Good day, Aurosikha Das, Ph.D.. 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?

Please start by introducing your professional journey in academia.

Good morning, I'm Aurshika Das, currently working as an assistant professor at SRM University I. Prior to this, I also served as an adult faculty at IT Andhra Pradesh. My academic journey in biotechnology began with UH Btech from VIT Vellore, followed by your Masters from IID Rootkey and a PhD from IID Bhubaneswar.

Address complex biological problems. My research interest lies at the interface of computational biology and experimental biology.

Particularly in leveraging data-driven methods to tackle challenges in health and biotechnology.

Beyond research, my strong passion lies in mentoring and fostering scientific curiosity. I'm deeply, completely committed to teaching supervision and creating an engaging learning environment that reaches theory with real-world biological applications. Thank you.

Thank you for sharing your research interests and your passion for teaching and mentorship. Let’s delve into our evaluation process now. First, can you elaborate on your expertise in bioinformatics, specifically within the scope of medical microbiology? How do you apply bioinformatics techniques to solve problems in this area?

So it's basically using UH sequencing, which is whole genome sequencing or imaginary sequencing. But my expertise is uh, mostly proteomics. And so I will see how proteomics will be helping in microbiology because my interest rise in tackling MA AMR that is antimicrobial resistance using non amino acids.

And, uh, producing vaccines, which are actually right now important in.

Tackling the EMR issue.

Yeah.

How do you integrate your expertise in proteomics into the teaching of bioinformatics theory and laboratory courses? Can you provide an example of how you would make these interdisciplinary connections tangible for students?

Yeah. So it's basically I'll be using molecular dynamics simulation data. So we'll be given a lot of datasets which will help in.

Gaining informations about the conformational changes in the protein itself and how these works. So for this we would be requiring ML also to understand and procure datasets and using machine learning to decode.

How these amino assets are particular protein helps in the AMR process.

Thank you.

Can you share any experience you have in evaluating students, such as designing exams, assessing practical work, or providing constructive feedback to support their learning and growth?

Yeah, so basically we generally conduct, uh, internal exams for, uh, mentoring students. We also, I also do quizzes, like short quizzes after every week so that I get to know if my students are, you know, uh, taking the courses, uh.

And learning things or not. And then for practicals generally I do all the practicals which are experimental as well as in silico methods so that they those are interdisciplinary nature and.

You know people can learn, rather than you know it's only experimental.

Thank you.

Yeah. So that is one of my weaknesses. I told you, I generally have a weakness of, you know, delegating the not delegating works. So right now I'm learning on those things and trying to.

In guiding student projects and research, how do you strike a balance between giving students autonomy and ensuring the quality and direction of their work?

For give authority to the students so that they do the work and.

With every, all the walks they give me, uh, I ask them if the if it is validated by other methods so that you know, I'm also satisfied with the work and I can give them the authority that they have done the work and the work can be published.

Thank you

Hello.

Yes, Professor. Let us discuss your communication and teaching approach. Can you explain how you structure and deliver complex bioinformatics concepts to students from diverse academic backgrounds, ensuring clarity and engagement?

So I generally if there's a complex subject or complex topic, I generally try to.

Give real-world examples or you know, something they can relate to what they have been doing since their childhood. Try to give examples which are not the not related to the subject, but something they'll understand in their own languages. Like simple example. If I have to make make them understand what is homology, I'll try to say that.

There's a box and you have to.

Fit something something that is unknown. You you have to fit something in that box and the box the the object will try to take the shape of the.

Uh, square of the box. So that is how homology, uh, modeling works for proteins. So I'll try to make them understand with the object oriented things, something they'll understand.

That’s a clear and relatable approach. Demonstrating abstract concepts with tangible analogies can indeed enhance understanding. Thank you for sharing.

Hello.

Yes, Professor. Can you describe your experience with publishing research and how your publications have contributed to the field of bioinformatics or related areas?

