Good day, Sandipan Chattaraj. I'm Arjun. I've had a look through your background and your professional record. I'm interested in hearing more about your work and how you see yourself fitting in here with our faculty. Ready to start?

Hi Arjun, good day. So in one sentence, I am a computational biologist working in the interface at the interface of bioengineering, biophysics and biomaterials. So I did my PhD from in in in polymer science at IIT Bombay. Then I went on to do my first postdoc at IIT Kanpur in the field of molecular dynamics simulations of polymers of the polymers PEAK and PEC.

Particle dynamics simulations of cells, tissues, and extracellular metrics.

Finally, I am uh. Currently I'm doing uh, uh, another interesting uh. I'm working with another interesting branch of materials called colloids. I'm doing distributive particle dynamics simulations of colloids.

So in I have a very into this, as you can see, I have a very interdisciplinary background, but it's rooted in bioengineering and bioscience and computational mechanobiology, which are all, which can all provide a lot of value to a department like bioengineering and biotechnology at VIT.

Thank you, Professor Chattaraj, for sharing that. Your multidisciplinary background spanning bioengineering, bioscience, and computational mechanobiology indeed aligns well with the core of an interdisciplinary department like ours. Let's focus now on verifying your qualifications and key areas of expertise. To start with your expertise, can you explain how your experience in particle dynamics simulations, especially in the context of colloids or extracellular matrices, contributes to advancements in organ-on-chip technologies or regenerative medicine?

Yeah, that's an excellent question. So in our first publication in EPL bioengineering where we introduced the model SEM square, we talked about interesting bioengineering applications such as cell proliferation in as an organoid or inside a microfluidic chamber inside a microfluidic channel. So for example, we have developed computational self proliferation simulations where the cells. Grow and divide.

In inside microfluidic channel, so there's a cylindrical confinement and how the mechanics of the cells and tissues develop. How the cell, cell junction and boundary boundaries develop in a situation where there is a cylindrical confinement. Sorry, as opposed to self proliferation in an unconstrained environment which simulate more and organized like environment.

Interesting, Professor Chattaraj. It's impressive that you've delved into cell proliferation under varying constraints, specifically simulating scenarios like microfluidic channels versus more organoid-like environments. This kind of mechanistic insight could be highly useful in the optimization of organ-on-chip technology, particularly for studying how physical boundary conditions influence cellular behavior. As a follow-up, could you elaborate on how these computational insights have or can be translated into real-world experimental validations or therapeutic applications, especially in relation to diagnostics or personalized medicine?

Yeah, sure. There is a very interesting question.

In our latest work, Biopoint, which is about to be published in Plus Computational Biology, we have talked about.

So for example.

The nuclear mechanics so the how stiff, how the stiffness of the nucleus affects cell migration. So for example, when we allow when we perform self migration simulations where a cell has to pass through a.

Narrow constricted, narrow constriction. How if if this nucleus is stiff then it doesn't pass it? It is not able to.

It doesn't allow the cell to migrate, whereas if the nucleus is softer it it deforms so that the cell migrates through. The narrow construction with this kind of scenario is very important in cancer cells where the nucleus is known to be stiffer than other types of cells. So cell migration in in cells where the nucleus is stiffer in cancerous cells.

And is an interesting direction of future work of our current paper by Biopoint, which is about to be published.

Thank you for that detailed explanation, Professor Chattaraj. Understanding nuclear mechanics and its implications for cellular migration clearly has significant potential in cancer research and diagnostics, especially for studying metastasis. Your computational approach seems to bridge a crucial gap in preclinical modeling and experimental validation. Let us shift our focus slightly. One responsibility of this role involves teaching both theory and laboratory courses. Can you describe how you approach structuring a course curriculum on computational modeling in bioengineering to ensure it is accessible yet rigorous for students across different levels of background knowledge? How would you adapt your teaching methods for undergraduates versus graduate students?

Thank you for asking this excellent question about teaching. So for so there are two aspects of this question. First is a theory course and then there's a laboratory course. For the theory course, I would try to 1st impart fundamental concepts to students that would be very basic and that would be accessible to all students of all background. Following that I would build I would build on that by. By giving them small exercises small I would get tutorial problems.

Where students who are not so from different backgrounds feel inclusive is for inclusivity. So and and I will give real world examples, biological examples which would connect with the students from biological from life science background.

So that way I would structure a course, the a teaching course that is, that is that will be interesting for students from all backgrounds. And then the according to the later part of the question where we are talking about undergraduate students versus post graduate students for the UG students, I would design courses which are more fundamental and which have. And I will give them modular small programs, so I will I I believe in.

