Yes, we can be Sure. So my name is Doctor Surabte. Right now I am an assistant professor at Karnavati University, Gandhinagar, Gujarat. I obtained my PhD degree in. Error correcting codes for DNA based data storage systems. So basically it is a. Support of. Algebraic coding theory.

Sure. So my name is Doctor Surabte. Right now I am an assistant professor at Karnavati University, Gandhinagar, Gujarat. I obtained my PhD degree in. Error correcting codes for DNA based data storage systems. So basically it is a. Support of. Algebraic coding theory. And I. I've done work working. Diverse areas of this error correcting. So these are basically comprising. The areas that are linear algebra, abstract algebra. And coding theory basically. Before that I obtained my masters and bachelors in mathematics. From Biswarathi Actually I focus on. Basically the. What is the target audience? The need and the status of the target audience sets the. Uh, diaspora, I mean, sets the stage for delivery. So basically if I teaching, if I'm teaching AB tech. Plus then it is. Uh, basically connecting the dots between the practical areas that. They are seeing. Everyday life. And then, uh. Discuss What are the? Algebraic tools. That are behind. Behind the working principle of the. Application. Such as suppose I am teaching linear algebra. The introductory class should. Comprising of something like image processing.

Sure. So my name is Doctor Surabte. Right now I am an assistant professor at Karnavati University, Gandhinagar, Gujarat. I obtained my PhD degree in. Error correcting codes for DNA based data storage systems. So basically it is a. Support of. Algebraic coding theory. And I. I've done work working. Diverse areas of this error correcting. So these are basically comprising. The areas that are linear algebra, abstract algebra. And coding theory basically.

So you’re working at Karnavati University and your research is in error correcting codes for DNA data storage—algebraic coding theory is a pretty deep area. Anything else you’d like to add about your academic journey or should we dive in?

So you've worked with linear and abstract algebra, and your focus is on error correcting codes. When you're teaching undergraduates, what's one foundational concept in algebra or coding theory that you find especially rewarding to explain, and why?

Actually I focus on. Basically the. What is the target audience? The need and the status of the target audience sets the. Uh, diaspora, I mean, sets the stage for delivery. So basically if I teaching, if I'm teaching AB tech. Plus then it is. Uh, basically connecting the dots between the practical areas that. They are seeing. Everyday life. And then, uh. Discuss What are the? Algebraic tools. That are behind. Behind the working principle of the. Application. Such as suppose I am teaching linear algebra. The introductory class should. Comprising of something like image processing. And then online gaming. To help them understand the. Application of linear algebra tools. That are used in everyday life. And then gradually. Going back towards the. Theoretical concepts.

Alright, so you use real-world applications like image processing to link abstract algebraic concepts for your students, especially in those early classes. Can you give me a specific example of how you introduced linear algebra through image processing—what exactly do you show or ask students to do in that first session?

So you bring in examples like image processing and online gaming to ground abstract concepts for your students—that's a strong way to make the material relatable. Can you walk me through a specific moment where a student struggled with the theory, and how you used those real-world examples to help them understand?

Yeah, so. Basically. The image processing. How the images are stored? And how the matrices are used behind them. What are the matrix algebra tools? That are used. Regarding the. Image processing parts. That are useful to. Help them understand the. Basic idea along with. Operations that they have done already or doing in everyday life. So suppose if I am cropping image. What are the mathematical tools that are used behind? Operational. That are helpful to understand. For the students. So that is my basic strategy.

Okay, so you tie the practical steps—like cropping an image—to the matrix operations behind the scenes, which helps students connect theory to what they already do. That sounds like a thoughtful approach. Before we move on, is there a foundational concept in mathematics you personally find most rewarding to teach, and why?

There are many topics that are useful. Uh, to me. The basic. Foundational Topic. That should be. And that is mostly interesting. Should be set theory. And logic. Because those are the building blocks for any type of mathematics. That are in. Let's say theoretical or. I mean or practical. That are the building blocks.

There are many topics that are useful. Uh, to me. The basic. Foundational Topic. That should be. And that is mostly interesting. Should be set theory. And logic. Because those are the building blocks for any type of mathematics. That are in. Let's say theoretical or. I mean or practical. That are the building blocks. And then there are some other topics like. Probability and statistics. Then these eloquent quotes, how they? Coming from linear algebra and abstract algebra. So many people find. I mean struggle to find. What are the applications of abstract algebra? So this. Error collecting quotes is a beautiful example. For the application to show the application of abstract and data.

