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Please start by introducing your professional journey in academia.

Thanks for letting me know. Please begin by introducing your professional journey in academia.

I have totally 18 years of teaching experience. I have worked in four colleges earlier. One is Mohan Babu University. That is in. Tirupati for 10 years. And one more year. At Mallardi Engineering College in Hyderabad. Under gates Institute of Technology for. Half semester.

Then I moved to G Narayanam instead of technology and science. And I have. Five and half years experience at my genius.

Thanks for sharing that. During your decade at Mohan Babu University, can you describe a specific initiative or project you led that had a notable impact on your department or students?

You’ve worked in a range of academic settings. Which foundational course in your field do you find most effective for engaging new students, and what draws you to teach that particular subject?

I I thought almost all data science allied subjects like database management systems. Distributed databases. Data warehousing, Data mining, data visualization. Data science using or. Then other subjects like. Programming for problem solving using C language. Then data structures. Then information retrieval systems.

Software engineering, software project management, Software testing.

Dr., I see you have several publications on machine learning in healthcare, such as your work on early detection of heart and diabetes using deep learning. How do you translate the findings and methods from this research into your classroom instruction for undergraduate or postgraduate students?

And other subjects. Out of uh. 18 years.

You mentioned teaching data science subjects like data warehousing and data mining—can you give a concrete example of how you’ve incorporated a recent research development or industry trend into your classroom instruction for these courses?

Then I have taught 4 subjects. For PG students. Which are. Software calls Azure and testing. Under Software Process and Project Management. In the M tech specialization with the software engine.

You mentioned teaching subjects like data visualization and information retrieval systems—can you describe a specific classroom project or assignment you've designed that helps students connect theoretical concepts to practical applications in these areas?

You mentioned teaching software project management to both undergraduate and postgraduate students—can you describe a particular project or exercise you assign that helps students understand real-world software development challenges?

And I did my PhD in data mining. Which is in Jain to a Anantapur. Andhra Pradesh in 2000. 17. And I have post PhD. Nine years. This is my 10th year of post PhD out of 18 years teaching experience. I did my B.Tech in uh. S3 University College of Engineering, which is main campus. Located at Tirupati in 2005. And did my memtech through gate qualification. And so we dedicate an engineering caller located at Tirupati and. I'm the gold medal for my batch, gold medalist for my batch. And after that I moved to PhD in a government university which is into Anantapur. I got an opportunity then I. In 2009 I was registered and. I have completed my PhD in 2000. 17. September. After that. Uh, I have entered into the research field data mining. I will move on to. Moved on to the data science and the data Analytics area. So my PHP. Area is. Spatial data mining, which is. Effective. Mining of. Frequent and maximal periodic patterns in spatiotemporal databases for shifted instances. So I have proposed 3 algorithms. And I have compared with all existing algorithms in terms of scalability and execution time. I got good results and I was awarded PhD in 2000. So in my career I have. Four DST projects, I mean 4 research projects. One of them is DST Serb. EMUQ project with the cost of 18,69,000. 2, not 8. Now it is a. It is valid for three years. And two years already completed just now. Recently I have submitted my UC and. Statement of expenditure and progress report for my second year. Then I have one more year to complete that DST project. Funded a project. On diabetes and heart attack disease detection using machine learning and deep learning areas. Then. Earlier I have conducted one AACP. UH sponsored a conference with the cost of three-point 5,00,000. I have conducted in genetics in 2022. And all the. Conference papers are published in Springer. ******* series. And all are Web of Science indexed. Currently. To my research I have.

Some 1624 journal publication out of that.

Your PhD work on mining frequent and maximal periodic patterns in spatiotemporal databases sounds technically demanding. Can you walk me through one of the algorithms you developed—specifically, how you addressed scalability when working with large real-world datasets?

You mentioned leading a DST SERB-funded project on disease detection using machine learning and deep learning—can you describe a specific technical challenge your team faced during this project and how you addressed it?

I was a resource person for many colleges in the data analytics and machine learning and data. Mining areas. And currently I am doing research in. Heart attack and diabetes prediction using deep learning and machine learning algorithms.

You mentioned you’ve published textbooks and book chapters—can you describe how you integrate material from your own publications into your teaching, and how students typically respond to learning from resources you’ve authored?

