integrating machine learning and quantum approaches. But let’s shift: day-to-day, accreditation isn’t just about advanced content. Imagine you join VIT and discover the outcome assessment data for your courses is inconsistent or incomplete. What would be your first steps to address and fix that problem?

Alright, so you’d structure the module stepwise, starting with coarse-grained simulations, moving through classical MD, and then on to ab initio and machine learning methods—making sure students see both the computational advances and the real-world applications. Now, accreditation cycles can be pretty rigorous. If you joined and found that outcome assessment data was inconsistent across courses—say, rubrics didn’t match or student learning outcomes weren’t being tracked well—how would you go about fixing that?

OK, actually. This is. This is not a problem. Actually this is a. The basic things that some of the students cannot be. With your own success.

OK, actually. This is. This is not a problem. Actually this is a. The basic things that some of the students cannot be. With your own success. That time. And if they're interested, I can also arrange some expert talk from Internet. Since faculties or expert on this field. Uh, to ensure that they are more connectivity. Or more tip to this knowledge.

OK, actually. This is. This is not a problem. Actually this is a. The basic things that some of the students cannot be. With your own success. That time. And if they're interested, I can also arrange some expert talk from Internet. Since faculties or expert on this field.

OK, actually. This is. This is not a problem. Actually this is a. The basic things that some of the students cannot be. With your own success. That time. And if they're interested, I can also arrange some expert talk from Internet. Since faculties or expert on this field. Uh, to ensure that they are more connectivity. Or more tip to this knowledge. I would like to. Keep short. A real high problem.

Alright, Dr., let's shift to something a bit different. Imagine this scenario: a student submits a formal complaint, claiming your grading is biased. At the same time, your department head is urging you to raise pass rates in your course. How would you handle this situation and make sure both academic integrity and institutional expectations are respected?

OK, actually. This is. This is not a problem. Actually this is a. The basic things that some of the students cannot be. With your own success. That time. And if they're interested, I can also arrange some expert talk from Internet. Since faculties or expert on this field. Uh, to ensure that they are more connectivity. Or more tip to this knowledge. I would like to. Keep short. A real high problem. You using these methods? As they get can. Directly, Does this method really help to solve the real life problem?

OK, actually. This is. This is not a problem. Actually this is a. The basic things that some of the students cannot be. With your own success. That time. And if they're interested, I can also arrange some expert talk from Internet. Since faculties or expert on this field. Uh, to ensure that they are more connectivity. Or more tip to this knowledge. I would like to. Keep short. A real high problem. You using these methods? As they get can. Directly, Does this method really help to solve the real life problem? And that's how they can build their interest on this. Field of computational simulation. When they can connect this? Methods actually. Not in the paper. Pen and paper of this can actually.

OK, actually. This is. This is not a problem. Actually this is a. The basic things that some of the students cannot be. With your own success. That time. And if they're interested, I can also arrange some expert talk from Internet. Since faculties or expert on this field. Uh, to ensure that they are more connectivity. Or more tip to this knowledge. I would like to. Keep short. A real high problem. You using these methods? As they get can. Directly, Does this method really help to solve the real life problem? And that's how they can build their interest on this. Field of computational simulation. When they can connect this? Methods actually. Not in the paper. Pen and paper of this can actually. Of the real life problem and using these methods.

OK, actually. This is. This is not a problem. Actually this is a. The basic things that some of the students cannot be. With your own success. That time. And if they're interested, I can also arrange some expert talk from Internet. Since faculties or expert on this field. Uh, to ensure that they are more connectivity. Or more tip to this knowledge. I would like to. Keep short. A real high problem. You using these methods? As they get can. Directly, Does this method really help to solve the real life problem? And that's how they can build their interest on this. Field of computational simulation. When they can connect this? Methods actually. Not in the paper. Pen and paper of this can actually. Of the real life problem and using these methods. And usually. Uh, solve such? Big problems. Without uh. Investing so much efforts in white lab. And before going to wait maps. They can design. This is the reaction they can put to the reactions. They can predict the result. Somehow little bit. They can go through the atomicity. Details of the system. Well, they can connect these things. After hands on experience or. During player. Solving small projects on this field. They can connect themselves and I think. This problem will be resolved.