So currently I have 11 publications all in good reputed journals. So my PhD work gave me around six publications which were generally it was related to AC 5A protein which is an anaphylotoxins which is a pro inflammatory protein and that was the main protein which was involved in the recent COVID-19.

Model the receptors of those proteins because during that time we do not know the structures of the proteins. Using computational techniques and then using experimental techniques, I tried to try to give how this protein interacted with the receptors and tried to design and repurpose drug molecules which will help in combating the C5, A protein which is actually which is a dangerous protein because that protein. Basically, is a bad protein which will.

Pandemic and my strategies were to.

Enhance your immune response. So my work gave.

Give how? What were the approaches to you know?

Approaches to.

That's impressive

So 2.

Please continue, Professor. What were your approaches to addressing this?

So my approaches was to develop the interactions of the protein with the receptors and to know what are the important amino acids which were involved in the interaction process and developing drug molecules. And also screening the existing drug molecules to combat the interactions between the receptor and the CFA so that we do not have a immune response which is actually pro inflammatory in nature.

So my strategy was to elevate the immune response in in any disease conditions.

So it's actually a complementary protein, complement protein. So which is the first line of defense in our immune system. So my work was on the first line of defense on my on the immune system.

And one of my work was also published in the French newspaper during because the work was related to COVID-19, so it was highlighted in one of the French news during 2022, I guess.

That's quite an accomplishment, Professor. It highlights both the significance and impact of your research.

I also modeled another receptor of the protein because the proteins structural.

Uh, structural knowledge was not known about the receptors, so that was also one of the contribution of ME towards the scientific community.

That’s commendable, Professor. Contributing novel structural insights for receptors is indeed a significant advancement for the field, especially in tackling critical issues like immune response in diseases. Thank you for detailing your impactful work.

Another I also to review people which is basically which which I wrote in my post doctoral postdoctoral research, research time. So this was basically an interface of biology and physics, which was mainly.

To focus on the physics of the 4th generations by myosins and dynein and kinesins. So that wallpaper was also for the the physics audience. So I contributed maximum and I was also a co-author in that paper and that paper was published in raw Divista New del Clemento and which has an impact factor of around 8:00.

So this so this is basically telling that I can also do interdisciplinary work which is interface of biology and physics and my PhD work represents interface with biology and computer science.

Thank.

Thank you, Professor. Let's move on to an essential requirement. Do you have experience working on industry projects or consultancy initiatives? If so, could you share an example?

I no I do not have any expertise or consultancy project in industry projects as well.

But I did work on my professors grant which was with COVID-19, during COVID-19 which was with the IIT Delhi.

And that was the paper that got published in that French newspaper. So I do not have any expertise in industrial projects or consultancy projects.

Delete.

Understood, Professor. Thank you for clarifying. Let us proceed.

Hello.

Yes, Professor. One final key question—your Ph.D. is a fundamental qualification for this role. Could you briefly outline your Ph.D. research focus and its implications in the field of bioinformatics?

So my degree must be a fundamental thing, but my specialization was computational biology as well as analytical techniques. So my PhD focused on C5 protein. C5 a protein is a pro inflammatory.

Protein which is involved in the complement complement cycle. So complement cycle is the first kind of defense in the immune system. So that protein is a bad protein which we can say and it generally when it interacts with the with its receptors which is a GPCR, it generally gives bad responses that is pro inflammatory responses that is it alleviates your inflammatory responses. So my.

You're focused on designing the receptors of the, the, the C fiber protein because it has two receptors that is 1 is C5 AR 1 and C5AR2SO1C5A interacts with C5 AR one. We generally have a pro inflammatory response, but when C5Y interacts with C5 AR 2, we generally have both kind of. We have both kind of responses and that is generally disease, disease oriented.

So that is context organized which can be either pro intermittently or anti-inflammatory meet nature.