So this is my. Entire brief. Brief profile of.

My ratio under CV. Thank you for giving this opportunity.

You mentioned your current research on heart attack and diabetes prediction using deep learning and machine learning algorithms—can you walk me through how you select and preprocess clinical data for these models, particularly with respect to handling missing or inconsistent records?

Thank you for the detailed overview. You mentioned your research on mining frequent and maximal periodic patterns in spatiotemporal databases—can you explain how you would translate some of those core algorithmic concepts into an undergraduate classroom exercise to help students grasp the principles?

That is that extended frequent pattern mining algorithms. And one more algorithm I have proposed. That is ETMA enhanced retaining algorithms. These two are actually. Performing well on Uddag which is up. A DAG based approach. Directed acyclic graph based approaches. Then if you want to run the. Algorithm if you want to run the. Algorithm on the data sets. Of forest fire prevention and other. Location and time oriented datasets. So, uh. We can extend still the research to improve the. Results to improve the predictions. Whether how much land? We can save in the forest to prevent the forest fights.

So I will explain to the students. Those projects in classes whenever required. Are in the middle of the discussions so that students also can propose. There I won algorithms in their. Academic projects. And I will support them. Towards this particular domain research. To get good publications or. To complete their PG PHP degrees. And all and I will also guide them. In terms of outcomes like patent and you know. Any project Expo, any collaborative research by the industries. So I will be ready to act as a mentor for them. In this particular area.

You referenced using DAG-based algorithms for forest fire data—how do you balance teaching the theoretical underpinnings of directed acyclic graphs with giving students practical, hands-on experience in your courses?

Thank you, Professor. Let’s discuss your research productivity and funding. Please outline your three-year research roadmap—specifically, what major research themes will you pursue, and how do you plan to secure sustained external funding to support your work?

The first research Cheryl, I will mention is data science in healthcare or AI in healthcare. Under machine learning in healthcare. So all these three areas. Nowadays. Will help us to give better results in. Short time. By without writing much coding actually. So all the machine learning ensemble classifiers and deep learning classifiers are. Available. To use the pre. Pre trained models to. Give better results like accuracy will be more. On the collected live data sets.

So already I have one DST Servo funded project. So after completion of that I am planning to. Show the demo. In the form of a. What is that mobile app? In that I can. I can connect directly to a data set. Then my algorithms will run on it and. My framework will give you fast result like. How much risk will be there for a heart attack and diabetic patients? In advance. To save the lifetime of the patients. The same thing I will. Give the motivation to the students. And let them continue their research on this area.

You emphasized using pre-trained machine learning and deep learning models for healthcare datasets—how do you plan to distinguish your research outputs in such a crowded field, and what is your approach to demonstrating novelty for grant agencies?

You mentioned developing a mobile app to demonstrate your algorithms—what is your plan for sustaining external funding after your current DST project concludes, particularly in terms of targeting industry partnerships or new grant opportunities?

Once I develop the. Mobile application. Then students and the faculty mentors like me. We will work together. To give more extensions of that. Mobile application. Where it will be very flexible for the people nowadays to interact with the mobile. And giving the parameters like health parameters. Like BP, BP, sugar, BMI. Their weight and other parameters it will take and it will give us. How much risk we? So we can. Send this application to various. Diseases and we can do. Extensive research in this area. By using machine learning and deep learning approaches. Nowadays we have almost all open AI tools are there. Will we can use them to simplify our regular task and we can. Contribute some algorithms or models and web applications.

To give the better results for the societal problem.

Let’s shift to your teaching approach. Imagine you are assigned a large-enrollment undergraduate course in data science, but you are not allowed to use traditional slide-based lectures. Describe in detail how you would implement an active learning model—such as a flipped classroom or peer-instruction—for this course, ensuring student engagement and concept mastery.

Understood. Can you explain your experience in student evaluation processes, and how you would ensure fairness and accuracy while assessing diverse learner abilities in courses at VIT University?

