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Interviewed on Apr 1, 2026
Overall performance
Demonstrated practical teaching and research mentoring expertise
Summary
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Good day, Dr.. 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. Let's begin.
I'm Doctor M Basmati.
I am Doctor M Vasumathi.
Thank you, Professor Basmati. Please start by introducing your professional journey in academia.
Thank you, Professor Vasumathi. In your teaching experience, do you find yourself gravitating more toward delivering foundational theory, or do you prefer hands-on, laboratory-based instruction with students?
I'm more. More in handling lab. Uh, like deep learning, machine learning? And other image processing related labs also have handled and I have conducted more than. More than five workshops. On Matlab. Matlab. Image processing workshops also. So firstly I I want to introduce myself. I didn't finish that one. Shall I proceed with that?
That's clear, Professor Vasumathi. You mentioned conducting multiple workshops on MATLAB and image processing—what specific skills or concepts do you prioritize when training students in these workshops?
A practical oriented explanations. For the better understanding of students.
A step by step evaluation. Also I have given for the. Students and also I have evolved the students using. Practical test cases.
You’ve published research on de-noising and key frame extraction in deep learning, as well as automated detection of foreign objects in pediatric radiographic images. How do you incorporate insights from your research into your undergraduate or postgraduate teaching, particularly when designing lab assignments or student projects?
You emphasized step-by-step evaluation and practical test cases in your lab courses—can you share a specific example where this approach helped a struggling student grasp a complex concept in image processing?
Yes. So image processing, my area of interest is medical image processing. Along with the deep learning. Most of the algorithms. And I have contributed my research works towards. Deep learning algorithms only. So for the students first I would first I will explain my. Work practical. Work and my research worked. For the better understanding and. Engage them towards the research. For example. For a medical image like. X-ray R Petty Majors. We need to clear. The simple I will start with the simple. Exercise by denoising. So starts with the denoising. So I have a. Demonstrated with several. Algorithms. And like. For applying. Unlike A median filtering for noise removal. And Sobel Canny. For the for the noise removal processes, I have explained these algorithms first. Then I will. Explain the age reductions algorithms, Canny edge reductions, Opal edge reduction. Uh, for the feature extraction process. Then I will explain some of the advanced. Concept that are relevant or trend are in trend like. Multiply. Optimization algorithms for feature extraction. And uh. I have incorporated some of the. A multi criteria. Based decision making algorithms like. And some of the. Algorithms like. In addition to that, I have explained the keyframe extraction. Keyframe extraction is nothing but from the IT is comes under the video processing. And by extracting the key frame. Keyframes. We have to select the optimized 1. Uh, for the. Uh, classification or for? For a temporal relation analysis using the. A deep learning. So these algorithms I will start with a very small algorithms like filtering. And I will slowly get them into. Very, uh, strong and elaborated, uh. Umm, advanced techniques And also I have to. Bring my students. To the research through this app.
Thank you for clarifying your teaching approach. Now, looking ahead, can you outline your research roadmap for the next three years, focusing on how your work could drive both high-impact publications and external funding for the institution?
Yes, sure. My recent work got published in September 2005 in Expert Systems. Sorry, September 2025.
Expert system with application. Uh, Q1 Scopus Index Journal with the impact 7.5 impact factor.
Let's shift focus to your instructional methods. For a large-enrollment course, how would you implement an active learning model—such as a flipped classroom—without relying on traditional slide-based lectures?
So this algorithm, sorry this work is titled Dual optimization.
You mentioned hands-on, practical engagement—Professor, could you share an example of a student project you have guided that aligns with emerging technologies, and describe how you ensured its successful completion?
Let’s turn to departmental responsibilities. Suppose VIT University wants to improve its “Research per Faculty” metric for accreditation purposes. What systematic approach would you take to help achieve this goal?
Strategy Denoising. And MCDM waiting for keyframe extraction. In deep learning. So in this book. I have um.
You mentioned your dual optimization strategy for denoising and keyframe extraction—how do you document and share the results of this work in ways that support accreditation processes and departmental reporting?
My work process is a dual optimization framework. For keyframe extraction, where I first remove. Noise frames. Then rank frames using MCDM. And finally use RNN. LSTM to capture temporal relationships. This approach improves.
Accuracy. Reduces redundancy. And F1 score. Uh improved F1 score compared to existing methods.
That’s a sophisticated pipeline, Professor Vasumathi. When mentoring students through similar research projects, how do you ensure that their experimental protocols and documentation are robust enough to meet both publication requirements and the standards expected in accreditation audits?
That's a sophisticated pipeline, Professor Vasumathi. When mentoring students through similar research projects, how do you ensure that their experimental protocols and documentation are robust enough to meet both publication standards and institutional accreditation requirements?
