Good day, Dr. R. Remya. 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.

So good evening, Sir Marisel Premia. I have completed with the history in the year 2021 totally. I'm having total years of working experience. I completed my aim in the area of applied electronics in the year 2012 and my electron and my using the year 2009 and my specialization is electronics and communication engineering and now I am.

Uh, in a machine learning algorithm, along with that, I have included IoT algorithm also, uh, IoT also. So I was IoT based work I'm doing now. Uh, so currently I have, uh, teaching digital electronics, microprocessor and PG courses with the soft computing, uh, previously until I have handled patent regulation paper. So I'm well. And, uh, I think from my point of view, I'm the just. Good in my machine learning algorithms and all.

Doing my post-doctoral in. Postdoctoral work in.

And also I'm expertise in doing so in projects also I'm I'll make the students to do the project by their own or so I make the students to publish their work in minimum as in the conference level. Also I focused on the journal publication also. Currently I'm having a 7 ACA journal and. Numerous conference papers also and.

Uh, now I have a submitted 2 papers in ACA journals with AQ1 index journals.

Uh. Then uh. And I have previously I have worked in now I'm working in Sri Krishna College of Engineering and Technology. It is an autonomous college. It is located in Coimbatore. Previously I have my working experience is at Vail Tech, Rangarajan Randy Institute of R&D, Institute of Science and Technology, Chennai. There I have worked for one and half years. There only I have started my research. Career. They are only focused on Iot-based projects and all.

There I have the research lab available there I have worked a lot with iOS debate works. So Iotcom machine learning algorithm industry came from there only Sir.

Thank you for sharing that, Professor.

Thanks.

You're welcome, Professor. Let us continue. To begin, could you briefly outline your academic and research journey, specifically focusing on how your expertise shapes your philosophy for teaching and guiding students?

Yes and no. I am currently I'm working in a institution only so so at each and every year I am I am come across so many students. At each student I will find out their inner knowledge and ask them to improve it by by giving some certain inputs to them and make them to convert that ideas into a project. Now I have converted one of the projects into a patent.

The same I asked them to submit in the project I also that is they have submitted for under Kabila scheme also. Now I have focused on another set of students to submit their work in the conference. Since their work is that much only I asked them to do like that to improve their work in the next phase. I also working along with them. I also know I am doing my PDF also that work also. I have worked along with the students so they can.

Also will get increase improve their knowledge. I'm also guiding at this side. So their research knowledge as well as mind I'm giving some inputs to them and also making them to do the work. So their knowledge as well as myself also getting improved at the same time. So now I am making so if if they are working in the their research work is focusing on. Meaning and my major phases there is means at the main project level.

1st to case level, I asked them to do the hardware level. Then in the second phase level based upon the outcome I I asked them to convert that into a data set. Using that data set I machine learning algorithm I have asked them to incorporate that the outcome should be based upon that is the outcome that is in the next Phase I asked them to do in the. Software level. So on the whole they are creating one set of worker that is.

I also to do novelty project also the novelty. You know in all my work I have included the novelty work. Also in my PhD work I have in I have I found a new algorithm that is called a series of exponential function that is a novel algorithm that is mainly used for images segmentation like that my or my my my aim is to make the students also to do the work like that.

Sir.

Yes, Sir, novelty is.

Is is that?

Novelty is the ultimate aim in all the research works. As all the resources well known that novelty is the main aim. So in my work also I have included novelty. So I also make the students to include the novelty workout. How means I ask them to learn the basic knowledge, basic algorithm in all the basic thing in all the algorithms.

Learnt all the things afterwards. Why they are using on what basis they are using. Then I ask them to include just include one more parameter along with the bias. For example. It's just an example along with the bias one more parameter. If I include a means what is happening at the output edge then accuracy has to be estimated for that outcome. Like that I ask them to do. Right now I I make the student like that to convert 1 work into a into that is either a poker like that. I asked them to change and I asked them to find how their performance will get varied at the out potential if a small variation is getting at the output end means I appreciate them so this much of improvement you made in your worker. So it is a well and good like that. I appreciated them and asked them to submit in any one of the channel for example in.

