Good day, Dr. G. Gomathy. 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?

Facebook.

For this interview, we must stay focused on your professional journey in academia. Could you briefly describe your academic background and experiences?

Good evening Sir, I'm Doctor Gomathi having 20 years of teaching experience in Electrical and Electronics engineering department and I'm completed my PhD in Power management technique for inverter based wireless Enzo network system. My core expertise includes power electronics, control system, circuit theory, measurements and instrumentation and electromagnetic pills. I have guided several undergraduate and postgraduate projects and actively involve students.

Research Oriented Learning I have published research papers in international journals and conferences, and I have also served as a coordinator for NAC and NBA activities, contributing to outcome based education and accreditation processes.

I am keen to integrate.

A-based optimization techniques in the power and energy systems research, which aligns well with Vrts interdisciplinary research vision. If given me an opportunity at VIT, I'll contribute effectively to students development, research output, and institution growth.

Thank you for sharing your academic journey and aspirations, Professor. It’s good to hear about your solid experience and focus areas. Allow me a moment.

Dr. Gomathy, I have your background in view now. Let us proceed to evaluate the essential skills. First, could you explain your academic and research experience in power electronics, power systems, or control systems? Specifically, highlight how your expertise aligns with these areas.

Actually, my PH3 research addresses the critical problem of high power energy consumption in embarrassed system based on a sensor network nodes HOD typically battery-powered and deployed in remote locations where battery replacement is difficult. To solve those, I developed a comprehensive power management framework that combines duty cycling, low-power forward design, dynamic voltage and frequency scaling energy-efficient communication protocol.

Sleep scheduling and data reduction technique. These things combines in interdisciplinary activities, that is, it's combined power electronics, power system and control system area. I also explored the integration of energy harvesting to further extended node lifetime. The outcome of my workers a significant reduction in power consumption leading to increased node lifetime and improved network reliability.

Uh, for example, when you're going for power management techniques, it's, it's coming under power system and here, uh, I'm going to improve the, uh, network lifetime, network lifetime. So, uh, actually, if you're using network, we are using thousands of notes. It should be deployed in the remote place. So for each and every node, it should be operated by a battery.

So it is very difficult to change the battery often, so to avoid that.

So we have to reduce the power consumption and as well as we have to increase the network lifetime. So I'm going for some power management already. I said no. So. So by using that power management technique I am I'm reducing the power consumption and increasing network lifetime. So by this method I can implement all these things by using that is in future by using. That is by using AI.

Uh, research what in uh, very good in uh control system as well as by using Baltronics application.

88 technology I can implement this.

At VIP this is.

Thank you, Professor. It’s clear that your research bridges several critical domains: power electronics, power systems, and control systems. You’ve addressed a significant real-world issue with advancements in power management, particularly with sensor networks and low-energy designs, which is commendable. Let’s touch on another area. Can you share how you approach teaching both theory and laboratory courses? Specifically, how do you ensure that students grasp not only fundamental principles but also develop the practical skills they need?

Uh, see actually when you're going for power stem analysis, by using MATLAB and Simulink software, I can implement all the things. It is very easy to explain students by using simulation software already. I said no, that is by using MATLAB and assuming and by ETAP method, I can explain the power system and as well as where the fault is occurring. And we can identify the fault by using simulation software in similarly for control system also.

We can find out the, that is, we can find out the, uh, what is that, uh, how the loop is, that is how the feedback is connected and you're and how we are getting the desired output by using some more tasks. So all these things, it should be connect. That is, it should be simulated by using simulation software, that is for by using MATAP software, simulate or protease software method and method and all, we can get the proper result.

Your integration of simulation tools like MATLAB, Simulink, ETAP, and Proteus into teaching is an effective approach. It is vital for students to visualize concepts and connect theoretical frameworks with real-world applications. This method definitely strengthens their understanding and skills. Next, could you elaborate on your approach to student evaluations? Specifically, how do you design assessments—both exams and continuous evaluations—to measure both theoretical knowledge and practical competencies?

Yeah, uh, actually, uh, for, uh, for, uh, by giving guidance to the students, for example, uh, if the students who are very slow learners, I have to find out the data from the assessment. So from that I can find out the slow learners list. So from them, I have to give the by contacting some extra, extra classes and by conducting some tutorial lovers for them and as well as by.

Getting that is for example some practical session session and as well as by guiding some simple example and real-time application oriented, I can explain the students in very good manner. So automatically they will get idea and they will improve in their subject. If you are, if you are taking fast learners for fast learners, we have to.