So you’d address gaps by bringing in outside experts for talks when students struggle or aren’t meeting outcomes, but I was asking more about the assessment side—if your department head or the accreditation committee said your rubrics or tracking weren’t rigorous enough, what concrete steps would you take to improve consistency and transparency?

So you’d bring in outside experts to boost connectivity and knowledge, especially if students are struggling. But let’s take a different scenario: imagine a student files a formal complaint, saying your grading was biased, while at the same time your department head is pushing you to improve pass rates. How would you navigate that situation while maintaining academic standards?

So you'd look to bring in outside experts or guest faculty if students weren't grasping material, but I'm asking about a different kind of challenge. Imagine a student files a formal complaint that your grading is biased, while at the same time your department head is urging you to improve pass rates. How would you handle that situation?

Alright, so bringing in outside experts makes sense for boosting student exposure, but I want to shift gears to ethical decision-making. Imagine this: a colleague asks you to co-author a research paper, but you notice some of their data looks questionable or possibly manipulated. What steps would you actually take in that situation?

Alright, so you'd boost student understanding by involving external experts and focusing on real-world applications. Let's shift to something more about professional conduct. Imagine this: a colleague asks you to co-author a research paper, but when you review their data, you notice something seems off—maybe inconsistent or even possibly manipulated. How would you handle that situation?

Alright, so your focus would be on helping students connect methods to real-world problems, and you’d bring in experts if needed. But let’s shift gears: imagine a colleague approaches you to co-author a paper, and while reviewing their data, you notice some results seem inconsistent or possibly fabricated. What would you actually do in that situation?

You'd boost student understanding by involving external experts and focusing on real-world applications, but let's talk about professional conduct. Imagine this: a colleague approaches you to co-author a research paper, but you notice some of their data looks inconsistent or possibly manipulated. What would you actually do in that situation?

OK, this is. Tricky suggestions but if? I am confident that there are some. Results that are manipulated or inconsistent. I would suggest the micro authors. That, uh, maybe there are some. Misunderstanding or some overlook of the results I would. First, I would recommend them to repeat the experiment. I and regenerate this data.

Alright, so you'd first raise the issue gently, suggesting they might've missed something and asking them to repeat or regenerate the data. And if your colleague refused to revisit their results or insisted on publishing as-is, what would you do then?

OK, this is. Tricky suggestions but if? I am confident that there are some. Results that are manipulated or inconsistent. I would suggest the micro authors. That, uh, maybe there are some. Misunderstanding or some overlook of the results I would. First, I would recommend them to repeat the experiment. I and regenerate this data. And if this is. Significantly convinced. Meet and after the resignations and everything is OK. After regenerating or repeating this experimental data. If I found this is. Convincing to me, then I can. Proceed by uh. Computational theoretical collaborations for this result. Data is manipulated. I would not proceed with. Or else I can also repeat the data. To check the data are correct or not. If possible. Or. I asked the students. Who produces the data? I would directly consult with them.

OK, this is. Tricky suggestions but if? I am confident that there are some. Results that are manipulated or inconsistent. I would suggest the micro authors. That, uh, maybe there are some. Misunderstanding or some overlook of the results I would. First, I would recommend them to repeat the experiment. I and regenerate this data. And if this is. Significantly convinced. Meet and after the resignations and everything is OK. After regenerating or repeating this experimental data. If I found this is. Convincing to me, then I can. Proceed by uh. Computational theoretical collaborations for this result. Data is manipulated. I would not proceed with. Or else I can also repeat the data. To check the data are correct or not. If possible. Or. I asked the students. Who produces the data? I would directly consult with them. And if. And I would ask to repeat the experiment again. And to reproduce the data, if everything is OK, the computer, theoretical method, experimental methodologies and everything is clear. In the in the script then I can. For this collaboration.

Alright, you’ve described how you’d uphold research integrity even under departmental pressure. Now, given your background in computational biochemistry and machine learning, do you have any industry contacts or collaborations that could translate into internships or placement opportunities for students at VIT?

Alright, so you’d try to resolve the data issue collaboratively—asking for repeat experiments or consulting the student who produced the data, but you wouldn’t proceed if the results didn’t check out. Let’s pivot to postgraduate research supervision. At VIT, interdisciplinary work—like combining genetic counselling with food science—is a growing priority. How would you guide a PhD student who wants to integrate methods or insights from two such distinct fields?