So in this work. I have applied two optimization techniques. The first one is denoising. Initially. Noisy and low quality frames are removed from. Hybrid optimization technique. Combining. Both flight optimization. Latin hypercube sampling. And softmax transfer functions. This ensures only. Meaningful frames. Art processed further. Image speeches like. Color texture. And deep CNN features are extracted from. Each frame and uses input. To mod flight optimization. This features help. Algorithm. Identify and remove noisy or less informative. Phrase umm. Then. The Modfly optimization. It's a bio inspired algorithm where candidate solutions. Move in spiral. Towards the best solutions. Similar to moth flying around the light. In my work it is used to optimize. Feature extraction and improve denoising of. Uh, video frames.
That's a sophisticated pipeline, Professor Vasumathi. When mentoring students through similar research projects, how do you ensure that their experimental protocols and documentation are robust enough to support accreditation reviews?
Next I have applied Latin hypercube. Sampling is combined with mouth flame optimization. To generate. Well distributed feature samples during the denoising stage. Improving the robustness and accuracy. Of frame selection. The next I have applied the softmax transfer function. Is used during feature. A processing. To normalize values. And assign probability. Based importance. 2 frames or features? Helping in better. Selection up. A significant key frames.
That’s a sophisticated pipeline, Professor Vasumathi. When mentoring students through similar research projects, how do you ensure that their experimental protocols and documentation are robust enough to meet institutional accreditation standards?
The second optimization. I have applied MCDM. So MCPM is a decision making method. Where multiple criteria are considered. And waited to select the best option. So in my work. Umm, to rank. To rank the frames. And choose the most informative keyframes. I have used this. Algorithm so critique is an objective weighting method. In MCDM. That assigns important. Criteria. Based variations and independence. In my work it helps identify. The most informative features. For accurate frame ranking.
That’s a sophisticated pipeline, Professor Vasumathi. When mentoring students through similar research projects, how do you ensure that their experimental protocols and documentation are robust enough to meet both academic standards and external accreditation requirements?
Then I have applied 2 deep learning techniques. One is RNN and another one is LSTM. So RNN is used for sequential data. As it remembers previous inputs. But it struggles with the long term dependencies. LSDM improves. This bike. Using memory cells and. Gates to retake important. Important features overtime. Making it more effective. For task like video analysis. Next I eat. Use the.
Use the LSTM. For.
You explained how your research uses dual optimization for keyframe extraction and detailed your use of MCDM for frame ranking—how do you plan to align this research direction with seeking external grants or forming industry collaborations to support your work over the next three years?
You’ve described a highly technical research process—when guiding students through projects that involve multiple optimization and deep learning techniques, how do you ensure their documentation and experimental records are detailed enough to meet national or international accreditation standards?
About my contribution. For the institutional development. Recently I have a. Contributed. To my institution for the development of setting up a team startup pre incubation center. With seven point 5,00,000 funding. From TN startup. Then. It is not. It is 7.5 lakhs.
You described helping set up a startup pre-incubation center with substantial funding—what specific administrative processes or documentation did you implement to ensure compliance with external funding and institutional audit standards?
Funding from PN Startup. I have initiated and received received from my institution. Then. I acted as a. Coordinator for. MSME project. Hackathons, MSME IDEA Acton project coordinator. And acted as a mentor and received. 15,00,000 Funding. For my student project. Recently it is held in a. The results out. Two days before. So next. Many accounts sih pentathlon cyber hackathons. Kentucky on cyber. At the turns conducted by the mighty. So that also I have get participated and also I have. Published the. Um, articles. Publish my blog in. Submitted. Yay, sorry not in a submit. India AI platforms.
You described your involvement in coordinating MSME hackathons and securing significant funding for student projects—what documentation or reporting processes did you put in place to ensure transparency and adherence to the funding agency’s requirements?
I'm doing the activities like uh. IPR activities. National level coordinating with IPR. Professionals. I'm organizing uh. Uh, workshops Like, uh. A Nippon. And it is not Nippon Nippon NIP AM.
Thank you for detailing your process. Now, Professor, imagine a scenario where a student alleges grading bias in your course, but the department is also under pressure to meet institutional pass-percentage goals. How would you handle this situation to ensure both fairness and adherence to academic standards?
So currently I'm involved. As a principal investigator. In the DSD Sangal project. Proposal writing. Representing my institution. Focusing on. Innovative Research. And technology driven solutions.
You mentioned leading IPR awareness programs and serving as an incubation cell coordinator—when disputes arise between student innovators and external partners over intellectual property rights, what approach do you take to mediate and ensure academic integrity is preserved?