That is research publications and by attending some quiz programs and paper presentation seminars to attend seminars and workshops. So by using these techniques they can improve their subject knowledge automatically. They will reverse the in the subject. So in this manner we can improve the students feedback.

Give us some mini projects and by by guiding some.

Your differentiated approach to student evaluations and development is noteworthy—identifying slow learners, providing them with additional support through tutorials and practical sessions, and encouraging fast learners with advanced opportunities like mini-projects, research guidance, and participation in academic events. This reflects a well-rounded and thoughtful pedagogy. Now, could you describe your experience guiding student projects and research? How do you mentor students to ensure not only timely completion but also academic and technical rigor?

Actually, I'm going to alot some time schedule for each and every work. First, I'm going to allow the allow the time period for project. For example, I'm going to guide some research project for students. Initially, I have to frame all the things that is, I'm going to fix the time schedule for each and every student. That means first initially I have extensive experience guiding students through both academic projects and. Introducing some research work.

And at the beginning of any project, I help students clearly define the problem statement, objectives and expected outcome.

And to ensure timely completion, I break projects into well defined milestone with realistic deadline and conduct periodic review meetings. These checkpoints allow me to access. Access progress, address technical challenges yearly, and guide students towards better design choice or methodological correction when needed.

From a technical perspective, I mentor students in writing clean, well documented code, validating results, and following ethical research practical such as proper citation and avoidance of plagiarism. I also encourage critical thinking by asking students to justify their assumption, interpret results meaningfully, and reflect on limitations and future scope for.

UH motivated and fast learner, I extend mentoring behind and coursework by introducing mini project, research oriented problem statement, paper reading session and guidance on presenting their work in seminars or academic events. Overall, my goal is uh not just project completion, but helping students to develop confidence, independence and strong foundation for future academic or industry work.

Your structured and comprehensive approach to guiding student projects and research underscores a strong commitment to their academic and technical development. Breaking down projects into milestones, conducting regular reviews, emphasizing ethical research, and fostering critical thinking—these practices reflect a robust mentorship philosophy that breeds both confidence and competence in students. Turning now to another critical element—communication and teaching methods: How do you ensure your style of conveying information resonates with students of varied learning abilities and keeps them engaged in both classroom and laboratory settings?

Is uh, uh, Sir, actually, can you repeat the question I'm not getting?

Uh, sorry.

I believe it.

No problem,

Yes, yes. So.

Please take your time, Professor.

Uh, I did.

OK, OK, Sir. Uh, actually I believe effective communication, Liza, the heart of success teaching especially in classroom.

It diverse learning abilities to ensure my teaching, uh resonance with all students. I adopt A blended and adaptive communication style that combines clarity, interaction, and real-world, uh relevance in the classroom. I structure concepts programsively, starting with fundamental ideas and gradually moving towards more complex applications. I use multiple modes of explanation including visual aids, real time analog, analog analogies.

Demonstration and short discussion so that students with different learning preference can graphs the material effectively. I also encourage questions and brief peer interaction to create an inclusive and participatory learning environment. To keep the students engaged, I frequently check for understanding through quick questions, problem solving activities, or concept recap session. This allows me to adjust the.

UH base or revise topics when necessary, ensuring no students feels left behind while still challenging advanced learners in laboratory and practical situation. My focus shifts towards and on learning and guided discovery. High demands rate procedures. Clearly explain the UH rational behind each step and then encourage students to explore, troubleshoot independently. Offerings support as needed.

This approach builds confidence, reinforce theoretical concepts, and promotes experiential learning.

Across both settings, I emphasize approachability and open communication, encouraging students to seek clarification without assistation. By maintaining A supportive and encouraging teaching style, I aim to foster curiosity, sustained attention, and a deeper understanding of the subject matter among students of varying abilities.

Your adaptive teaching style—blending structured progression, diverse learning aids, and interactive elements—demonstrates a thoughtful commitment to inclusivity and engagement. By fostering curiosity and confidence, especially through guided discovery in laboratories, you exemplify the attributes of an effective educator. Now, turning to your academic qualifications, you hold a Ph.D. in a relevant specialization. Could you briefly share how your doctoral research has prepared you for this role, specifically in contributing to advanced teaching and research initiatives?

Uh, actually I have completed my uh, research work in the field of power management technique for embodied system based wireless Enzo network node. So in this case, I'm facing many challenges initially, actually, uh, the power consumption is very high, uh, by using embedder system in uh, existing, that is in previous method.

