Good day, Aakashdeep Gupta. 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?

Clarify what you mean by work.

Yup.

What do you mean by work?

Yes, yes, yeah.

Yeah, thanks for the clarification.

So I could say that.

Uh, again, my life starts. Career starts with bachelors and then masters and PhD.

And most of the time where the in these three stages of my academic journey, most of the knowledge and skill.

Uh, comes from working as a, as a project associate in it, then masters and then PhD at IIT Madras. So as in as my alma mater. It's a lot of things I have learned from my time at item address. And also I was, uh, for a, for a short one year, I was part of a big MNC that is global foundries in Indian side. So there I have.

How to act professionally and how to be a team player if there is a task given at hand, a challenging task to the whole team.

Learnt more about.

At the present moment, I am. I have been serving as a post doctoral researcher at IIT Bombay.

And uh.

And here again I have.

Developed a very particular in-depth in depth insights and understanding on reliability mechanisms of semiconductor devices. So to detail a little further.

Uh, during my, uh, time at IT, Madras I.

I have been involved very very in depth.

I had to study devices such as.

HPTS which terms as heterojunction, bipolar transistor and my most of my research was around studying silicon germanium HPTS and the inner mechanisms when it comes to electrothermal analysis of it.

Uh, our prime goal in, in research, the group's research was to develop a compact model or a spice based model with, uh, with features so that it can be, uh, implemented along with industry standard model that is Haiku.

Our goal was to figure out simple derivations of compact models which can be easily implemented in industry standard hiccup model.

And the bigger goal was to to analyze the heating phenomena to that accuracy so that we can predict what is the device temperature after elliptical operation of certain time, how how much heat can be dissipated when we are turning the transistor on and letting it run.

For different different bias conditions. So most of my MSN PhD work built in that.

And.

Before MSI was for one year I was predicted associate where I had to again get the depths of the the term which is used in that tradition, that is parameter extraction parameters for again high compact model and again our device of interest was in Germanium HPT.

And uh.

As it is now very well established, we our goal was to get more in depth mechanisms of this HPT device when it operates in sub terahertz or in intensive gigahertz we used to study.

And.

Come up with some parameter extraction strategy at high frequencies.

At in in during high current injection.

Biases.

And in.

In PhD.

Once we manage to develop a compact model for our thermal heating.

We also were trying to devise a simple device design approach using.

The compact model and we used.

The compact model to to to propose an approach in multi finger structure that is non non uniform finger spacing or design of multi finger structure for certain power amplifier applications while minimizing the maximum temperature of of the device at high injection.

So that that was how we concluded the work. MSN, PhD work.

Followed by an MSN PhD. I also actually end up learning lot on TCAT a lot. A good understanding of SPICE compact models and implementations and parameter extraction and dumping the compact model into into a very low case script and running circuit simulation.

Once we are satisfied with the parameters and as as early as I graduated.

Immediately I had to join Global Foundries.

Where I was taught a very precise and professional way to handle a TCAT problem. TCAD is 1 jargon which we use in semiconductors and there were tools like synopsis tools different different tools to to develop a more in depth physics models which.

We can which was used to help process engineer guys and predicating.

So.

I I quickly grasped a lot of in depth.

Strategies to prepare a ticket model and primarily I was involved in Google Foundries very latest technology know that is friendly to FTX and also I was part of 55 BCD dev development.

These nodes if now we know Google foundries, most of the profit comes between.

From utilization of these two nodes and larger notes as well in RF applications. So I learned a very professional strategy how to initiate the TCA development and how to make the TCAD deck or the TCAD model more precise with the help of measurement data coming from process engineers guys and also to give a feedback on device design.

The process guys.

And I must say that.

I most of the ticket what I know at presently. Most of it I learned in Bluetooth foundries.

And after one year, I left the company and I joined IIT Bombay as a post-op fellow or postdoctoral researcher.

And here I was exposed to.

Complex reliability mechanisms in finfets and gait all around.

I also got exposed a very good exposure of the the in the the big literature literature which exists in reliability modeling or modeling of reliability physics such as BTI or other phenomena such as time-dependent dielectric breakdown, hot carrier effects.

For different different.

Devices. Some are on latest CMOS notes and.

One, I also had to study reliability effects in 3D NAND technology and.

Given the complexity of reliability mechanisms in current CMOS notes, UH, I was exposed to the latest modeled by IIT Bombay's team, which very well works and explains the observed characteristics of degradation and end of life prediction models.

It's very exhaustive physics based model and we often term it as Mahapatra reliability model for every in-depth physics and also.