Yeah, usually students will come from different States and different. Backgrounds. We have to teach the concepts according to the student levels. And we have to teach the topic. In terms of average. The slow learner and fast leadness point of view. And all the students are having equal learning capabilities. We have to teach the topic to reach. Into their levels. Nowadays, the students certificate learning is more important than teacher-centric and NEP 2020 and AACT model curriculum and other. SDG's like Sustainable Development Goals are also there. Everything we have to teach to the. Uh, social impact that will be having social impact in the. Uh, classroom environment. So. I will teach the class. For every class I feel that it will be a. Uh, fresh class for me and everything should be. A student centric, learning oriented, but not one way or. Teaching centric. Oriented. Yeah, that's it. Thank you.

Let’s discuss your approach to institutional stewardship. Suppose your department is aiming to improve its “research per faculty” metric for the next accreditation cycle. What systematic steps would you implement to achieve measurable progress on this front?

Yeah, to improve the research. For faculty we have to create some awareness session like research methodology. Then calling some industry or research principal scientists or academia. Some professors. From academia we have we have to invite them like IIT, NITS and other deemed central universities. To give us some motivation, lectures towards the research. Like research is not nowadays. Is optional. You can say that it is a mandatory in academia. To improve our teaching skills and research skills. And also. We have to. Yeah, motivate the faculty by creating awareness session for them and. Collaborative research with other faculty members in the department. And making clusters in the department or clubs in the department. And collaborative work with them establishing research centers. And students formation. With the mentor formations. And a collaboratively if they do in the labs, R&D labs. Better outcome we can produce.

You mentioned forming research clusters and collaborative labs—what concrete strategies would you use to ensure that these groups consistently produce quality publications, rather than just forming in name only?

Yeah. So after forming the research clusters every three months once or six months once our monthly ones, we have to conduct the meetings and give the targets to them. And they track the progress monthly or quarterly. With them. And have some group discussions. Have some. The Radical progress meetings with them. And on particular problem or a group of problems. Then one particular period of time we will get definitely the. A good outcome in terms of a publication, in terms of a conference publication or in terms of a patent. Or in terms of any project Expo. Or at least in terms of. And their academic projects. Also we can convert with. Some industry mentorship like that. So we can, uh. Improve the research work. By mentoring the.

Research cluster members frequently. By monitoring. Thank you.

Let's turn to a scenario involving academic integrity. Imagine you receive a formal complaint that your grading decisions are biased, but at the same time, the institution is pressuring you to meet a specific pass-percentage target for your course. How would you resolve this conflict while upholding fairness and professional standards?

Let’s talk about bridging academia and industry. Describe a concrete strategy you would use to leverage your professional and research network to create new internship or employment opportunities for students in your department.

So to bridge the gap between an industry and academia, first of all. The industry oriented guest Lexus to be conducted. The industry oriented hands-on session to be conducted. And what are the?

Job oriented courses in industry. Those courses based on that. We have to arrange the sessions for student. Especially theoretical session we have to avoid only. Hand sanitation we have to plan. For three to four days and the last day we have to conduct hackathon for two days. Continuously encouraging the students in participating of hackathons. And calling the industry people to evaluate their projects are. Inviting the industry people to act as men. Mentors. In our academic projects. Then when the people are writing proposals. Like students and faculty as a team, then inviting them. Uh, industry people in the evaluation process of the. Projects. That will be better. So under any publication also if they are doing. Then calling the industry persons also. Collaboratively, if they do publication, it will be better.

Now I’d like to verify your depth in a few specific areas required for this role. First, can you walk me through how you have applied multimedia or artificial intelligence techniques in media-related research or teaching contexts?

So like that we can fill the gap between Academy and industry and. We have to conduct the placement training classes for. Each and every student like second year, third year and final year. Of their UG and PG and PhD. Times.

You mentioned inviting industry professionals as mentors and evaluators—can you share a specific example of how you facilitated an industry collaboration that resulted in direct internship or placement offers for your students?

You mentioned organizing hackathons and inviting industry mentors—can you describe a time when this approach directly led to a student securing an internship or job placement?

Yeah, so if you call the industry people in for hackathons as judges are some mentors. So they will identify maybe if they like our student problems or student academic projects. Maybe they are ready to invest the amount. To continue the students projects. To get some deliverable outcome or market viable product. That is 1. Uh, feasibility where? Students can directly get into the. Product-based companies. If they give any opportunity for the students. Definitely. There will be a there. There are more chances to get internship opportunities by the. In the by the industry people in industries. For the students. If we are having connection with them frequently. And involving them more in the academic. Works.