Modular research. So a small sub problem of our research or some other or or the research of some other group who are who have published recently. I I would give a small part of the part of the big problem that they have tried to solve to the students, to the undergraduate students and help them to generate end interest for post graduate students. I would I would give a problem in more detail. Maybe a a bigger problem than the than than the extremely small problem.

And help them to analyze it and come up with solutions which might not allow, which might or might not align to the solution that has been provided in the published paper or by micro.

Thank you for detailing your teaching approach, Professor Chattaraj. Your emphasis on starting with foundational concepts, providing relatable examples for diverse audiences, and tailoring problems to the complexity levels of undergraduate and graduate students is certainly commendable. Your strategy of using real-world research problems also aligns well with fostering both curiosity and critical thinking, which are essential for learners in bioengineering. Let me now turn our discussion to your experience with student evaluation and exam duties. Could you provide insights into how you structure assessments in your courses to effectively measure both theoretical understanding and practical application skills?

Absolutely. So this is something which has which I've been thinking about. So first my my way of approach of evaluating students will be threefold. First would be classroom, classroom participation. So the I would try to try to have my courses as interactive as possible and I would see the level of excitement and participation of the students. And that would that would constitute a part of the evaluation. The second part would be the. Would be exams like mid semester or end semester evaluations of the training of of of the concepts that they are that have been taught to them. I will design interesting problems which would be more.

More interesting because they're related to real research problems tied to published research papers.

And the third part would be projects. So in the end semester, towards the end of the semester, I would divide the class into smaller groups of students for and I would assign them and I would assign a project to each of these groups. So the students can have a feel of solving research, tackling a research problem to understand a research problem and analyze a research problem and take steps towards solving a research problem. And they will be evaluated on their analytical skills and problem solving skills.

In the particular project, so classroom participation.

Theory exams and projects and and research projects is is going to be my my my my strategy.

Thank you, Professor Chattaraj. Your comprehensive approach to student evaluation—combining active classroom participation, theoretical assessments grounded in real-world applications, and hands-on project experience—provides a well-rounded measurement of student abilities. It is clear that you emphasize both engagement and critical analysis, which are critical for fostering deep learning. Moving forward, guiding student projects and mentoring research is another significant part of this role. Could you share examples of how you've guided students through research or projects in the past, or how you would mentor students to ensure they achieve their full potential in terms of both academic knowledge and practical research?

Absolutely, thank you for asking me this. So I had the opportunity to train masters students while I was doing my PhD and also a PhD students while I was doing my post docs. So what I have followed with the approach that I have followed is first in first giving them the the essential material, the reading material which would help them to understand the concept. So the the state of art. State-of-the-art research papers.

Seminole Research works textbooks that are related to the related to the subject and which would help them to build fundamental concepts in the subject. Followed by that I would help them to find. I would encourage them to find the problem that is going to be pertinent, that is going to impact the world that is going, that is going, that is going to be interesting. And out of that I would evaluate the strength and weakness of each of the topics.

Research topics that they propose and we can together we're going to choose one of those and work on one of those. And as we now that we after devising the research problem, we would we would design the experiments of simulations that we are going to perform. And once we have done that, we are going to do experiments and simulations, collect data and and then we are going to analyse the data and see whether. They whether they align with the literature, whether with the literature results which are already.

In there and what is and what new results we have with new analysis we can perform, what new deductions we can do from there so that we can bring novelty to our research work. And once we have the novelty, I would mentor them to turn the to translate the knowledge that we have developed into a beautiful story that can be shared with the outside world through interesting publications and impactful journals.

Thank you, Professor Chattaraj. Your mentorship process, focusing on guiding students from foundational learning to identifying impactful research problems, conducting experiments or simulations, analyzing data, and culminating in high-quality publications, demonstrates a thoughtful and comprehensive approach. Such a method not only builds scientific rigor but also encourages creativity and independent thinking among students. Now let us discuss your research publications and their relevance to this role. Could you highlight a specific publication from your portfolio that has made a meaningful impact in your field and explain how its findings could contribute to advancing biotechnology and bioengineering education or research?

Dori, thank you for asking me this question. The RES, my research work which is most relevant to AP to the bioengineering and biotechnology department is Semsquare subcellular element modeling and mechanics which we have published in APL Bioengineering. So there goes the relevance to bioengineering. So we have and and our group is probably only one of the groups which have which are working on this LAMPS based implementation of subcellular element modeling which has.

Of considerable advantages over other similar computational models in in solving problems in bioengineering, in mechanobiology, which would then translate into solving problems in disease modeling and Cancer Research and so on.

So, so we we developed this model which where we are assuming a cell to be consisting of a of a group of particles and thus we can access the mechanics that is there not only outside the cell, not only the tissues but also inside the cell. So we have a complete spatial resolution of the inside of the cell and.