OK. Yeah, it's really impressive, that bit. Actually encourage interactive therapy research. Like, uh, and. If some postage students are really interested in this kind of. Combination of two fields I. I would be happy to. Guide him or her. In this regarding.

OK. Yeah, it's really impressive, that bit. Actually encourage interactive therapy research. Like, uh, and. If some postage students are really interested in this kind of. Combination of two fields I. I would be happy to. Guide him or her. In this regarding. And although. I don't have that much expertise in the food papers industry of these things, but. In some cases if. I would suggest or help the students that. In the fate of this building on the. On my basis of the expert knowledge which I have on the predator. Medical chemistry and biochemistry. Would like to help.

OK. Yeah, it's really impressive, that bit. Actually encourage interactive therapy research. Like, uh, and. If some postage students are really interested in this kind of. Combination of two fields I. I would be happy to. Guide him or her. In this regarding. And although. I don't have that much expertise in the food papers industry of these things, but. In some cases if. I would suggest or help the students that. In the fate of this building on the. On my basis of the expert knowledge which I have on the predator. Medical chemistry and biochemistry. Would like to help. The student. Update.

Alright, you said you'd be happy to guide a student doing interdisciplinary work. Can you give a concrete example—maybe from your own experience or a collaboration you’ve witnessed—where methods from biochemistry and, say, food science were successfully integrated in a research project?

Alright, so you’d be open about your own expertise and focus on supporting the student with what you know, while encouraging interdisciplinary work. Can you give a concrete example—maybe from your own experience or a collaboration you’ve witnessed—where methods from computational biochemistry were successfully combined with food science or genetic counseling?

Right, so you’d support the student with your expertise and encourage them to draw from other disciplines or collaborators when needed. Earlier you mentioned working on machine learning for potential generation during your postdoc at IIT Bombay—have you established any industry links from that work, or can you see ways those connections could help students with internships or placements?

First, let me clear that. I did my second post off. And Tia for Mumbai not in high cloudy. And my one of my research work is. Exactly is. Just building. Potential energy surface. Is think machine learning based? Data and the data generated mainly from this. Path integral molecular dynamics and. And and this is a very. Going and very fascinating. Domain of computational chemistry, which is. Just going up. At this expertise I. Confident, uh. That it will help students with gain.

First, let me clear that. I did my second post off. And Tia for Mumbai not in high cloudy. And my one of my research work is. Exactly is. Just building. Potential energy surface. Is think machine learning based? Data and the data generated mainly from this. Path integral molecular dynamics and. And and this is a very. Going and very fascinating. Domain of computational chemistry, which is. Just going up. At this expertise I. Confident, uh. That it will help students with gain. To get up. Internship and opportunities. In. Premium institute in India as well as a products. And constant on that, this kind of expertise. Will help. Surely help.

So, you clarified that your postdoc was at TIFR Mumbai and not IIT Bombay, and your work focused on machine learning-based potential energy surfaces—especially using data from path integral molecular dynamics. In your current role, have you had a chance to bring any of this research into industry projects or consultancy work, or do you see a pathway for that happening?

That's friends to get up. A chance of internship as well as the position. PhD position.

That's friends to get up. A chance of internship as well as the position. PhD position. Uh, uh, a. Yeah, please continue.

Okay,

Right, so you see that expertise as a strong pathway for students aiming at both internships and PhD positions. Shifting gears, when you're evaluating students—say, designing exams or practicals—how do you make sure your assessments are fair and accurately reflect each student's understanding?

So you clarified your TIFR Mumbai postdoc and emphasized your work on machine learning-based PES, which you see as giving students a real edge for internships and future positions. When it comes to evaluating student performance—like designing exams or practicals—how do you ensure your assessment methods are fair and actually reflect what students have learned?

So it is a regular process for assessment that students are really learning the. The facts and the subjects are not. To ensure that. I according to me, I think I. I would like to. Conduct. Regularly give them assignments. With the real life connecting problems which can. Not be like, uh uh. On the knowledge based assignment, it should be application based. Sometimes. So they can. You will still uh. Purely whatever they learn during their classes, they can use this. Their knowledge to. Solve this kind of problems. And sometimes I would like to. Surprise. Take surprise. Paste during the class. And sometimes. Beyond the class Persons, I can. Consult with experience paragraph. They are checking their interest or not with their. Following the classes of notes regularly. Their attendance in the classes are regular or not. This other facts are actually. Important to. For a regular growth of students OK, do you know the guiding? A research. Of the such news. I would really prefer to give. Individual problems.