So my work focused on designing both the receptors, that is modeling both the receptors using computational techniques and then and then doing the docking of the C5 way with the receptors itself, which is the GPCR which is generally in the transmembrane area and then.

After docking of the C5 way with the C5 AR 1 and as well as C5 AR 2, we went for the molecular dynamics simulation to see what are the conformational changes of the C5 wave when it interacts with both the receptors.

And how this interaction affects in the intracellular side of the receptors so that it will bind to two different entities. When it is, pointometry generally binds to the G protein because it's a GPCR. And when it is anti-inflammatory, it generally binds to beta adistain, which is.

Anti-inflammatory region.

So my my project, the computational part was the modeling, talking as well as simulation part. And then going for the going forward, I did experimental analysis we're using by analytical techniques which involved UV spectroscopy, FTIR, HPLC.

Mass spectroscopy and as well as fluorescence spectroscopy and CD spectroscopy to see how the C5, a protein interacted with the extracellular part of the receptors. So because I designed the part of the receptors to see how it interacts with the C5 or protein and what are the important residues and then.

Designing and seeing what are the possible existing drugs, how they interact with the C5.

And how it affects its interaction with the receptors and then doing the experiments to see how the.

How there are changes in the C5 wave protein which will help me in decoding what is happening in the intracellular part of the?

Receptors to see how the changes are. So my work, my degree might be a basic degree, but my work was a specialization in computational biology as well as biomanitical techniques which involved using computational techniques like molecular dynamics, simulation, docking and modeling.

And then bioenergy techniques using if you set spectroscopy or process spectroscopy, CD spectroscopy, FTIRHPLC and mass spec.

Thank you.

Thank you, Professor, for outlining your Ph.D. research in such detail. Your work clearly demonstrates a strong specialization in computational and experimental biology, with impactful applications in immune system research. Let’s move forward.

Hello.

Yes, Professor. One final area to address—what is your experience with guiding interdisciplinary research or collaborating across diverse fields in academia?

Sorry to interrupt, we're down to the last 5 minutes.

Yeah, so come. So since my area is computational biology, which it itself is a interdisciplinary subject that I'll be dealing with. So my work will be basically tackling biological problems using computational tools. My research interest lies in tackling this AMR that is antimicrobial resistance, and antimicrobial resistance has been a problem.

For decades right now, and we do not have drug molecules which can.

Address this problem. So my area of my area would be addressing this issue using non potent amino acids and making vaccines so that we have a structural stability of the proteins and making this as a stable vaccine candidates so that vaccines may might be or may not be. Maybe a solution to the problem using this techniques like so. It will be use of experimentals so.

Address

Umm, which will be using, uh, this molecular dynamic simulation data as sequencing datas and everything. So which will require the expertise of computational people also. So for modeling and everything and then tackling this issue using this both the areas that is combined actually as well as computational.

Will get details from experiment as well as computational data.

So that is how I would try to integrate both.

And this.

Please continue, Professor.

And then since my expertise is computational biology, I would also require a proper biology person which will help basically a genetic engineering person which will basically help me in. Since our genetic code only codes for 64 amino acid 6020 amino acids, my area of focus will be this non volatile. So how these?

Non core amino acids can be synthesized in the body and you know, incorporated into the antigens. So that can be a good vaccine candidate. So it will be basically a bioinformatics person, genetic engineering person, and a computational person.

Will help us in the machine learning part and everything.

So it's basically a amalgamation of biology, genetic engineering as well as computational person who will be doing the work.

Thank you, Professor. Your interdisciplinary approach integrating bioinformatics, genetic engineering, and computational methods for addressing challenges like antimicrobial resistance is well-articulated and impactful. Let’s conclude the skill verification process here.

Professor, could you share which introductory course in bioinformatics you find most engaging to teach and why?