With this, armed with this model, we have dealt with problems such as cell migration.

Self proliferation, we have added advanced added value to previous publications where we have added biasing forces to the nucleus. We have dealt with nuclear positioning, we have dealt with cell proliferation examples, we have dealt with cell cell boundaries and we have performed cell proliferation in organoid like environments and inside a microfluidic channel like environment.

Thank you for sharing, Professor Chattaraj. Your work on the SEMsquare model and its LAMMPS-based implementation clearly demonstrates a significant advancement in computational bioengineering. The ability to resolve both extracellular and intracellular mechanics at such a granular level is indeed a considerable breakthrough for studying complex phenomena like cell migration, nuclear positioning, and cell proliferation in various environments. The applications to disease modeling and cancer research are particularly compelling, and your work clearly offers substantial potential for future exploration in biotechnology-related fields. Before we conclude this section, I would like to briefly touch on your experience with industry projects or consultancy. Could you share any experience you may have had in this regard, and if not, how you envision leveraging industry collaborations to enrich your teaching and research agenda?

Well I have like I I have industrial experience in my background. So I have before starting my PhD I have worked in the industry. Do I completely different industry but I have worked in the industry for 2 1/2 years and I know how the industry works. But as far as industrial project is concerned I have not up till now. But I have a plan. I have worked in in a in a lab where the Pi was. Had considerable industrial collaboration. He started an ERC project.

And then he translated many of the ideas to the industry. So I have plans to to to get in touch with pharmaceutical industries and pitch potential interesting competition biology results, interesting computational biology models that we develop to show and showcase them. Showcase to them how it can add value to the to the experiments that they perform. How we can inform their experimentalists to perform to avoid.

Trial and error experiments to do more targeted experiments, more effective experiments so that they can reach.

Conclusions faster and thus develop drugs faster prevent diseases faster. So this is something I'm going to speak with the pharmaceutical companies in the area and pitch by computational results by computational model to them and and discuss possible collaborations with the industry.

Thank you, Professor Chattaraj, for elaborating on your background and vision. It is commendable that you already have insights into industrial operations and a strategy for leveraging computational biology to engage with pharmaceutical companies. Your emphasis on reducing trial-and-error experiments to accelerate drug development highlights the practical and transformative potential of your work. That effectively concludes the skills and expertise validation. Thank you for your detailed explanations and thoughtful insights. Let's move forward.

Professor Chattaraj, let's delve into your research. From your resume, I see that you completed your PhD in Polymer Science, Nanoscience, & Technology at IIT Bombay and have published multiple papers on the subject. Could you highlight one of your research works that you believe is most impactful to your field?

Yeah. So during my PhD we have worked on nano annotation of polymers. And I think the publication that is most impactful is the first one that we published in Polymer where we are saying where we deal with activation volume and activation number like how many chains move cooperatively to result in yield in a densely cross-linked thermoset is what we were looking at. So we try to. Connect the mechanical observations in mechanical.

Experiments to the molecular level behavior of the polymer in this in this paper and we try to and we come up with a correlation between 2 volumes. 1 is the activation volume which is measured from experiments where micro pillars of experiments of micro pillars of a polymer are compressed and the effective chain volume which is which comes from the molecular structure. So how so we provided A molecular basis for yield in densely crossing thermosets.

This is this is was a very impactful work and we I totally enjoyed working on it.

Fascinating work, Professor Chattaraj. Bridging mechanical observations with molecular-level behavior is indeed a significant contribution. To better understand how this translates into teaching, how would you go about explaining the concept of activation volume and its significance to undergraduate students with little prior knowledge of polymer science?

OK. So yes, so to undergraduate students, I would I would explain activation volume in the following manner. So if so, if we can, polymers are ubiquitous, they're everywhere. So if we can find a cylindrical block of polymer somewhere or if we can design a small micro pillar of a polymer and then we compress it.

And compute the stress versus strain which is known to all the engineering students. We can find out the stress versus strain curves at different strain rates. And the maximum of the stress strain curve is the yield stress. And if it now if we plot that yield stress versus strain ratio, we have stress strain curves at different strain rates. We compute this yield stress at each strain rate. And if we plot yield stress versus log of strain rate on a log log.

Now from this slope of this curve we can compute the activation volume where log of so the. So the yield stress is equal to a constant multiplied by the log of strain rate and in this constant is. This constant constitutes A parameter called the activation volume. So this is a. This is a parameter that is computed from experiments and is called activation volume and this correlates yield stress with strain rate in.

Versus Love Australia, we see a linear variation of the yield stress versus log of strain rate which conforms to Irons theory.

Mechanical experiments on polymers and other materials.