Dr. Surabte, I noticed your recent paper, "On the classification of codes over non-unital ring of order 4" published in Discrete Mathematics, Algorithms and Applications. How has your research on codes over such algebraic structures influenced the way you teach abstract algebra or coding theory to undergraduates?

Alright, so you see set theory and logic as the foundation, and you're passionate about showing students how abstract algebra applies to real-world problems like error correcting codes—that connection is often missed in undergrad teaching. Dr. Surabte, I noticed your PhD focused on "Error correcting codes for DNA-based data storage systems." Can you walk me through a time when you had to explain that research to a non-mathematical audience, say, a group of biology students or industry partners? What approach did you use to make the key ideas accessible?

Yeah, so. Primary example for a recording codes. To anyone. Not from academia at all. Or not a literate person. Is to see uh. Their reaction when I say something. That is not. I mean not. Understood by them.

Yeah, so. Primary example for a recording codes. To anyone. Not from academia at all. Or not a literate person. Is to see uh. Their reaction when I say something. That is not. I mean not. Understood by them. So the communication is I am saying something to someone. Who is? To understand or get it at the first day. So the first part is they will ask me. To repeat myself. Or say pardon. So that is they are asking the information. In a repeated way.

Yeah, so. Primary example for a recording codes. To anyone. Not from academia at all. Or not a literate person. Is to see uh. Their reaction when I say something. That is not. I mean not. Understood by them. So the communication is I am saying something to someone. Who is? To understand or get it at the first day. So the first part is they will ask me. To repeat myself. Or say pardon. So that is they are asking the information. In a repeated way. Electronics, then I will. Uh, deliver the information again. And if they get it? Then the correction part is done. An information is. Communicated.

So you pay close attention to the audience and their reaction, especially if they're coming from outside mathematics. When your explanation doesn't land with a non-expert, what do you do next—how do you adjust your approach to help them connect with the idea?

Okay, so you use the idea of repeating information and asking for clarification as a way to explain error correcting codes—relating it to everyday communication problems. How do you adjust that explanation when the audience does have a technical background, like computer science undergraduates or engineers?

Given your background in error correcting codes for DNA-based data storage, where do you see the most fundable research directions emerging over the next three years? Which grant agencies or funding streams would you specifically target to support this work?

Yeah, so. Primary example for a recording codes. To anyone. Not from academia at all. Or not a literate person. Is to see uh. Their reaction when I say something. That is not. I mean not. Understood by them. So the communication is I am saying something to someone. Who is? To understand or get it at the first day. So the first part is they will ask me. To repeat myself. Or say pardon. So that is they are asking the information. In a repeated way. Electronics, then I will. Uh, deliver the information again. And if they get it? Then the correction part is done. An information is. Communicated. So that is a. For electric cell in a basic communication between two people or a. From a people. Is there anything more specific that? Do you want me to?

Right, so you use the idea of repeating and clarifying messages as an analogy to error correction—makes sense when talking to a broader audience. Now, given your background, where do you see the most promising or fundable research directions coming from your work on error correcting codes for DNA-based data storage in the next three years? Which grants or agencies would you target to support that research?

Shower. Couple of ideas.

Alright, you mentioned you have a couple of ideas—I'm interested in how you'd bring industry or consultancy experience into your academic work. Given VIT's focus on industry-academia collaboration, how would you use your experience from consultancy or industry projects to enrich both the academic environment and student learning in mathematics?

Shower. Couple of ideas. That is floating around. In the market? For product development. So already there is a apparatus. Uh, build by. Some university. Group in US. And along with the Microsoft Research. That is in I think. Redmond, USA Group. They built an apparatus in 2019. That is a fully automated system that can store data in DNA. And retrieve also. But the issue with that system or apparatus is it took. Around 25 hours. To just encode. The message hello. And then?

Shower. Couple of ideas. That is floating around. In the market? For product development. So already there is a apparatus. Uh, build by. Some university. Group in US. And along with the Microsoft Research. That is in I think. Redmond, USA Group. They built an apparatus in 2019. That is a fully automated system that can store data in DNA. And retrieve also. But the issue with that system or apparatus is it took. Around 25 hours. To just encode. The message hello. And then? So there's an ample scope of probe. Product development in that area. But that is a big thing. So we need to think. Like 1 is. The storage centers. For DA.