Right. When you involve industry professionals in student evaluations or project assessments, how do you ensure the process remains objective and aligned with academic standards?

Yeah, when we call the industry professionals in the student evaluation projects, we have to consider. Novelty. Then presentations. Then question and answers. Then technology they used. So like that we have to divide like 4 to 5 parameters.

So society relevant application also one of the parameters then. How well they have explained within a short time how? Well, they have prepared. Like that some parameters we have to decide, we can call that one as rubrics. Based on rubrics. We can evaluate all the. The industrial people can evaluate the projects. Where academic people also will be there, but. More. Involvement and final judgment will be by the. Industry people because they are only in future. Giving the internship opportunities for the. Students. So in this way. We can evaluate student projects. But not like for just the namesake conduction is not. We have to follow some rubrics for every project evaluation.

You mentioned using 4 to 5 parameters like novelty, presentation, and technology—how do you ensure consistency in the way these parameters are applied when different industry professionals are involved in the assessment?

Understood. When industry professionals and academics are both involved in evaluating student projects but may have different expectations or standards, how do you resolve disagreements or ensure a fair outcome for the student?

Yeah, during project guidance, during project with the students. We have to feel first.

Okay. Can you give a specific example of a disagreement between an industry evaluator and an academic regarding a student project, and describe how you facilitated a resolution?

The AIR project is our project. And we have to involve. Frequently.

The project guiding. Like, you know.

How do you approach situations where a student project falls short of both industry and academic expectations—what steps do you take to guide the student toward a more successful outcome?

Each and every. Moment we have to spend some. Miserable or reasonable time with them? But not like in Haraveri situations. So we have to. Spend some time with them very clearly. And patiently we have to explain. The interestingness. We have to create. For the students. And we have to motivate with the. Problem statement and research questions First we have to give them. And do some proper survey. After doing proper survey. Then only the people will be uh. Ready to identify the problem? So we have to have, we have to sit with them. Patiently. For a long period of time during the project. Guidance otherwise. Getting outcome is very different. Under to avoid any miscommunication misconceptions. So better to. Meet with different meetings periodically. To improve the error. Project Guideship. Then only students will be interested. We have to sit with them. We have to. Create interest in the project. Implementation.

You mentioned frequent involvement and a sense of ownership in guiding student projects—can you give a concrete example where this approach helped mediate a disagreement between evaluators and resulted in a fair resolution?

As per my knowledge.

You emphasized patient, frequent meetings during project guidance—can you describe a time when this approach helped a struggling student turn their project around and achieve a publishable result?

You emphasized the importance of regular, patient mentorship during project guidance—can you share a specific instance where this approach directly resulted in a student’s project being accepted for publication or winning recognition?

This is my. 18th year of. Experience in the teaching community.

When I started my career in 2008 as a faculty. In each and every year. I have worked. Almost with. Many students. Frequently.

With your 18 years of experience, can you point to a particular student project where your hands-on mentorship directly resulted in a journal publication or award, and briefly describe what you did differently in that case?

So almost out of 24 general publications and. 16 conference publications.

You mentioned working with many students over 18 years—can you describe how you structure your evaluation process for student exams to ensure fairness and consistency across such a large group?

You mentioned having 24 journal and 16 conference publications—can you walk me through your process for selecting which student projects have the potential for publication, and what specific criteria you look for before moving forward?

Most of the. Proplications are uh. With the students only. So if. We guide them properly. Students are.

Students, they will submit the paper. They will publish the papers. The refuted journals and conferences.

Given that most of your publications are with students, what specific strategies do you use to identify which student projects have strong potential for publication, and how early in the process do you make that determination?

So especially there is more scope if you guide the PG projects and PhD projects.

You mentioned that most of your publications are with students—can you describe the steps you take to ensure students are actively involved in the research and writing process, rather than just being listed as co-authors?

So publication. Our dressing is very easy because more results will be there. Uh, more mathematical formulas will be there in the PG and PhD. Projects because. They will spend. Years of time. To get a reasonable outcome when compared to UG students but.

You highlighted the importance of guiding PG and PhD projects for publication—when you mentor these advanced students, what specific role do you play in shaping their research questions and ensuring the work meets the standards of reputed journals?

