Interviewer 0:00:00
Good day, Mrs.. 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. Shall we get into it?
Interviewer 0:09:00
Please start by introducing your professional journey in academia.
Mrs. Preetha R 0:09:24
I am Pritar. Currently working as an assistant professor. In department of. CSC Emerging technologies at SRM Institute of Science and Technology. I completed my PhD from Vit Vellore.
Mrs. Preetha R 0:09:43
Where my research focused on deep learning based detection classification. And segmentation of. Brain tumour using magnetic resonance images. My work resulted in. Reputed journal publications including I Triple Access and Scientific Reports.
Interviewer 0:09:29
So you're currently teaching in Computer Science and working with emerging technologies. What's one foundational concept or topic in your field that you find especially rewarding to teach to students?
Interviewer 0:09:46
Right, so your research on deep learning for brain tumor detection led to publications in IEEE Access and Scientific Reports. Can you describe how you bring concepts from that research—say, image segmentation or classification—into your undergraduate teaching?
Mrs. Preetha R 0:09:52
I have also 10 years of teaching experience. Handling.
Interviewer 0:10:10
Given your strong publication record in brain tumor detection using deep learning, where do you see the most fundable research directions in medical AI over the next three years? Which granting agencies or funding sources would you specifically target to support this work?
Mrs. Preetha R 0:10:33
Yes, I can. Uh. I can implement my research in. Undergraduate teaching, including a assisted learning. Uh for medical image processing applications and I also have applied these. Research works in. My undergraduate student projects.
Interviewer 0:10:35
You mentioned applying your deep learning research to undergraduate projects and classroom learning. In practical terms, how do you ensure those student research projects actually produce outcomes that are publishable or competitive for major conferences?
Mrs. Preetha R 0:10:39
Which includes segmentation, classification and medical.
Mrs. Preetha R 0:11:05
And also it it will be useful for a assisted diagnosis. Yes, did medical diagnosis, uh. Uh, my undergraduate students. Doing the projects. For this AI assisted diagnosis projects.
Interviewer 0:10:55
You mentioned guiding students in segmentation and classification projects, drawing directly from your own research. With your background in deep learning and medical imaging, what's the most effective way you've found to secure external funding or grants to support your research group?
Interviewer 0:11:07
Alright, you mentioned your students are working on AI-assisted diagnosis projects tied to your research. Thinking about the bigger picture—how would you scale that into a formal research group, and what funding sources are realistic for this line of work over the next couple years?
Mrs. Preetha R 0:11:58
I make a research group including this medical research projects and we apply for different I. ICMR. And ICMR funded projects. I applied last ICMR projects for brain tumor detection and also for cardiac related. Projects. And also for. We apply some project, some funded projects including.
Mrs. Preetha R 0:12:05
This uh. Tumor detection. And classification. Projects.
Interviewer 0:12:11
Okay, so you've formed research groups and gone after ICMR funding for your medical imaging work. Shifting to classroom teaching—imagine you have to run a core lab session for a group of 50 undergraduates, but you can't rely on slides or standard lectures. How would you keep those students actively engaged and ensure they really grasp the material?
Mrs. Preetha R 0:12:57
We collected the real time. Images from UH Sims Hospital, SRM Institute of Medical Sciences. From there we collect. And we will do The Sims projects also. Related to this. Medical. Uh, projects.
Interviewer 0:13:06
Okay, so you've built research groups, secured clinical data, and involved students in funded projects. Shifting gears—imagine you can't use slides or traditional lectures for a large undergraduate class. How would you design a session that keeps 200 students actively engaged with, say, medical image segmentation concepts?
Mrs. Preetha R 0:13:30
1st we collect the real team datasets and then. Uh, we will start. Preprocessing that, uh, MRI images. Uh, we collect the images in uh. Matte format, MATLAB format as we want to. Convert that images into. JPG format. And we will work on that all.
Interviewer 0:13:32
Okay, so you’re working with real clinical datasets, handling all the preprocessing, and guiding students through the full pipeline from raw MRI data to classification and segmentation. When you’re running these sessions, how do you actually check if your students are grasping the deeper concepts—like, not just following steps, but understanding why each one matters?
Mrs. Preetha R 0:17:10
They will do each step. By step, that is, first they collect the data assets, then they will analyze the data sets. They will study all the characteristics of the data sets. And then if you if they want to change the data set that that means they want to please preprocessing the data set, they will do that all things. Then they will, uh, split the data sets for training and testing. Then implement some models and they will do. Works on that if they get. Uh, good research. They are comparing different models and when which model gives more. Accuracy. They will choose that model and uh. Training that model and give the external data sets and if it gives more accuracy. They will try with another data set source, so. In that way they will check. If it is working or not.