ISRO. Funded project.
Thank you for detailing your involvement as an incubation cell coordinator and in IPR awareness programs. When you encounter disagreements between student innovators and external partners about intellectual property ownership, how do you mediate those conflicts to protect both the students' interests and the institution’s reputation?
So, which is held in 2011 to 2013. Vit University, my principal investigator is. Doctor S Margaret Anusha, Professor. Spoke uh from BIT University.
So that that work also. I have worked in image processing only.
Thank you for sharing those details, Professor. You mentioned serving as a principal investigator for a DST-SERB project proposal—can you describe a situation where you had to balance the interests of your research team with the expectations or requirements of external stakeholders, such as funding agencies or institutional leadership?
And so if you want I can elaborate that work also.
Thank you, Professor. You described your dual optimization framework for keyframe extraction, combining denoising with Modfly optimization, Latin hypercube sampling, and softmax transfer. Can you walk me through a concrete example where a specific set of frames was misclassified as noise or keyframes, and how your approach corrected that classification compared to a conventional method?
Thank you, Professor. Based on your experience with multiple research funding cycles and institutional coordination, describe a time when you encountered a conflict between your commitment to academic integrity and pressure to adjust grades to meet an institutional pass-percentage requirement—how did you address this situation?
So in this situation. I will handle the. The pressure or this kind of situation, uh. The time management is very important. And I get my. Team or or my student team to the positive. Reinforcement, that is uh. Giving some. Positive energy to my team. I can handle this very well, so already I'm in a situation like this when I handle. Projects so. So. So first I would uh. Elaborate the.
First I would elaborate the need for that work. And the importance of the work. How? How? Uh. How? What is the need for the? Work and what is the importance or significance of that work, uh, for our institution or for that work nature? Uh, so. So in that way I will. 8 days my students are in. To involve, to get involved that situation.
Okay. You mentioned using positive reinforcement and team management to address such pressures—can you give a specific example of how you maintained fairness and transparency in your grading when institutional expectations conflicted with your academic standards?
Okay. You mentioned using positive reinforcement and team management to address such pressures—can you give a specific example of how you maintained fairness and transparency in your grading when institutional expectations conflicted with the actual student performance?
It's like you give a specific.
Understood. In your experience as a project coordinator or mentor, have you ever had to formally document or defend your grading decisions to either students or administration—if so, what process did you follow to ensure your evaluation was defensible and transparent?
Both. I have applied both defensive, defensible and transparent techniques. Uh, in our institution, current institution, we are following the. Uh, grading systems, uh, using uh, Blooms Taxonomy. Uh, evaluation. Uh, so by using that one, we can easily identify the keywords from the. Answer sheets and I can give. Evolution based on that only. Uh, so in case of. Project evaluation. And lab manual evaluations. I give some of the. Test cases. To run. Based on the test cases I will evaluate. So.
Either true or false. Both the condition I will check.
Thank you for detailing your approach. Shifting focus, how do you leverage your professional network or industry contacts to create meaningful internship or employment opportunities for your students, especially in areas like multimedia or AI in media?
Thank you for describing your evaluation strategy using Bloom’s Taxonomy and test cases. When you design student projects or assessments to align with emerging technologies, how do you ensure that the skills and outcomes are relevant to current industry needs?
Quote and. Its not IP song, it is IPR support.
IPR support and engaging them to. Start up Udayam registration. And other incubation cell activities. So which motivates the students? To actively involved. In the given solution, the given real time. Solution building. So in this way I can uh. Do or improve the students? Abilities.
Now I need to confirm a few specific skills directly. Can you describe how you ensure your lectures are structured and communicate complex concepts in a way that students with varied backgrounds can understand?
You mentioned supporting students with IPR and startup incubation—can you give a concrete example of a student project that successfully transitioned to an incubation cell or startup, and describe your specific role in guiding that process?
One of my student. Have invented. Cybersecurity related product. Which is called AGNI C2. Her name is. Shakti Sri from. Final year. Btech IT student from Kingston Engineering College. So what I found is. Our project is very relevant and I found the novelty in a project. Uh, by analysing the. The title and under UPT. Abstract and some of the keywords. Using the keywords I have searched. With the. WIPO. And Google patents. For the novelty, check. 1st the initial stages started with the novelty check. Then after that. I have proceed. Proceed with the. Forms. That is technical description. So I guided. To develop our. Research work, that is. The Acme situ is. Cybersecurity related product. Which gives educational environment. That is. It provides. Both attack and defend. System in a virtual environment. There is no need of. Physical system. For testing of that. Cybersecurity attacks as well as the defund. So it is our idea. So I I I insisted our. To develop this idea. And we've filed a patent for this one. That is got published also.