Thank you, Professor Chattaraj. Your explanation demonstrates a thoughtful approach in breaking down the concept for students with relatable examples and clear steps. A follow-up question: how do you encourage students to connect theoretical concepts like this with real-world applications of polymers in engineering or technology?

So Paul, for example, polymers are like I said, polymers are everywhere, they're ubiquitous. And a very pertinent problem is to find out is the degradability of polymers. So finding biodegradable polymers which don't pollute the environment, which don't constitute the problem which we now call the white pollution, white pollution, which is plastic pollution. So for that we need to understand how the.

Particular level behavior of the polymer is tied to its mechanical property. Therefore, if we understand that we can develop polymers, new polymers which are biodegradable but has significant mechanical properties like the ones that are in use. So and also we can search for new. We can design new biodegradable polymers which are easily degraded and also have significant mechanical properties so that we can use them in our daily lives.

Understood, Professor Chattaraj. Your approach to linking polymer mechanics to sustainability and environmental impact provides both relevance and inspiration for students. Thank you for sharing that.

Professor, for this section, I need to assess your ability to drive institutional rankings through impactful research and revenue generation. Could you present a 3-year research roadmap that aligns with the core areas of Biotechnology/Bioengineering, such as regenerative medicine, microfluidics, or therapeutics and diagnostics?

Yes, thank you. Since there is not not a lot of time, I would say in short that for three years I would try to generate generate a road map where we are first performing simulations on of microfluidic channels of proliferation, migration and microfluidic channels. And then when we have when we understand how how the cells make cell mechanics works in various. Various channels we are going to tie up with experimentalists.

And then we are going to collaborate with them to to create a concrete understanding that would that would impact the field.

Impact the field of bioengineering and biotechnology. So that way in the first year I would we would try to develop an understanding. In the second year we will try to collaborate with experimentalists and the third year we would try to try to develop a cumulative understanding on the subject and then tie it to. To to real-world problems and then sharing.

With the rest of the world to see whether it is how the others in the field are receiving it and how we can build on it to solve real world problems by providing.

By providing meaningful solutions. By providing meaningful analysis. Analysis by meaningful experiment, simulations and analysis.

Thank you for outlining that plan, Professor. Scaling this roadmap further, how do you envision mentoring junior students in your lab to ensure a consistent pipeline of robust publications during this period?

I plan to mentor junior students in my lab by by introducing to the them to 1st the concepts of the of the field, the the techniques to I would encourage them to be a master of the techniques that are needed to solve the problems then, and then finally to interpret their problems, to analyze the data to to form a meaningful story, to form a meaningful. Theory Hyper.

The hypothesis which we can then translate into a theory and then we can share it with the rest of the world. Apart from that, a very important part of mentoring a student I feel is to is communication. So I would send them to various conferences, encourage them to present posters, deliver oral presentations in conferences and then finally, most importantly. Writing papers so writing papers reports.

And finally their PhD thesis. So I would focus on both, both technical expertise, methodological expertise, expertise to analyze the results meaningfully and and and also communication in science such as presentations and writing papers, publications.

That sounds comprehensive, Professor. Let me take this a step further. How do you plan to leverage international collaborations to enhance citation metrics and expand the global impact of your research?

Yes, I have. There's a very important and pertinent question. Since I have spent quite some time in in Europe about from, about from the research that I did in India. I have done performed research in, in Italy and now I'm performing research in Greece. So I have developed connections with various, with various researchers in the field. So that would help me to connect with the rest of the world.

I have also contacts in in the US so I would.

Try to to foster international collaboration so that we can do collaborative research, collaborative, impactful, meaningful research work.

Apart from that, I would try, I, I would try to that would automatically improve the quality of our, of our research and that, and that would increase, improve the citation metrics of, of, of our group, of me of our group and VIT most importantly. And apart from that, I have this experience of working in a lab which is funded, which is funded by ERC starting grand winner. So I have some experience of writing grants. I have written the Ramanujan.

Fellowship Ramalinga Swami Fellowship grants in India. I've written grants, the Mercury Fellowship grant in Europe, and I have worked in tandem with an ERC starting grant winner. So that expertise, that experience will help me to to write effective grants effectively and raise money for my research and for the research of my collaborators at VIT.

Thank you for sharing this vision, Professor. Your emphasis on leveraging international connections and grant-writing experience is clearly aligned with institutional goals for research growth and global impact. That will conclude this section. Let's move to the next.

Professor, let's discuss your teaching strategies. How would you implement an active learning model, such as a Flipped Classroom, for a large-enrollment course in biotechnology or bioengineering while avoiding traditional slide-based presentations? Please provide detail.

So yeah, flipped classroom is of course is one of the one of the very interesting concepts that are that are practiced.