So so to. To rectify that fault I'm going some some concepts like that is I'm using some power management techniques I'm using that is. I'm going for a low power system hardware design and energy efficient system protocol and then by using time scheduling, that is scheduling timing that is duty cycling and using duty cycling in the sense whenever we need we can turn on the device whenever we don't want, the device should be.

The goes to uh. That is uh. It should be goes in uh sleep mode. So by using that technique, I can that is uh I can go for I can improve the power management of battery as well as I can increase the lifetime.

In my research address the critical problem of high energy consumption in embodied system-based wireless enzyme network nodes, which are typically battery powered and deployed in remote location where battery replacement is difficult.

To so to solve this, I developed a comprehensive power management framework that is due to cycling, low power hardware design and dynamic voltage and frequency scaling, energy-efficient communication protocol and sleep scheduling and.

I can reduce the power consumption and I can increase the network lifetime. I also explored the integration of energy or wasting to further extended node lifetime.

That is, what is that voltage scaling and voltage voltage frequency scaling energy efficient communication protocol by using these techniques?

The outcome of work is significant reduction in power consumption leading to increased node lifetime and improved network reliability. So in this research, I can be extended into funded projects by incorporating incorporating Ai-based prediction and optimization techniques for adaptive power management in IoT enabled sensor networks. This aligns well with funding opportunities from DST Shop and Smart Energy Research.

Initiatives by using some government organization as well as by using some private organization.

Your doctoral research has clearly addressed a significant challenge in wireless sensor networks, and the proposed power management framework showcases a deep technical understanding. Incorporating AI for adaptive power management and aligning with potential funded projects reveals both academic depth and practical foresight—qualities that will undoubtedly contribute to advanced teaching and research initiatives. Let us now focus on research publications. Could you elaborate on your contributions to reputed journals, particularly discussing any impactful findings or methodologies you've shared?

Uh, Sir, actually in my research work I'm using.

Duty cycling.

That methodology.

Duty scheduling I'm using. So in this duty scheduling technique the the node it should be that is the device. It should be operated in two modes 1 is active mode and another one is a sleep mode. When you're going for active mode, whenever the node it should be on that is the whenever the node it should be getting data. So that time only the corresponding node should be on condition otherwise it should go to sleep. Sleep state to conserve power while maintaining.

Sir.

I actually I'm using duty.

Performance and instead of keeping all notes active all the time, duty scheduling Ensure that only a necessary subset of nodes is active at at any moment. Other nodes remain in low power sleep mode, so network coverage, connectivity, and data reliability are still preserved. Common duty cycling techniques. Static duty cycling.

So in this static duty cycling pixel sleep and wake scheduling. Simple to implement and less adaptable to changing network conditions.

Example for example node wakes every 10 seconds the wise sleep, otherwise it will go to sleep mode. And next one is dynamic adoptive duty scheduling duty cycle adjust based on traffic loads, residual energy or environment and more energy efficient and responsive. Responsive.

So in this case, the example notes stay awake longer during high event activity and then randomized data share duty scheduling. So in this randomized duty scheduling, notes wake up randomly based on probability reduces synchronization, hover it and it is useful in dense networks and coverage based duty cycling. Only notes required to maintain sensing coverage stay active and written notes or put to sleep and.

Extensions Network.

Class time significantly. Next one is cluster based duty scheduling. So in cluster based duty scheduling cluster heads stay active longer. Member notes follow scheduled communications clause and it is common in protocols. Likely it's protocols and AI assisted intelligent duty scheduling. Also we can go by using that users machine learning or reinforcement learning. We can go for predicts.

Optimize sleeps vacation dynamically. So the key benefit of my research workers extends network lifetime and reduces energy consumption and improve scalability and maintain quality of service. And the total performance metrics is network lifetime, energy consumption latency, packet delivery ratio and coverage ratio.

Traffic and events or energy trains?

Your detailed discussion highlights significant advancements in duty cycling methodologies. The depth of your research—spanning from static to AI-assisted scheduling—clearly reflects your substantial contributions to the field. Furthermore, addressing parameters like network lifetime, energy consumption, and scalability underscores the practical impact of your findings. Lastly, could you elaborate on your experience with industry projects or consultancy? Specifically, what challenges have you encountered, and how have you contributed to solving real-world problems through your expertise?