So it is a regular process for assessment that students are really learning the. The facts and the subjects are not. To ensure that. I according to me, I think I. I would like to. Conduct. Regularly give them assignments. With the real life connecting problems which can. Not be like, uh uh. On the knowledge based assignment, it should be application based. Sometimes. So they can. You will still uh. Purely whatever they learn during their classes, they can use this. Their knowledge to. Solve this kind of problems. And sometimes I would like to. Surprise. Take surprise. Paste during the class. And sometimes. Beyond the class Persons, I can. Consult with experience paragraph.

Alright, so you prefer application-based assignments and surprise checks to make sure students are really applying what they learn, not just memorizing facts. When you guide students on research projects—especially undergrads or master's students—how do you keep them motivated and on track, especially if they get stuck or lose interest?

OK, do you know the guiding? A research. Of the such news. I would really prefer to give. Individual problems. To each of them. As according to my research. I would also follow. Rather than. Uh, giving a problem? And distributing it among all these students. Are you usually? Slide 2 Give one problem to. Each students. Single problem for different problem for each actually.

OK, do you know the guiding? A research. Of the such news. I would really prefer to give. Individual problems. To each of them. As according to my research. I would also follow. Rather than. Uh, giving a problem? And distributing it among all these students. Are you usually? Slide 2 Give one problem to. Each students. Single problem for different problem for each actually. It helps. Friends to. How to complete or how to? Complete a research properly. Throughout from this. To the end. From the generating the result past. Designing the research.

So you'd rather assign each student their own individual research problem to make sure everyone is truly contributing and not just following along with stronger group members. Okay, when you're introducing a complex topic—like advanced simulation methods—how do you make sure your explanations are clear and structured for students who might be totally new to the concept?

OK, do you know the guiding? A research. Of the such news. I would really prefer to give. Individual problems. To each of them. As according to my research. I would also follow. Rather than. Uh, giving a problem? And distributing it among all these students. Are you usually? Slide 2 Give one problem to. Each students. Single problem for different problem for each actually. It helps. Friends to. How to complete or how to? Complete a research properly. Throughout from this. To the end. From the generating the result past. Designing the research. Going through the research. This is. These things give their. Proving their lives. Then they can. As individual researchers. It's helps them to. Build their career as a complete researcher.

OK, do you know the guiding? A research. Of the such news. I would really prefer to give. Individual problems. To each of them. As according to my research. I would also follow. Rather than. Uh, giving a problem? And distributing it among all these students. Are you usually? Slide 2 Give one problem to. Each students. Single problem for different problem for each actually. It helps. Friends to. How to complete or how to? Complete a research properly. Throughout from this. To the end. From the generating the result past. Designing the research. Going through the research. This is. These things give their. Proving their lives. Then they can. As individual researchers. It's helps them to. Build their career as a complete researcher. But it's also true that sometimes there are some problems which also leads. More than one instruments to complete this. Early or within a. Uh, finite time. So. Is I would uh. Rely all of the sprints. Actually without. I also directly participate with the experience. That's what I. I have also have that knowledge of whoever which experience is doing how much and. Whatever their contributions. As I am going to. Quickly participate on each of the projects.

OK, do you know the guiding? A research. Of the such news. I would really prefer to give. Individual problems. To each of them. As according to my research. I would also follow. Rather than. Uh, giving a problem? And distributing it among all these students. Are you usually? Slide 2 Give one problem to. Each students. Single problem for different problem for each actually. It helps. Friends to. How to complete or how to? Complete a research properly. Throughout from this. To the end. From the generating the result past. Designing the research. Going through the research. This is. These things give their. Proving their lives. Then they can. As individual researchers. It's helps them to. Build their career as a complete researcher. But it's also true that sometimes there are some problems which also leads. More than one instruments to complete this. Early or within a. Uh, finite time. So. Is I would uh. Rely all of the sprints. Actually without. I also directly participate with the experience. That's what I. I have also have that knowledge of whoever which experience is doing how much and. Whatever their contributions. As I am going to. Quickly participate on each of the projects. So that there is no questions for this doubting the. Or believing under the stronger. Students so that. Because I am going to participate each of the projects whatever going on in my. A group. So I will be. Uh, I would have that all the information set out whatever the. Portraits of these projects and whoever tends to help.