Understood, Professor. To ensure a comprehensive evaluation, let me dive deeper into some of your specific skills and expertise now. Ready?

Student level I, I'll make it, I'll make them through. So in the for example, in the case of publication handle, if that journal paper got rejected when I asked them to submit in the conference level there, I won't make them to disappointment.

Accept.

Thank you, Professor. It’s commendable how you guide students through the iterative process of improving their work, emphasizing novelty and ensuring they gain valuable knowledge from both successes and rejections. Now, I’ll ask questions directly tied to your skills and expertise to assess further. Could you describe your understanding of how machine learning models can be effectively used for biomedical image processing, referencing your own research or teaching experience?

Yes Sir. When I completed my PhD in that biomedical image processing only Sir. So my work is to detect the brain tumor by automated system for identifying brain tumor using magnetic resonance imaging. In that imaging work I have included I have incorporated a new methodology for image segmentation and also a novel detection for filtering algorithm. Also filtering means filtering, how filtering will done means either remove the noise. So in my work I have included a discrete wavelet transform that is a general algorithm. But there I have included a thresholding algorithm. Is there the more a new equation have been has had included in that thresholding concept. So the output will be is better when compared to the previous one that that is that is enhanced DWT filtering algorithm for brain tumor detection. For that taper I my citation is of 22 count that is.

There is a I love the paper that is that much of effort I put in that work to get the output that that is a simple algorithm. That is the key point of my research. After that, I have focused on the machine learning algorithm. That is the next level of my work. That machine learning algorithm I have included in the image segmentation work. In that image segmentation I there there I focused on the machine learning algorithm. There have included a series of exponential function like there is some.

Summer 3-4 product terms I have included in the equation to generate the outcome there I have a that paper was published in the elsewhere that is biomedical signal processing and control. It's a Q1 channel. They are also in that paper I have included the novel workup. So my area is fully focused on the image segmentation image that is fully on image, image filtering, image segmentation. After that I have.

Included that is published 1 paper in image that is similarity metric algorithm. There I have included a small equation that is not on machine learning algorithms Segmentation segmentation paper. I have included the machine learning concept. So I won't depend on the previous algorithm and all just I will learn all the things but I will include some novel equation in all the algorithms that is.

My uniqueness.

Thank you, Professor. Your extensive work in biomedical image processing, particularly focusing on novel algorithms for segmentation and filtering, is indeed impressive. Incorporating discrete wavelet transforms with innovative thresholding and transitioning into machine learning with novel equations demonstrates both depth and originality. Let’s explore another area of your expertise. How do you approach teaching foundational concepts in AI, machine learning, or data science to ensure students with varying levels of preparedness understand and engage with the material?

Uh, as a yes, a uh, then about my teaching, uh, my in previously I worked at Vailtech. They are, uh, they are focusing on the fast tracker students, fast track student in the sense they are a well and good, good in their academics. So they are focusing towards the placement. So they are concerned as a fast track. So far their students, they asked me to teach those kind of, uh, subjects. So for example, there I have taught the software computing and the pattern regulation. These all are very.

Well, I'm good papers. So it is a fully focused on my research also. So, so those kind of papers I taught taught for the students also the especially for fast talking students. I will teach then about the slowness. They also give some slow learners students also to me based on in that area, I will give the those kind of things. Then a tool for data sense also I thought that is tool for data sense in the sense we have the data set using that.

We are performing the processing then how we are visualizing visualization in the sense that is without doing any coding and directly using the data set. We can visualize it by either in the form of a bar chart or in the form of file chart.

Then.

Tableau Data, Tableau software, those kind of papers also I taught to them. Then Python for data sense also well and good. Then in the NPTEL course also I have completed those kind of papers. So based on their based on the knowledge only, they have assigned the papers to me. Python for data Sense, tools for data science, those kind of papers I taught, taught through the students.

Then some great views and all I can visualize using.

Though so that much of experience also I have.

Sir.

Thank you, Professor. Your teaching experience clearly demonstrates a balance between addressing the unique needs of both advanced and slow-learning students, with a focus on practical tools like Tableau and Python for data science. It's evident you emphasize practical understanding and visualization to ensure student engagement. Let me shift a bit. How do you evaluate students' understanding of complex topics in AI/ML, ensuring they are not only learning but are prepared to apply the concepts in real-world scenarios?