Guiding UG students in a short period of time, maybe one year or one. Six months. So we have to. Carefully guide them by giving our publication as references. Are some top. Researchers Profiles. Giving to them and search for. Some good papers in their profiles. And top. Index databases like Scopus, Web of Science databases. Google Scholar like that? If we give correct resources to them, they will go. They will. Do good research. Indira Kalnik projects. So we have to.

Understood. You mentioned guiding both PG and PhD students over the years—can you describe a specific challenge you faced when evaluating a large number of student exam papers, and how you ensured your grading remained consistent and unbiased throughout?

Work with them patiently. I can say so in research outcome will not be there. In one day or one month or three months. Especially. This SCA and Cohen journals. So the work will be. One year, 2 year and publication also takes. One year, two years.

You mentioned using top index databases like Scopus and Web of Science to guide students—can you describe a time when a student initially struggled to find quality references, and what specific steps you took to help them improve their literature survey?

Right. You mentioned using your own publications as references for UG students—can you describe a time when this approach directly helped a student overcome a research obstacle or improve the quality of their final project?

Obviously, suppose if we are giving a project. For example, a in healthcare. Suppose if I give, what are the already healthcare problems and how they are solving? How they have? The literature survey has been done. How the results will be displayed? How the formulation? Mathematical formula to be represented. How to identify limitations? How how the problem statement? What we mentioned in the introduction How to write abstract in 150 or 100 to 150 words? What is the importance of keywords? How can we frame the title? So. With you know with all how to mention the references also. How to cite the references in the paper? Everything. Uh, we can explain easily.

Thanks for breaking that down. When guiding students through writing their first research papers, how do you ensure they develop their own research voice rather than simply mimicking the structure and wording of the references you provide?

With our. Published articles with the students. Then students can have more interest than. Other publications if I show. My own publication to them. So directly they can motivate and they can do accordingly. Their publication or. Project work. Definitely it will. Having a factor. For the students. To improve their research or to get a. Product or. Project Publication.

That’s clear. Given your experience guiding students through structuring their research papers, how do you balance providing detailed templates or examples with encouraging original analysis and critical thinking, especially for undergraduate projects?

Yeah, for undergraduate students, actually. Their IQ levels are very good. So students nowadays need. Very crispy and important information. In a short period of time with some interest, we have to create.

We have to create some motivation, interest with them. And then we have to give a. Some motivation for the students. Uh, towards the critical thinking. It's like a brainstorming session we have to conduct. How to solve a problem in different different ways? We have to conduct the sessions. Like. Giving a. Quiz are a puzzle problem. And invite a different. Solutions under one problem. So some critical thinking are brain charming session mind map techniques. So we have to. Give the awareness on that. So that students can have different approaches to solve a problem in different ways.

You mentioned the need to create interest quickly with undergraduates—can you give a concrete example of an activity or technique you’ve used to spark that engagement at the start of a new project?

On that, we have to spend much time on it. So in research methodology. Some uh.

Interesting approach. When you use techniques like brainstorming sessions or mind maps with undergraduates, how do you assess whether these activities actually improved their problem-solving or research skills over the course of the project?

Skills are there for a research scientist or. Research scholar, if he is a UG or PG or PhD doesn't matter. But we will. Have some brainstorming session for students like. Mind map techniques then how to do the survey? Then how to solve a problem different ways? What are the existing methods? How to identify your problem?

You described organizing brainstorming sessions and mind map techniques to foster critical thinking—can you share a specific example where these methods led to a student uncovering an unexpected solution or novel research direction?

So how to identify research question and all? How to divide a research into different objectives, solving each objective instead by step? And consolidating all them together. So like that initially some. Sessions are required. For them.

You mentioned teaching students how to conduct literature surveys and identify existing methods—can you walk me through a time when a student initially struggled to find relevant prior work, and how you specifically guided them to improve their search strategy?

You mentioned the importance of teaching students how to identify research questions and break them into objectives—can you share an example where a student initially framed their research question poorly, and how you guided them to refine it into something publishable?

Yeah, for example.

Understood. When a student’s initial question is too broad or vague, what concrete steps do you take to help them narrow it down and define clear, measurable research objectives?