Interesting example. When mentoring the student through the patent filing and incubation process for AGNI C2, what specific challenges did you and your student face in translating the prototype into a deployable product, and how did you address those challenges?
So in the technical description, I insisted. To develop the backgrounds. Or to search about the background of the study. 1st so I have included that background study. With the literature and existing market product analysis, everything we have did and. Uh conducted uh literature review. And constructed the background of the worker. Then we have moved with the. Uh, description of the innovations. It is like that innovation, uh. Based on uh. Novelty. Inventive step. Uh, theoretical. Uh, application. Sorry, industrial applications. Then relevant to the. Publics.
Thank you for sharing those details about AGNI C2 and your guidance through novelty checks and patent filing. During the literature review and market analysis phase, what criteria did you use to determine whether the project had sufficient novelty and commercial potential to justify moving forward with IPR and incubation support?
Public relevant to the. Public usage. So based on this four. Parameters we have developed are. Innovation work. Then I will proceed with the. Diagrammatic representations of this one. And detailed diagrammatic representation and. We have developed this software using Gallery Linux. Kali Nilitz.
It is not gallery, it is Kalinin X.
You mentioned using Kali Linux for software development—what specific technical hurdles did your team encounter integrating the AGNI C2 product’s attack and defense components in a virtual environment, and how did you help them resolve those?
Thanks for clarifying the technical process. During your patent development with Kali Linux, how did you and your student validate the accuracy and security of the virtual environment simulations—did you use any specific testing protocols or third-party tools to ensure robustness?
Kali. Linux Kali Linux.
Thanks for clarifying. During your work with Kali Linux on the AGNI C2 project, what specific steps did you take to document the architecture and ensure reproducibility for future student teams or potential industry collaborators?
The student. Towards the IPR technique.
Understood. Given your experience guiding students like Shakti Sri through the full patent process, how do you adapt your mentoring approach for students who initially lack confidence or exposure to IPR and innovation activities?
First, I will motivate them. And increasingly positively so. There are. I'm working in mostly the rural environment. So those students are really talented. But lag in communication skill first. Uh, so I will, uh, insist them to improve their communication. To come up with the best solutions and I encourage them to participate in many. Akathan's works. And conferences. So through this they can improve, they can gain some. Confidence. So after that I encourage them to. Do some. Worked under. I proceeded with them with the IBR work and incubation cell and slowly I bring them to. Research.
Right, so when you encourage rural students to participate in hackathons and conferences to build confidence, can you share a specific example where a student's communication skills improved noticeably through such participation, and how that impacted their research or project outcomes?
Initially, she is. Low confident girl only so I increased our. To get participate in VIP conference. So. Through the stick and gain some confidence over. Her work, then she she got second place in. Many hackathons also so conducted by the university. And nearby colleges. Then. I I asked her to apply IITM. Summer internship program. Because I went for the Saturday development program. Selected as top 25 from nationalwide. Using that opportunity. I have talked with the. Professors and I get a. Introduced about Shakti to them because she's also worked in a cyber security and Sai *. IITM is. Mainly for operating in cybersecurity only. So I identify this Shakti's talent and introduce them. Uh, to work in the internship projects through to. When she applied that internship project and she got now she worked in a intern intern. Intern in IATM. Size *.
Thanks for explaining how you facilitated Shakti Sri’s introduction to the IITM internship—what tangible changes did you notice in her research output or technical presentations after she completed that experience?
Yes, now she's. Very interested about the cybersecurity. And she's well. Trained in UH. ML Security. As well as the.
You mentioned she's now trained in machine learning security—can you describe a specific project or paper she produced post-internship that demonstrates this new expertise?
Many she can able to deliver. Many workshops as a resource person now.
You mentioned she now delivers workshops as a resource person—can you share how you evaluate her effectiveness in teaching technical content to her peers or juniors?
I have. I have arranged a workshop for my students under the incubation cell. And as the alumni talk. I engaged her as a resource person. To deliver about the introduction about the cybersecurity and. The Pentathlon, 2026. Cybersecurity com competition. Uh, conducted by the. Ministry of Metis.
Interesting. When Shakti delivered the alumni talk and cybersecurity workshop, what specific feedback or metrics did you use to measure how well the participants understood and engaged with the material she presented?
First, she's explained our project Agni C2. Which is which is mainly for the educational purpose, so through which she started her. Explanation. And uh. Umm, slowly she's getting into our.
Okay. When you observed the audience during her workshop, did you notice any particular questions or discussions that indicated the students were able to grasp advanced cybersecurity concepts because of her explanation?
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