Umm see actually, umm, by using, uh, real time, that is uh, uh. My experience with industry oriented projects and consultancy as a primarily involved applying academic research principles to solve practical real-world problems, particularly in areas related to networking, embarrassed systems, and intelligent system design. Those engagement have strengthened my ability to bridge the gap between.

Theoretical models and deployable solutions One of the key challenges I have encountered in industry projects is balancing performance requirements with real-world constraints such as limited power availability, cost sensitivity, scalability, and deployment feasibility. Unlike controlled academic environment, industry problems often involve. Incomplete data.

Uh, tight timeline and uh, evolving specifications addressing these challenges required adoptive problem solving and close collaboration with multidisciplinary terms. My contribution typically begins with problem analysis and requirement mapping and followed by proposing technically sound and cost-effective solutions. And I was able to design solution that improved system reliability and resource.

Utilization without significantly increasing complexity. I also focused on validating solution through simulations, prototyping or pilot testing to ensure practical viability.

In consultancy role, I have supported organizations by offering technical guidance, feasibility assessment.

And performance optimization strategy. I also assisted teams in understanding emerging technologies and aligning system design with long-term scalability and sustainability goals. Importantly, these experiences have informed my teaching and research by providing real case studies, industry-releven problems statements, and. Pragmatic perspective that I actively integrate into the classroom.

Overall, my industry and consultancy experience has enhanced by ability to deliver application revenue, researcher, mentor students with industry, align skills, and contribute meaningfully to collaborative projects that address real social and technological challenges.

Your industry and consultancy experience highlights your ability to extend academic research into practical, real-world applications. Your approach to balancing performance with constraints like power, scalability, and cost is commendable, as is your emphasis on pragmatic problem solving and multidisciplinary collaboration. Additionally, the integration of these experiences into teaching and research demonstrates your strong adaptability and relevance as an academic professional. At this stage, I have completed verifying the essential skills required for this role. Allow me a moment.

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

Professor, to begin, could you describe a specific setting or teaching method you find particularly effective in engaging students with complex material in your field?

Uh, no queries. Uh, nothing, Sir.

Understood. Professor, let's proceed. Could you share a foundational course within your discipline that you find rewarding to teach, and why?

MMM.

And uh.

Whenever

Yeah, uh, within, uh, my discipline, I find, uh, topics related to energy efficient communication system and intelligent network design practic particularly rewarding to teach these areas naturally bridge theory and practice, allowing students to see how fundamental concepts such as algorithm optimization and system modeling translate into real-world application. Umm. And what makes these topics especially engaged?

Is there a relevance to current technologies like IoT, smart environment, and sustainable computing? Students are often motivated when they understand how they are learning connects to real societies and technological challenges, and teaching these subjects also allows me to incorporate recent research findings. Case studies and end zone experiments, which keeps the classroom dynamic and encourage.

Um, iniquity driven learning.

Thank you, Professor. That's an excellent approach, combining practical relevance with cutting-edge research to foster curiosity-driven learning. It demonstrates both pedagogical depth and an ability to inspire students. Let’s continue.

Dr. Gomathy, I see from your record that you have been engaged in significant research, including your doctoral work on "Power Management Technique for Embedded System based WSN Node" and postgraduate work on "Novel Loss Reduction PWM Technique for Brushless DC Motor fed by MOSFET Inverter." Let us delve deeper into these topics. Could you start by providing an overview of your doctoral research? Specifically, how does it contribute to advancements in the domain of power management for embedded systems?

In uh, power management technique for Amber, system-based wireless sensor network plays a significant roles in interdisciplinary collaboration and uh, this optimizing energy consumption. These techniques enable efficient communication, data aggregation, routing topologies, uh, fostering collaboration across fields like computer science, electronics and communication engineering.

And, umm.

Go ahead, Dr. Gomathy. Was there something more you'd like to add?

Nothing, Sir.

Understood. Building on that, could you elaborate on how you balanced theoretical research with practical application in this project? Specifically, were there any real-world systems or experimental setups involved in validating your findings?

I uh that bridge theory with practice. I Val validated the proposed approach through expansive simulation based experiments that closely, umm, mirrored real-world operating conditions. The simulation environment was designed to reflect practical constraints such as limited node energy, variable traffic patterns, communication overhead, and network scalability.

And a standard performance.

Metrics such as network lifetime, energy consumption, latency and throughput we're used to ensure meaningful evaluation. In addition, I align the system assumption with these of the real wireless sensor network deployment, including realistic radio models, snow density variations and failure scenarios where possible across.