Developing an automated web application for healthcare. So in this project, suppose if a student was struck with any one particular stage. Before publishing, we will guide them easily. How to represent the results in a paper? How to represent graphs and tables? How to write conclusion? How? The Journal. Editor will think. So what are the? What are the principles and formats given by the journal? The gaps in between publication or paper or. Raft documentation to the publication in that gap in. For that gap. We have to fill. With by giving instructions. Like arranging the paper into proper format then checking line by line. How the paper was written so any gap is there between the. The. Publication definitely with our guidance, with our research experience. With our research methodology skills. We'll guide them easily to get into the. Publication. If they are very poor. Publication. Definitely, I will act as a mentor for them.

Because almost my. More than 50% of my publications are with my students. UGPGNP. PJ and PG and some colleagues.

You mentioned acting as a mentor when students struggle with publication quality—can you describe a specific intervention you made that turned a weak draft into a publishable paper?

Understood. When you're mentoring a student whose draft is not meeting journal standards, what specific feedback do you prioritize in your initial review to help them make the biggest improvements?

Yeah, first of all, I. I have already mentioned that. To write a research article in SCIS corpus indexed free journals. First of all, we have to know. How to write a research article effectively? So each and every section we have some command. Our idea about. It may be starts from research title. Problem title and also abstract and also keywords and also introduction. Then survey, then implementation methodology. Graphs, tables, conclusions feature. References acknowledge. Citing citations. The number of authors. And the journal format single column or two column. Then review time. When each stage by stage. You have to attempt the reviews properly. And if you do any changes in the coding that also reflected should be reflected in the paper. Under should be verified with all plagiarism tools and oak. AI content also. We have to check. So there are a lot of checks. Before. Getting into a quality publication. There is if there is any gap in the publication. Definitely I will guide them. To get into the quality publication.

You emphasized the importance of ensuring code changes are reflected in the paper—can you share a case where a last-minute implementation change significantly affected the results section, and how you managed the update process with your student?

Yeah, in the results section, actually each and every graph or table you mentioned.

Little bit, one hour, 2 lines explanation should be required and also mention on.

Right. When you or your student update a graph or table due to a code change, how do you ensure the rest of the manuscript—particularly the interpretation and discussion sections—are kept consistent and accurate with the new results?

What approach actually given improvement? So what are the mathematical measures or metric used in your research? That you have to mention. And accordingly. Clearly you have to mention where the novelty is there. Then which algorithm you have? Taken for a comparison. So all these are all very important for.

Okay. In your experience, how do you verify that every update in the results or graphs is accurately described in both the discussion and the conclusion before submission?

Right. When you guide students to highlight the novelty in their research, what strategies do you use to help them clearly differentiate their work from prior studies in their writing?

Improvement of the results section. In the research article. Results analysis results section is more import.

Right. When a student selects a machine learning algorithm for their healthcare project, how do you guide them to justify their choice over alternatives in both their implementation and their write-up?

Oh.

Yeah, when a student selects machine learning algorithm for healthcare project.

Thank you for sharing your process. When guiding students to compare algorithms, what specific metrics or evaluation criteria do you ask them to report in their results to demonstrate their algorithm’s effectiveness?

Understood. When students are comparing algorithms, how do you instruct them to select and justify evaluation metrics that are both relevant to healthcare data and meaningful for publication?

So like that all the features we have to collect and implement. And get the result then. Improve the. Result section.

Through the machine learning approaches and all.

So all the machine learning and deep learning approaches Sir, you have to identify. All the medical datasets you have to identify. Once the work is completed. Then you have to go for. A real time data set. And consult with doctors and physicians.

Got it. Earlier you mentioned the importance of preprocessing in machine learning projects—when working with healthcare data, what preprocessing steps do you consider essential before training and why?

Right. You emphasized collecting all features and thorough preprocessing—when working with sensitive healthcare data, what techniques do you rely on to ensure data privacy and compliance during preprocessing?

Radiologist take that. Then have a frequent discussion with them and improve the results. Then we'll have to go for publication.

Right. Once your students gather real-world medical data and consult with physicians, how do you ensure their project remains compliant with ethical standards and institutional review requirements during publication?

Understood. When coordinating with physicians or radiologists on a student project, what strategies do you use to manage differing expectations or feedback between the academic and clinical sides?