Okay, so rather than group projects, you prefer assigning each student their own distinct research problem to make sure everyone is engaged and contributing their own work. Shifting focus—clear communication and structuring your teaching is crucial, especially with complex topics like computational biochemistry. How do you break down a difficult concept in class when you notice students just aren’t getting it?

So you make sure every student gets their own problem, which helps you assess their individual growth across the whole research process. When you're introducing a new concept in class—especially something complex—how do you structure your explanation so that students with different backgrounds can all follow along?

So you give each student their own research problem so you can see their full process—from problem design to final results—and make sure they grow as independent researchers. Now, when you're introducing a new concept in class—especially something complex—how do you structure your explanation to make sure students with very different backgrounds can follow and actually engage?

Right, so you tailor assignments to real applications and keep a close eye on engagement to make sure your evaluation is fair. Now, clear communication and structure are crucial for teaching—can you walk me through how you’d introduce a complex topic, like quantum effects in proton transport, so that students without a strong physics or math background could still follow along?

So you keep close involvement with each project so you always know who’s really contributing—not just relying on group dynamics. Now, clear communication and structure are critical for teaching—can you walk me through how you’d introduce a challenging new topic in class to make sure students of all backgrounds can follow along?

It's yeah, it's really. Sometimes it is difficult, but I think. If you have a. Clear concept then it is not a very. Challenging job for you? For it example.

It's yeah, it's really. Sometimes it is difficult, but I think. If you have a. Clear concept then it is not a very. Challenging job for you? For it example. In catastrophic physics, quantum mechanics is a very, very. Fundamental topics and. Most of the times. During my. Student life or. Telling me sometimes my. During my coursework. I realized that. Even master today. Earlier. They could not connect. The mathematical derivation. And all this. Things to the real life problem, why they are solving things and why this is. And for this kind of thing. I think for the introducing this. OK, what's the? Introducing. And. Events regarding. Associated with this kind of. Problem is actually encourage the students to focus. Yeah. Is there interest on that topics? So did. This kind of introductions. Help like. For fundamentals, why?

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

It's yeah, it's really. Sometimes it is difficult, but I think. If you have a. Clear concept then it is not a very. Challenging job for you? For it example. In catastrophic physics, quantum mechanics is a very, very. Fundamental topics and. Most of the times. During my. Student life or. Telling me sometimes my. During my coursework. I realized that. Even master today. Earlier. They could not connect. The mathematical derivation. And all this. Things to the real life problem, why they are solving things and why this is. And for this kind of thing. I think for the introducing this. OK, what's the? Introducing. And. Events regarding. Associated with this kind of. Problem is actually encourage the students to focus. Yeah. Is there interest on that topics? So did. This kind of introductions. Help like. For fundamentals, why? White people hate this quantum that. Why don't you want to ship from classical? Like there are some physical phenomena like black body radiation. And this kind of things, there are so many. Other I compels also be important. Not explained by the so-called classical. Uh, Netflix. That's why this quantum mechanics arrived. And sometimes. Kochler quotations from this. Uh, some popular scientists, some still can popular. Quotations like nobody can understand quantum mechanics and. Which was supported by the chat in Mansour. Considered as one of The Pioneers of quantum mechanics. I think. This kind of involvement and sometimes some. Discussions out of the on the syllabus or. Make students more. In pain towards learning more inclines towards your postmodern clients.

So you focus on building clear conceptual foundations and use relatable motivations—like why quantum mechanics matters in real-world scenarios—to get students engaged from the start. Alright, we're wrapping up. Is there anything you'd like to ask about the role or the team before we finish?

So you focus on the motivation behind the concept, connect it to real-world phenomena like black body radiation, and use stories or famous quotes to make the topic relatable—especially with something abstract like quantum mechanics. Alright, we're wrapping up. Is there anything you'd like to ask about the role or the team before we finish?

Is that in your position? Is only for research, as whenever I receive the mail it was. The written that this is the assistant. Assistant professor position. In the research, so is that only a research position or also teaching will be assigned? Or it is a regular assistant professor position. Can you clarify it?