Shower. Couple of ideas. That is floating around. In the market? For product development. So already there is a apparatus. Uh, build by. Some university. Group in US. And along with the Microsoft Research. That is in I think. Redmond, USA Group. They built an apparatus in 2019. That is a fully automated system that can store data in DNA. And retrieve also. But the issue with that system or apparatus is it took. Around 25 hours. To just encode. The message hello. And then? So there's an ample scope of probe. Product development in that area. But that is a big thing. So we need to think. Like 1 is. The storage centers. For DA. I'm already working on a JPG DNA standards. So what will be the? Analog standards. That are uh. Already in the market like PNG, JPEG for physical storage systems. Mobiles or any electronic devices? So analog to that, there is a need for. Uh, setting standards for images. To get stored in DNA mediums. So that. One part is. Uh, highly demanding. Another part is. Finding the right. Or I mean. Appropriate error correcting part part.

Shower. Couple of ideas. That is floating around. In the market? For product development. So already there is a apparatus. Uh, build by. Some university. Group in US. And along with the Microsoft Research. That is in I think. Redmond, USA Group. They built an apparatus in 2019. That is a fully automated system that can store data in DNA. And retrieve also. But the issue with that system or apparatus is it took. Around 25 hours. To just encode. The message hello. And then? So there's an ample scope of probe. Product development in that area. But that is a big thing. So we need to think. Like 1 is. The storage centers. For DA. I'm already working on a JPG DNA standards. So what will be the? Analog standards. That are uh. Already in the market like PNG, JPEG for physical storage systems. Mobiles or any electronic devices? So analog to that, there is a need for. Uh, setting standards for images. To get stored in DNA mediums. So that. One part is. Uh, highly demanding. Another part is. Finding the right. Or I mean. Appropriate error correcting part part. With less amount. I mean less expensive. To use. Storage systems. That can be also useful. And regarding the funding part, there are. Civil funding agencies. That are I'm targeting right now. One is an RF. Then there is matrix by Sharp.

So that apparatus you mentioned from Microsoft Research and the US university took 25 hours to encode just “hello” into DNA—that really highlights the current bottleneck for practical applications. Given those constraints, what's your strategy for making your research attractive to funding agencies? Are you focusing more on advancing the technology itself, or are you positioning your work as a foundational mathematical contribution that could open up multiple downstream applications?

Shower. Couple of ideas. That is floating around. In the market? For product development. So already there is a apparatus. Uh, build by. Some university. Group in US. And along with the Microsoft Research. That is in I think. Redmond, USA Group. They built an apparatus in 2019. That is a fully automated system that can store data in DNA. And retrieve also. But the issue with that system or apparatus is it took. Around 25 hours. To just encode. The message hello. And then? So there's an ample scope of probe. Product development in that area. But that is a big thing. So we need to think. Like 1 is. The storage centers. For DA. I'm already working on a JPG DNA standards. So what will be the? Analog standards. That are uh. Already in the market like PNG, JPEG for physical storage systems. Mobiles or any electronic devices? So analog to that, there is a need for. Uh, setting standards for images. To get stored in DNA mediums. So that. One part is. Uh, highly demanding. Another part is. Finding the right. Or I mean. Appropriate error correcting part part. With less amount. I mean less expensive. To use. Storage systems. That can be also useful. And regarding the funding part, there are. Civil funding agencies. That are I'm targeting right now. One is an RF. Then there is matrix by Sharp. And some other. Agencies. That I want to explore. Regarding. The international collaboration. Like. Indo. Funding opportunities. And then in the German. Letter TR as well. I was already. A participant in a DST Dad. Close it that where. That was focusing on. Archival Storage. In DNA.