Mrs. Preetha R 0:16:18
Implementation.
Interviewer 0:16:23
Alright, Professor, shifting focus a bit—accreditation cycles can get pretty demanding. If you joined our department and found that outcome assessment data was inconsistent across courses, how would you approach fixing that?
Interviewer 0:17:16
Alright, Professor, let me give you a scenario. Suppose a student files a formal complaint, saying your grading was biased and unfair. At the same time, your department head is urging you to improve pass rates in your course. How would you handle this situation and balance academic integrity with these institutional pressures?
Mrs. Preetha R 0:18:50
For, uh, balancing my academic integrity with the institutional pressure. I will do. I can improve the student. Uh, learning capacity by giving them. More opportunities to do the works. That is, first I want to analyze the student. Behavior. Student capacity. What is the learning ability of? The student. What is the problem? What subjects? He wants to more. He or she wants to more concentration that all things I want to know. After, uh, after, uh, checking all these things, what is the? Uh, drawback. Or what is the? Limitation of his uh. Uh, study first I want to know all these things, so then only I implement what to do? For his improvement.
Mrs. Preetha R 0:19:02
What also I give uh, I'm doing the works uh which given by. My institutional head also.
Interviewer 0:18:55
Alright, Professor, with your deep work in medical image analysis and AI, do you have any connections with hospitals, healthcare companies, or industry partners that could open up internships or placement opportunities for your students?
Interviewer 0:19:08
Alright, now I want to focus on how you evaluate students and handle exam duties. Imagine you’re in charge of a large final exam—how do you ensure the grading is fair, consistent, and actually measures the students’ understanding rather than just memorization?
Mrs. Preetha R 0:19:56
When uh, when I set the question paper itself, I make the questions in application level only. Don't make the questions in direct way I I want to. Uh, analyze the students application ability. So from the starting itself, I'll Geeta. Application level of the questions and also. I did. Uh, I'll teach them the concept and, uh, I'll. Info I'll.
Mrs. Preetha R 0:20:26
Teach them to how to apply these concepts in application level and also the questions may ask in that way. Then only I can. Analyze that. Uh, what is the? Uh kept what is the capability of the student to understand the things if he memorized the things he didn't understand anything if he apply the. Concepts in the application. He can understand what? He he launched.
Interviewer 0:20:03
So you design application-focused questions and try to push students to demonstrate real understanding, not just recall. Makes sense. Now, switching gears—can you give me a concrete example of an industry project or consultancy you've been involved with, and what your specific role was?
Interviewer 0:20:29
Alright, so you focus on application-level questions and make sure students can actually use what they've learned, not just repeat back facts. Switching gears, can you share a concrete example of a consultancy or industry project you directly contributed to, and walk me through your role and how you engaged with the external partner?
Mrs. Preetha R 0:20:42
How he answered the. Uh, answer how he answered the questions in application level. From that only we can understand how much. He learned. From the concept.
Interviewer 0:20:54
Okay, so you intentionally design your assessments to push for real understanding and guide students to apply concepts, not just memorize. Now, when you guide student research projects, how do you help them choose between pursuing a publication versus focusing on a practical prototype or industry deliverable?
Mrs. Preetha R 0:22:11
When I guide my student projects, I. I insist them to do the. Some projects which are helpful to the public itself. For example, for a medical field. There are many projects which are useful for the. The public so I. Info I I teach them to. Learn from the real time data and do some projects. Which are helpful. To public. And implement that all things. For example, for my research, it is a brain tumor detection. So I I. I teach them to research on this topic and do some. Hardware projects also and implement that things for detection of brain tumor and then implement them that for the classification and the grading of that tumors.
Interviewer 0:22:14
Alright, we're wrapping up. Is there anything you'd like to ask about the role or the team?
Mrs. Preetha R 0:22:38
In implement integrating the hardware with this. This project, so this research project, Sir, only we will do the simulation only we. We couldn't understand anything. If we implement the hardware itself, we. Will analyze the. Umm, after we will analyze the problem. And we will. Find out the solution of that. Problems.
Interviewer 0:22:40
So you emphasize practical impact and push students to move beyond simulation, actually integrating hardware and real data where possible. That’s a pretty hands-on approach to research training. Alright, Mrs., we're wrapping up. Is there anything you'd like to ask about the role or the team?
Mrs. Preetha R 0:23:28
I'm very much interested in vit. Research. Research Environment. I want to know about the research. Fundings and all the things that. Given by the. Vit.