So first would be, uh, introductory course would be the protein, uh, homology modeling in proteins and everything. So this would be, uh, basic, uh, as basic course because that will help people understand how proteins work and how they are modeled and what are the bioinformatics tools we use to generally.

People should take to understand protein structure and because that is every diseases and everything that happens to us, the main workers of the SALSA proteins, so I would prefer the basic.

Protein sequencing and protein homology modeling as the basic introductory course which should be given to.

Our students.

So first, my basic idea would be teaching them what are my assets, what are the level of structures of my, the proteins that we have, the primary, secondary, tertiary and the quaternary. And then maybe I go to this homology modeling, so the modeling processes that we have the experimental as well as the computation.

Thank you, Professor Das. Let’s delve deeper into how you bridge your research in protein studies with teaching. You spoke about introducing students to protein sequencing and homology modeling as foundational topics. Could you explain how you would structure an introductory course around these topics to make them accessible and relevant to undergraduates with little prior experience in bioinformatics?

And then maybe we have this admin issue modeling, uh, this.

Another type of model I'm not able to remember, so how these will be?

Homology, modeling and then.

How these are done using them. And then after that we'll have all this, uh, alignment techniques, that is, uh, little man, uh, methods and the Waterman methods. How these metrics help in the homology modeling and what are the scores that we get After that, we'll be dealing with BLAST, which for which I'll be giving.

Experimental we'll also have a lab which will help on hands on experience with these techniques as well. And then maybe I'll go to the.

How this?

We go for the simulation processes, how there's conformational changes and everything going on when you have a protein, and then maybe I'll go for this docking process.

No, prior to simulation, I'll go for docking to show students how the drug molecules interact with the proteins. So in that I'll be teaching allosteric and autostaric finding sites and then how this enzymes the drug molecules interacts with the proteins and then I'll be teaching them the simulation methods to how the conformational changes are done. So.

It will be a basically theory as well as a practical course so that you know.

For the students to understand how the what are the things. So theory will give them a basic knowledge of all the subjects and practical will tell them how it is done.

There's also hands-on experience of.

Thank you.

So what I'll do is I'll maybe divide the class into groups and give them a little mini project so that you know, and try to so many projects. I'll try to assess them every month wise so that I get to know how they're doing the projects if I give them short projects and how they what are the approaches they are trying to incorporate the from the teachings that I'm doing and what are the results?

You're welcome, Professor Das. Based on your explanation, it seems your approach integrates theory with practical application effectively, providing students both the foundational knowledge and hands-on experience. Let me ask—how would you assess student understanding and ensure they are applying these complex concepts effectively in both theoretical and practical settings?

So many.

Thank you, Professor Das. Using group-based mini-projects for assessment sounds like a practical and collaborative approach. How would you ensure that students from various academic backgrounds and skill levels can equally contribute and benefit from these projects?

So I would tell you basically.

I can ask students to do similar. If there are different background students, I can pinpoint and tell them that you do this part, you do that part, and that way I can.

It seems like you plan to assign specific tasks to align with each student's strength based on their background—a thoughtful approach. How would you encourage students to step out of their comfort zones and develop new skills while ensuring the group's overall progress?

That I've not thought about it, but uh, that is something, uh.

I will try to.

1st I'll try to know what does, what is the problem they're facing and maybe that might be the approach, I'm not sure.

Thank you, Professor Das. It's clear you're considering ways to address diverse student needs, which is commendable. Let's proceed.

Professor Das, can you outline your 3-year research roadmap and discuss how it aligns with the institution's goals for impactful and sustainable bioinformatics research?

So my 3 year old plan was developing developing vaccine candidates for the escape pathogens. So my first year would be requiring to stabilize the antigens of the escape pathogens. So I'll be only dealing with one of the microorganisms.

From the escape pathogens and list out what are the antigenic proteins they have. And then in the first year of first year, I'll be listing all the antigens and seeing what are the important residues, how pathogenic are there and then listing out all the nonprofit amino acids that I'll be.