So far that what I will do means starting from the scratch. I also I will I'll teach I'll I used to teach stuff. So in the interest rates itself, I won't teach the basic algorithms and all first I will go ink ask them to do the some practical examples, for example Python by using the Python, it's open, so it's open software.

I single matrix matrix in the sense. It will be a forecast for Vitex or Firetrust 5 metrics and I I prepared the cons content in excel sheet using that I asked them to reduce the noise or first I asked them to visualize what are the things present in the in nature image. In the sense it is combusted pixels only. So pixel means in the data set in the excel sheet we have some phytrosphere matrix means. I asked them to ask them that as an image so far in that image I asked them to find how many zeros will. Is there any zero exist to visualize then not a number is there or not like that ask them to visualize that one. So by manually itself they are creating the data set and checking whether it is visualize visually itself. They can know and algorithm practically also I ask them to check like that step by step I ask them to look then if any not a number, not a number means I ask them to assume that does a noise then I need to reduce the remove. So for that I need to check pixel wise if not a number exists remains I need to convert that into its zero or based upon the neighboring value. Either it may copy the neighboring value or you may take the mean of the neighboring or median of the neighboring like that. I also should do so. So I I asked them to assume that if you are doing like that the noise will get reduced like that. I asked them to do step by step so practically as well as theoretically also they can understand what is the concept behind.

Just a single matrix. I will be taken then for that.

The image what the mission will do like that starting from the staff 'cause I asked them to do Sir.

Thank you, Professor. Your structured, hands-on approach to teaching complex AI/ML topics, starting with basic concepts like pixel understanding, visualization, and progressing through noise reduction using theoretical and practical methods, is innovative and impactful. It clearly reflects your dedication to ensuring students grasp both foundational principles and their real-world applications. Let’s move forward into another area of your expertise. Could you share an example of how you’ve guided students in their academic research or projects, particularly in incorporating novel AI/ML methods or contributing to research publications?

Sure, Sir. So first, for example, I am asking I am I'll be as the mentor or as a teacher of a particular student means first I will identify and all better in that who and all log lag in that I I will group the student as weak student prize student like that I will group in a single batch in a single bus. There is composed of so many students, Then I ask them to do a separate work for each one. That is if they are weak in their work means I ask them to collect. Get the data set so if I gave somewhat means they will they will eager to do their work. So they are assuming that my mom is. My mom asked me to do something so they will focus on that worker so they will collect the data details after that what they what this what I asked the second member to do means to convert to do some literature survey. So if another two I asked another two members to do 5 literature survey like each. Then I asked them to explain.

While explaining, I asked all the five students to come and meet. Come ask them to meet me. So if one student is explaining this, I ask all the students to listen. Then I'll give some some inputs to them. Your way of presentation is correct only. But if you are checking like this, if you are working, if you are reading go through all the content. Means while reading itself you should compare with the matrix. 15 Cos 5 matrix like that you compare and prepare the literature survey. So if they are well and good in the literature survey means it will be well and good to prepare for to do novel work in their algorithm. So if they are strong in one algorithm means by using that algorithm itself they can't prepare a new one. So if they if they are well on good means at each step if they have understood the knowledge means they should they can they can do some.

In the in the same algorithm itself like that I asked them to do the research work. So if I did the work for I gave assume two students to with the 255 literature service and all. So now three those two three student works got over. Then I asked the next two students to do the project to do the project in lessons coding work, one student will do the coding work means another student will do the thoroughly do the paperwork.

Paperwork like that, I asked them to do so within one or two months. I will convert the project either in the form of a literacy survey paper or in the form of a conference paper that much of confident I may confident level has to be given to the students.

Right now till now, I'm doing the same, starting from the research, I'm doing like this only for my students. So finally what they will, which will tell me to mean, ma'am, tell, tell to me that, ma'am, because of you only we gained this much of knowledge like that. They will, they will tell to me.

Thanks.

Thank you, Professor. Your collaborative approach of grouping students, assigning thoughtful tasks like data collection, literature review, coding, and paperwork—and mentoring them step-by-step toward publications—is highly commendable. It’s clear you imbibe both rigor and encouragement in your teaching and research mentorship. Let us now focus on validating some specific skills. Shall we proceed?