Shower. Couple of ideas. That is floating around. In the market? For product development. So already there is a apparatus. Uh, build by. Some university. Group in US. And along with the Microsoft Research. That is in I think. Redmond, USA Group. They built an apparatus in 2019. That is a fully automated system that can store data in DNA. And retrieve also. But the issue with that system or apparatus is it took. Around 25 hours. To just encode. The message hello. And then? So there's an ample scope of probe. Product development in that area. But that is a big thing. So we need to think. Like 1 is. The storage centers. For DA. I'm already working on a JPG DNA standards. So what will be the? Analog standards. That are uh. Already in the market like PNG, JPEG for physical storage systems. Mobiles or any electronic devices? So analog to that, there is a need for. Uh, setting standards for images. To get stored in DNA mediums. So that. One part is. Uh, highly demanding. Another part is. Finding the right. Or I mean. Appropriate error correcting part part. With less amount. I mean less expensive. To use. Storage systems. That can be also useful. And regarding the funding part, there are. Civil funding agencies. That are I'm targeting right now. One is an RF. Then there is matrix by Sharp. And some other. Agencies. That I want to explore. Regarding. The international collaboration. Like. Indo. Funding opportunities. And then in the German. Letter TR as well. I was already. A participant in a DST Dad. Close it that where. That was focusing on. Archival Storage. In DNA. So there are ample opportunities for funding. Regarding this area. And the outcome should be. Somehow, uh. Will be able to deliver some eroculating quotes that are in practical use. In practical sense, not in theoretical at all.

So you're pointing out that while there's been a breakthrough in DNA data storage hardware, the bottleneck now is speed—taking 25 hours just to encode "hello" makes it clear how far the field has to go for practical applications. Given VIT's emphasis on industry-academia collaboration, how would you use your experience with consultancy or industry-oriented projects to enrich the academic environment and student learning in mathematics?

The point about developing standards like JPEG or PNG for DNA-based image storage is pretty intriguing, especially since you’re already working in that direction. Given VIT’s strong push for industry-academia collaboration, how would you incorporate your experience with industry projects or consultancy to enrich the academic environment and student learning outcomes in mathematics?

You mentioned using real-world examples like image processing to help students connect abstract math to practical applications. Suppose you couldn't use slides or typical lectures—how would you design an in-class activity for 200 students that gets them actively engaged with a core mathematical concept, rather than just listening?

The way you described setting standards for storing images in DNA, and navigating agencies like NRF and DST for funding, shows you're thinking well beyond theory. At VIT, fair and transparent assessment is a big deal—how do you ensure your exams or evaluations in mathematics courses are both rigorous and genuinely fair to all students?

Okay, you described practical product development and the need for standards like JPEG for DNA storage, and mentioned targeting agencies like NRF and international programs for funding. At VIT, fair and transparent assessment is a big deal—when you're running a mathematics course, how do you make sure your exams and evaluations are both rigorous and fair to a diverse group of students?

So I believe. Only pen and paper evaluations are not adequate for. A diverse group of students. Some of the students may excel in that and paper. Examination and they make it. Excel also in the practical application. Based on that fundamental value. So my idea is. Giving ample opportunities to diverse group of schools.

So I believe. Only pen and paper evaluations are not adequate for. A diverse group of students. Some of the students may excel in that and paper. Examination and they make it. Excel also in the practical application. Based on that fundamental value. So my idea is. Giving ample opportunities to diverse group of schools. Like pen and paper? As well as. Project is I mean project. Development. That can be. Turned into a. Term paper or a. Mini research paper. Or a full research paper. Otherwise some. Product development, software development, these are also there. And based on that. I would like to. Evaluate their performance throughout the semester Yeah, so. Regarding the advanced statistical methods.

So you see pen and paper exams as just one piece, and you want to give students different ways to show what they know. Can you give me a concrete example—maybe a project or assignment—that's worked well for students who don't always excel in traditional exams?

You were about to share an example related to Advanced Statistical Methods. Go on. Yeah sure, you were starting to talk about Advanced Statistical Methods—can you walk me through an actual project or assignment you've used to assess understanding in that class?

Yeah, so. Regarding the advanced statistical methods. Hey I mean I am right now working in a problem. I mean, there are many research problems that. In this area. That is this. DNA error correlating quotes part. That relies on statistical tools. To measure the efficiency of the system. So. Small. Problems can be divided. Into groups. Of students. To evaluate their. Assessment or approach towards the problem. It is not required every time. That a project. Swept, turning into a. Positive right answer. It may get somewhere, uh, I mean. It may get a negative approach that. This problem cannot be. Done using this statistical tool. That is also a meaningful contribution towards that problem. In the research direction. So it is. Will I mean well deserving to say. If a if a group. Is working in that way and. Will be able to understand. What are the statistical tools that are? Required in this research domain and what are not. That is also a big achievement. Shows the fundamental understanding of those students.

Given VIT’s focus on industry-academia collaboration, how would you bring your experience with consultancy or industry projects into the classroom to enrich student learning and the academic environment in mathematics?