I, I, I had a very good experience in implementing the model this MRM in TCAN for 2D and 3D devices. Again, our current focus has been so far on FinFET and gear around technology node, the latest one which is in competition between industries.

And, uh, simultaneously I.

I I I went through and saw a very large literature of and I still have been dwelling in literature of reliability modeling.

Which in itself is a.

It's it's I saw big task. If someone wants to say that they know that reliability, the there are some models which became classic and are still in use today.

There are models to predict TV time dependent electric breakdown and trap generation, trap formations when BTI gets activated or HCD and how the physics I I know now that how?

Ideal transistor age down due to electrical stress and at different different temperature and how one can precisely model it through MRM?

So that insight I I.

I I that insight I understood and learned, giving me an extra scientific edge on reliability.

Which is another reliability effects and that also add-ons with my PhD experience where I was again doing reliability modeling but from self-witting point of view. And now there are reliability effects in post log which I understood which are in addition with self heating and other non-linear or non ideal effects of oxide breakdown.

Or dietary breakdown and as I mentioned BTI, CD and in both NMOS, PMOS and very, very keenly I managed to get exposure in 3D NAND how some of the.

Reliability, uh, mechanisms are impeding the technology evolution of 3D net, which is at present again another competitive technology of 3D NAND companies are going crazy.

To they're going crazy to expand it, scale it up and increase the volume of production while doing that.

Yeah, I hope my response is is very concise and precise. I hope so.

I could you repeat the question? I couldn't hear the full sentence.

OK. Yeah, that's a good, that's that's a good question. So.

Of course. Can you explain how you approach teaching complex topics, like semiconductor reliability modeling, to students who may not have prior expertise in the subject?

First thing I know.

That given my experiences in both Academy and industry, that a topic of reliability physics is is not so.

Simple to to teach a Btech student or a master student.

When the student doesn't have a sufficient background funda clarity of fundamental concepts in semiconductor device physics so.

I I would prefer to 1st.

Focus on what is reliability, the terms it has reliability.

What it implies when I say reliability physics modeling?

In semiconductor I will detail it.

And I will.

Request or ask students to have an open mind and get the terms right first and with explanation. Uh, what is the narrow definition of reliability modeling? What it means when we say model?

And why we have to model something which is not, which is not so simple phenomena, why we have to worry about it. So there comes the motivation, along with a very a very short introduction and motivation to why to discuss.

And with a with a with a slight.

Extra knowledge or extra by mentioning where industry lacks when it comes to reliability. What is going on at the moment in these big companies? What is happening and why?

This reliability physics modeling is the focus.

And that I have in my observation is sufficient to to increase the attention of students towards the teacher making sure.

That they also don't get drift away from the topic at hand and I tend to use that curiosity which just got induced in them to define further in depth terms such as.

What we mean by device physics and what it means when I say modeling of device physics. OK and I'm sure with a with a good attention, students would get adapt to their concept of.

Semiconductor aging or the term as what it means when transistor goes through aging just like a human there are certain.

Reliability mechanisms which turn on.

When I put a very high voltage and the gate of mosfet and slowly step by step I would.

Help them to understand that.

What really happens if I have a vertical elliptic field in the gate or lateral field from the train and in a very strategic way, the in depth of how we define hot carriers, cold carriers and.

Why electric field from gate and drain they all come together.

And shows us the effect of aging in in a in a in a very planar MOSFET device. So yes, it is cumbersome, but I do believe there is a very linear.

And a simple approach is first to get a good grasp on the motivation and then a bit by bit encroaching, encroaching the depth of the particular topic. And I firmly believe one students gets hooked on to the class when I'm explaining this there itself, I believe half of the battle has been won already by the faculty because. You need a very good attention with an open mind.

But see something which is not which you you have not seen before.

And a very sharp curiosity helps to bridge that gap between faculty and student. And it also helps us to appreciate that even though students may not be interested in whole subject, they may appreciate what concept is being taught on the board.

So.

Please go ahead.

Arjun, are you there?

Yes, I'm here, Professor Gupta. Thank you for the detailed explanation. You clearly emphasize motivating students and breaking down the complexity of topics into simpler, digestible steps. When guiding students through their research projects, how do you ensure that they maintain academic rigor while also fostering their creativity?

This is what I.

Firmly believe till I mean now.

Active importance to motivation first.

If a candidate or a student or a research scholar lacks motivation.

To push.

To push themselves out of the comfort zone.

Then nothing will do any good.

Because I asked for my.

Awareness or as per my understanding of human psychology.