Oh, sure, Sir.

So.

Set.

Sir. Your voice is breaking, Sir.

Apologies if there's been any confusion, Professor. Let me continue. Could you explain your approach to developing coursework that effectively balances theoretical foundations with practical applications in Artificial Intelligence and Machine Learning?

Sure, Sir, in the case of an artificial intelligence, they need that is in the theoretical side and all they can learn so many things. But if it is a theory come project theory, come paper means for the for example, the same thing, it means reduction, image segmentation, image filtering and always there means parallel, the course and the course itself. Python or Jupyter, that kind of practical works and all can be included.

If they are, if they have completed all those scores in the lower semester means data visualization tool and all they can can be included in the courses and also so AML means it is the IT is a well developed one also in the developing stage. The usage of tool is very very important. If they are well, good well and good in the coding part only they can sustain the future.

So coding part is a very, very important one. Visualization is as a part, as a small part. So coding part is very, very important. So initially Python for data science is very, very important. Afterwards, little bit, little semester by semester, they can learn what, what, what is the basic concept behind each and every algorithm. So each course coding is a major part.

All those kinds should be included in all the courseworks.

Thank you, Professor. Your emphasis on a step-by-step approach—starting with foundational tools like Python and progressively advancing to algorithms and coding-intensive coursework—shows a strong commitment to ensuring students build both theoretical understanding and practical skills over time. Now let’s discuss your understanding of guiding research students. Can you explain your process for helping students identify and refine a novel research problem within AI/ML?

Sir, uh, the kind of, uh, knowledge we need to, uh, make that is, uh, that should be developed from the first year onwards. So basic thing. Then in the second year, they should, that is the, the first year they can learn the basic fundamentals. Second year coding part, then third year algorithm level like that, they can't be improved. That is, at each level, different set of guidance should be given for the students at the external, that is either by.

Channel number or by the internal number. The internal numbers play the major role. So they are leaving, they are standing at their at the side. So main tab as well as the course staff, course faculty plays a major role in guiding the students at various level. So knowledge at the programming level from the scratch is needed for both the faculty as well as the students.

Understood, Professor. Your structured approach to guiding students—starting with fundamentals, advancing through coding, and culminating in algorithmic work—emphasizes the importance of gradual and consistent guidance. Faculty involvement at every stage is indeed critical. Let’s now discuss something specific to your professional qualifications. Could you share how your PhD work and your research publications have influenced your ability to guide student projects effectively?

Our scheduled time for the interview is now up. Before we conclude, do you have any questions related to the role or the company?

So am I audible?

Yes, Professor, you're perfectly audible. Shall I repeat my question? How have your PhD work and research publications influenced your approach to guiding student projects effectively?

Yeah, sure, Sir. So, yeah. So after my PhD, I have made I made the students to do the pro, do my project. So initially I have a little bit knowledge to know a little bit knowledge of how to guide the students. So, so I make the students to redo the coding of my project. So at first that is my first stage. After that I know how to guide. I came to know that how to guide.

The students, so afterwards I made them. Dear student, you may do like this means you will get you may check how much variation will happen like that. I make the students to do that is in my work I comes. I assumed that that is my optimal workup, but after making the students to do the work means work after that is after finishing their after the completion of their work again to know that the outcome is better than my own work.

Like that I may like that I visualized that is so that's sort of work. I have wish I visualized Sir. So that kind of students are are there that is so afterwards only again to know that. So if I gave some input to others means they are knowledge plus my knowledge will get will boost up the outcome. That is a lie. Nowadays I'm working like that. And I will do some work after that I I make the students to upgrade that one so they are.

Knowledge and my knowledge partly will get increased.

Scrap it.

Understood, Professor. Would you like me to move on to any specific area or question?

So nothing, Sir.

I'm very happy to interact with you, Sir.

Oh, OK, sure, Sir, we can conclude.

Thank you, Professor. It has been a pleasure learning about your expertise and approach to teaching and research. If there's nothing further you'd like to discuss, would you like to confirm that we can conclude the interview?