So regarding this academia, industry collaboration. There are right now many. Companies that are. Working on. Specific direction. And uh. As setup research labs.

You started to mention companies setting up research labs for academic collaboration. Can you give me an example of how you’d actually structure a course project or student activity around one of those industry partnerships, so the mathematics students see real-world impact?

So regarding this academia, industry collaboration. There are right now many. Companies that are. Working on. Specific direction. And uh. As setup research labs. That is center of excellence. In many institute campuses. So what's that? Direction we can. Work with some. Research areas. To get some. Focus with the relevant industry partners. Like right now there is a global. Research alliance that is going on. Named DNS Storage al. And many of the Giants. Uh, data storage science like Seagate? NVIDIA. Are already Samsung already part of that? Academia industry collaboration with. Research groups from various. Academic institutes in US. And. All over the world. So in this long scale we can start with. Thinking about this kind of areas. There are some, uh. Industries or research centers? Of the industry partners. That are already. Immersed as. Key contributors to different domains like. Cryptography.

So regarding this academia, industry collaboration. There are right now many. Companies that are. Working on. Specific direction. And uh. As setup research labs. That is center of excellence. In many institute campuses. So what's that? Direction we can. Work with some. Research areas. To get some. Focus with the relevant industry partners. Like right now there is a global. Research alliance that is going on. Named DNS Storage al. And many of the Giants. Uh, data storage science like Seagate? NVIDIA. Are already Samsung already part of that? Academia industry collaboration with. Research groups from various. Academic institutes in US. And. All over the world. So in this long scale we can start with. Thinking about this kind of areas. There are some, uh. Industries or research centers? Of the industry partners. That are already. Immersed as. Key contributors to different domains like. Cryptography. And then quantum computations. And there are not much regarding the DNA storage part. But we can explore. The potential opportunities.

Alright, you mentioned those industry research centers and alliances—like the DNA Storage Alliance and industry players partnering with academia. Can you give me a concrete example of how you’d actually structure a course project or student activity around one of those collaborations, so students get real exposure to industry methods or data?

So. These are very rare movements, I suppose. But uh. My uh. My evolutions are. Based on. The pure uh. Input from the students. And then fair evaluation based on. Based on. Parts I mean. Based on divided.

So. These are very rare movements, I suppose. But uh. My uh. My evolutions are. Based on. The pure uh. Input from the students. And then fair evaluation based on. Based on. Parts I mean. Based on divided. What should I say? That is. I evaluate. On not a scale of 10. Let's say if the total marks is 10. Then I divide it into. Smaller parts. To help me understand. In evaluating and. For the other part, the counterpart as well. That is the students. They will able to understand. How this? Tail marks is divided into 5 components and those five components where the main components. Where I have evaluated them. So in that process. That will be helpful to understand. What is the evolution process and if there is any bias? Introduced unknown.

Alright, Dr. Surabte, you mentioned setting up research labs and partnering with industry players like Seagate and NVIDIA. Can you share a concrete example of how you'd structure a student project or classroom activity that leverages these collaborations to build real employability skills for your mathematics students?

So. These are very rare movements, I suppose. But uh. My uh. My evolutions are. Based on. The pure uh. Input from the students. And then fair evaluation based on. Based on. Parts I mean. Based on divided. What should I say? That is. I evaluate. On not a scale of 10. Let's say if the total marks is 10. Then I divide it into. Smaller parts. To help me understand. In evaluating and. For the other part, the counterpart as well. That is the students. They will able to understand. How this? Tail marks is divided into 5 components and those five components where the main components. Where I have evaluated them. So in that process. That will be helpful to understand. What is the evolution process and if there is any bias? Introduced unknown. And regarding that? Passing rate. Passing rate I mean. Requirements. I believe. That it is. Not the uh. Academic. Excellence. That is. That is helpful. In passing in. Having a greater pass rate. But rather than. What is the students ability to? To express. His or her thoughts? Regarding that topic.