Which helps in teaching.

It is quite easy nowadays in this.

Understood. Motivation indeed plays a crucial role in driving students to push past comfort zones. Beyond motivation, do you have particular strategies or frameworks to guide them in balancing creativity and methodological rigor in their research?

I wish.

I can give importance to.

The creativity, but the term creativity.

UH has to change if I'm talking between, uh, teaching a course or attending a course versus attending a real engineering problem that is challenging.

It is highly assumed that if a candidate is good in theories, they most likely will just.

You know, devote themselves to research problem. But I disagree on that because.

Theory has been abolished and refined through decades of.

Academic pursuit and and.

The development from technology of technology.

Via by this big big company so.

There itself is a big gap that more theory we understand. They are classical, most of it classically explained. But real research problems are nowhere near to classical, or I I should say they are more challenging in semiconductor engineering and they are far from simple to say they are complex problems are there.

So.

If even if a student doesn't show up in a class, say, and he or she is not paying attention to theory, which faculties have to teach?

I have experienced that.

It doesn't imply they may not be interested or they may not be able to figure out solutions to the problem if given a research problem, Uh, a decent research problem if it is given because.

Research is more about figuring out where I am wrong or where I am right.

While given with the literature.

Of big ocean of literature now.

Ability to be patient with this process of realizing something new or learning and unlearning something which is known already it it requires a lot of patience.

And the devotion of sticking with the method.

The method which?

Is in, is going to be with the measure which student is learning.

It needs a lot of patience and.

It hurts everyone if I'm telling this but.

The the goal of a class is to evaluate students on a predefined framework with questions and answers and homework.

In research, the goal is not at all a short term goal.

The research methodology can take many up and down turns and as my as per my engagement experience, there are times when there is a research proposed using a methodology and there can be.

There can be scientific debate about it. Some people may accept this study, many may not. And it often goes through a lot of critique from society, society which is paying attention to the, to the development of science, development of the science of a particular subject. So.

Skill of being patient and very intuitive.

Intuition intuitive.

Uh, with awareness that OK, it needs a very in depth time.

Uh, uh, a lot of personal time has to be in thinking and then reading again. And I, as I use the word learning and unlearning again. And sometimes even it may involve not following what existing theories I have to say. So I, I believe that if someone was interested in established theories, mail like the research, but I, I don't believe anymore that.

The creative mindset which which may not be visible in theory classes, is required in research research patients and.

A conscious awareness about.

Where things may be falling intuitively and that has its own journey to make prepare a human being to acknowledge and understand.

Things which are beyond the.

And that itself is a.

Has to be a scientific mindset and.

Ability to unlearn some of the theoretical concept which might be wrong and and then coming with our own methodology again with cycles of failure and again proposing and failure and not able to explain.

A given phenomena with help of measurement or learning simulations.

That creativity in research is is is not what?

We see in theoretical classes, so.

I have found some of the key students tends to be there in a class who are very much interested in doing practicals or playing with some things and connecting something and thinking out-of-the-box. In practical classes we can see there are a few students who who are doing well and they may not know theory, They may have missed their classes.

But there are set of students who may question something which is not.

Unconventional and they can think out-of-the-box. So practical classes.

Irrespective of what are this thing practical classes are are there to expose some key students who are there to think rather than getting things done and getting the marks so.

So yes, there are some students, but I don't see a creative overlap between between an predefined academia versus.

The open ocean of knowledge and research and.

A competitive research so it doesn't strictly overlap the creative thinking. We need more sometimes than creation as well. Not everything can be guessed.

And as I said, patience is a virtue in research.

And sometimes one has to be very, very.

Confident on what they're proposing makes sense. Again, another set of experience. We don't see that in class. It can be.

It it it can be induced in a student through.

Through a room to play.

With.

And uh.

Mindset of academia where the student is thriving.

With with a good.

So.

I'm repeating myself again. Theory classes, homeworks and marks don't define the extra edge which is required in research and I always say to myself.

Research is not easy, but it can become easy for someone who has come into research with with little patience to think.

And to listen and to think, OK.

Giving time for the giving time with the process of research.

To develop that scientific mindset, and again, it needs, it needs calm patience with the room of Freedom Master.

So I guess.

I guess my response is sufficient.

My apologies for the.

For the disturbance in in vicinity.

Yeah, Yeah. Please go ahead. Please go ahead.

In your research and teaching experience, how do you balance advancing cutting-edge research, publishing in reputed journals, and meeting the demands of teaching responsibilities, such as student evaluations and guiding projects?

Time is up! Ending the interview now.