So. These are very rare movements, I suppose. But uh. My uh. My evolutions are. Based on. The pure uh. Input from the students. And then fair evaluation based on. Based on. Parts I mean. Based on divided. What should I say? That is. I evaluate. On not a scale of 10. Let's say if the total marks is 10. Then I divide it into. Smaller parts. To help me understand. In evaluating and. For the other part, the counterpart as well. That is the students. They will able to understand. How this? Tail marks is divided into 5 components and those five components where the main components. Where I have evaluated them. So in that process. That will be helpful to understand. What is the evolution process and if there is any bias? Introduced unknown. And regarding that? Passing rate. Passing rate I mean. Requirements. I believe. That it is. Not the uh. Academic. Excellence. That is. That is helpful. In passing in. Having a greater pass rate. But rather than. What is the students ability to? To express. His or her thoughts? Regarding that topic. To a diverse group of. People or in. Some way that can be explainable? So if throughout. TSMS the students performances are. Constantly increasing. However, their evaluation parts is. Lower. It should not be a. Concern for the student or the institute? To see whether the students are failing. That is from myself.

Okay, so dividing total marks into smaller components makes your evaluation process more transparent, which can help address concerns about fairness or bias. Now, let's shift gears and talk about some specific skills for this role. Suppose you're teaching a course on Advanced Statistical Methods, and you want to introduce a new unit on the application of machine learning in supply chain management. How would you design a hands-on assignment for your students that requires them to apply both advanced statistics and AI techniques to solve a real supply chain problem?

Alright, so you break down the grading into clear components, which helps both you and your students see exactly how marks are assigned and where any possible bias might creep in. And you’re firm that boosting pass rates shouldn’t come at the expense of academic standards. Now, earlier you mentioned working with research groups internationally and participating in collaborations. Can you share one publication from a reputed journal you’re most proud of, and tell me what made that work significant in your field?

Alright, so you make your grading transparent by breaking marks into smaller components, which helps students see exactly how they're being evaluated, and you’re clear that raising pass rates isn’t your main concern—student development is. Now, thinking about guiding student research, suppose you’re supervising a master's thesis where the student’s results don’t match their hypothesis, and they’re discouraged. How do you support them to keep moving forward in their work?

So that is. The core part. Regarding. Teaching and mentoring. I have already minted. 4-5 graduate students, actually. And that turned into. One full journal paper. One conference poster. And then? Two of the journal papers. Already in pipeline. So regarding the monetary part. I always. Start with the idea. That there is nothing like. No in the research. That I obtained from my research mentorship.

So that is. The core part. Regarding. Teaching and mentoring. I have already minted. 4-5 graduate students, actually. And that turned into. One full journal paper. One conference poster. And then? Two of the journal papers. Already in pipeline. So regarding the monetary part. I always. Start with the idea. That there is nothing like. No in the research. That I obtained from my research mentorship. That there is. Always a rule. For a partial, use. In a research so if. Their hypothesis, I mean their results are not matching with the hypothesis. That helps us to. Suppose explore the new areas. That is this. Approach is not suitable for this. Area. And that can be helpful to find out. Some fundamental ideas. Or some fundamental. To specifically. Target that hypothesis to make possible. That is first part. The second part is if some approaches are not applicable to that. Specific target. Then we can. Narrow down the area. Or narrow down the number of approaches and. We start working with the remaining approaches. That is. Healthful Acid. I mean. In my research. Journey I have faced. This type of problems many times. And that. Help me to understand. Why this specific approach is failing? Towards this specific target. And then we were able to sit. A new approach with better accuracy or better intuition. To get the desired result.

Okay, so you see setbacks in research as learning moments and you’ve already mentored several students through to publications, even when results didn’t match their hypotheses. Now, thinking about your own teaching, how do you ensure your lectures are clear and structured, especially when introducing complex topics like DeepTech or AI in mathematics to students with very different backgrounds?

So you've mentored several students through setbacks and helped turn those moments into publications, which shows a lot of patience and practical guidance. Now, in your teaching, how do you make sure your lectures are structured in a way that helps students at different levels grasp complex mathematical concepts, especially when some might not have a strong background?

So the basic idea of having a successful. Is relias from the start. That is the course curriculum. And how the? Designing of that course curriculum. And that should be. In a gradual manner. Ford, I mean. For a basic. Audience. That may do not have. The adequate backgrounds. Regarding that topic. So the designing of the course curriculum is. The core part of having a. Successful teaching services. For a course. So. Regarding that. My main focus is. Uh, placing the fundamental ideas. That are easily. Achievable, uh. By solving some. Theoretical problems and then turn them into a real life application based problems. To help students understand. And gain confidence. And then gradually increasing the difficulty level. To a certain point. Where student will be able to. Class the ideas 1 by 1. And then turned into. A productive. Output.

Right, so you put a lot of emphasis on scaffolding—making sure the curriculum starts with fundamentals and only then moves into applied and advanced material, so students don’t get lost if they’re not coming from a strong background. Shifting gears, Professor, how do you approach guiding student projects or research, especially for those who are just beginning and might feel overwhelmed by open-ended topics?

So my approach is always targeting. But what can be done by a student?

So my approach is always targeting. But what can be done by a student? From the beginning. Towards that problem direction. So if we if I am. Approaching to a theoretical problem. And the student is. Uh, very good in programming. Or software skills. Then we can start having gathering data. Based on the students programming skills. And then we can turn them. The date turned the data. Into a hypothesis. That since the data shows the hypothesis is true, then. We can start. Reviving the theoretical part. And between the that. Data gathering part. I always mentor the student. Regarding the. Theoretical aspects. And provide materials. And discuss with them constantly. To gain confidence and then small pieces. Uh, split into. Right places. And then they are able to. Contribute meaningfully. Based on theirs. Strong points first. And then gain. The knowledge regarding the other parts that they are not might might be strong. Towards the end So my PhD is basically. In a specialized area that is also a state-of-the-art technology. So it is not a. Not a technology that is used. But it is. A kind of technology, that is. Being developed for the future. So.

So my approach is always targeting. But what can be done by a student? From the beginning. Towards that problem direction. So if we if I am. Approaching to a theoretical problem. And the student is. Uh, very good in programming. Or software skills. Then we can start having gathering data. Based on the students programming skills. And then we can turn them. The date turned the data. Into a hypothesis. That since the data shows the hypothesis is true, then. We can start. Reviving the theoretical part.

Okay, so you focus on what’s feasible for each student. Can you give me a recent example where you adjusted a project topic or research direction for a beginner, and how that helped them engage or succeed?

So my approach is always targeting. But what can be done by a student? From the beginning. Towards that problem direction. So if we if I am. Approaching to a theoretical problem. And the student is. Uh, very good in programming. Or software skills. Then we can start having gathering data. Based on the students programming skills. And then we can turn them. The date turned the data. Into a hypothesis. That since the data shows the hypothesis is true, then. We can start. Reviving the theoretical part. And between the that. Data gathering part. I always mentor the student. Regarding the. Theoretical aspects. And provide materials. And discuss with them constantly. To gain confidence and then small pieces. Uh, split into. Right places. And then they are able to. Contribute meaningfully.

Alright, so when a student’s strong suit is programming, you have them start by collecting and analyzing data, then use the results to pivot toward more theoretical questions—that’s a hands-on way to scaffold research. Now I need to touch on your expertise in supply chain management, advanced statistics, and AI in mathematics. Can you give me a specific example where you used advanced mathematical or AI methods to optimize a real-world supply chain or logistics problem?

Alright, so you tailor the starting point of projects based on each student's strengths, like leveraging their programming skills to collect data before moving into theory. Shifting to communication—how do you ensure your lectures and materials are clear and structured, especially when you need to explain advanced topics like deep learning mathematics or supply chain algorithms to students who might not be familiar with the basics?

So my PhD is basically. In a specialized area that is also a state-of-the-art technology. So it is not a. Not a technology that is used. But it is. A kind of technology, that is. Being developed for the future. So. This is relevant regarding the. Potentiality of the DNS storage in terms of. The volumetric. Density that DNA gives. So it is the need for the future actually. With the sustainable goals.

So my PhD is basically. In a specialized area that is also a state-of-the-art technology. So it is not a. Not a technology that is used. But it is. A kind of technology, that is. Being developed for the future. So. This is relevant regarding the. Potentiality of the DNS storage in terms of. The volumetric. Density that DNA gives. So it is the need for the future actually. With the sustainable goals. So the research is not only current. But also relevant towards future directions as well. And then there are some other topics that I am exploring. Right now, those are. Involving AI and e-mail. In this research topic and then. Quantum error collecting codes or quantum deletion codes? That are also a hot topic. Now, and they are going to be a moment. That we'll have the. Quantum. Regarding this. Physical world. So the research will be current in the future essentially.

Okay, you mentioned your PhD is in a cutting-edge area, but let's touch specifically on supply chain management and advanced statistical methods. Suppose you're asked to design a mathematical model to optimize inventory levels across multiple warehouses with variable demand—how would you approach building and validating that model?