Hello I'm

Sunny Guha

Opportunities in life are like trains. Like you missed that train because had you caught on to it like five years back, you would be in a much better place.

M.Sc. Physics

B.E. Electronics and Instrumentation

CGPA: 8.1

EXPERIENCE

Sep 2020 - Present

Mathworks, Massachusetts

Application Support Engineer II

As an Application Support Engineer, I have dual roles. In the development role, I work on deploying deep learning models that are trained in MATLAB. Models are coded in Tensorflow, Pytorch but when you deploy them using C++ inference libraries, they need to be optimized for performance. I work on this optimization process. In my customer-facing role, since I have a specialization in deep learning and physics, I provide domain-specific help to customers regarding such tasks. Recently, weather.com was building a model for some weather prediction and needed someone who had domain expertise in deep learning to help them out. So that's what I do.

2017-2020

Texas A&M

PhD Student in Theoretical Physics

I had seven research publications in renowned journals on practical aspects of String Theory and CFTs involving complex mathematical and statistical analysis inclined towards the understanding of fundamental physics.

May 2015 – Aug 2015

CERN Internship, Geneva

Software Engineer

In the first month, we were given coursework. There were no exams, but they started from the very basics right upto all the recent developments. In the next month, students were either assigned or given the option to choose a supervisor. My task was to design a modified implementation of a clustering algorithm to detect jet structure in collision data at CERN. This turned out to become my most cited paper.

May 2013 – Jul 2013

University of Leipzig

Intern

My project was based on Feynman Diagram computation. The scattering of electrons is one of the simplest processes. But when you compute the amplitude of that process, it's a four-page, tiny handwriting long calculation. Spinner, helicity formulas help do that computation in four lines. My project was just this new formalism like doing fine computations, and with these new methods. I wasn't doing any new research but I was reading research papers and then applying them to certain things.

QnA

I simply applied on their portal. In Mathworks, it doesn't matter if you join as a PhD, Masters, or a Bachelor's, you have to go through this support engineer role because that gives you a good idea of what your customers are. And then within a year then you move on to full-time development roles.
Unlike other companies, in MathWorks, you can switch your roles every two months. You have these two-week-long projects. For example, my first cycle was with the performance team. I learned how to make up for the deficiencies in performance of C++ STD libraries. On a code basis just to make 0.1% of increment is a big deal in a large codebase. Right now, I'm working with the GPU deployment team. My next project will be with the signal processing team where I would apply deep learning to those tasks. So this is one good thing about the work that I can keep on switching. To add on, the working hours are flexible but like in general, I have to put in like eight hours of work but it can be whenever I want.
In my opinion, theoretical particle physics is a dying thing because the funding is very less. There’s also a lot of competition because there are many applicants, but fewer positions to offer. I highly discourage anyone from doing theoretical physics because there's no room for average people. There is no room for very good people. There's only space for brilliant people. Plus, there’s financial instability. If you want to be a professor in physics, you have to do at least two rounds of Postdoc. And a Postdoc gets a little salary. Also after every three years, you have to apply for Postdoc again. And there's a chance that you might not get any Postdoc position. You also don't know where you'll get a Postdoc. If I apply for Postdocs, I'm not guaranteed to be in the US because I might not get accepted by any of the US institutes. There is no location stability as well. Thus, at a point, I decided what matters to me the most. Yes, I loved physics but then I'm not getting any money or location stability. And I wanted to stay in US and given it was a 70-30 for me (70% chances of me not getting a Postdoc in the US), I said, “hey, okay, so I don't want to take this risk, I would rather go into data science and those kinds of fields.”
I was always interested in physics. I had a pretty high BITSAT score. But I just wanted physics. During my time, BITS Goa was probably India's best Institute to do physics in. If you just count my physics courses, I have a ten-pointer but in all my EnI courses, I have Cs, like barely just barely making it through. Professors at Goa were offering top-notch electives that are taught in grad school. I took these high-level courses and that motivated me to walk in theoretical physics. There was this professor, Chandra Dave Sharma at BITS, Goa. I used to be in his office all day every day. I'm sure he hated me because I used to bug him a lot. Later, I did my thesis with Ashok Sane, one of the top five physicists alive.
If I had to do it over again, I would still do a Ph.D., because knowing that I know more than almost anyone on this planet about a certain thing is a feeling that you only get after you do a Ph.D. But if anyone says Ph.D. is easy, he's clearly lying. It is a big struggle. Maybe your first few years would be fun, but then when the grind begins it becomes depressing. But then, at the end of it, it's nothing like it.
PhDs are highly valued. Each company has an initial screening process, and when you say that you have a Ph.D., that gets you through that door. When they see that you have a Ph.D. that means you can be committed to some things and you have the aptitude to acquire those skills. You will get a lot of interview offers, and now it depends on your skillset to convert those interviews to jobs. I spent two-three of the final months of my Ph.D. on interview preparation.
Definitely a Ph.D. However what I would do a Ph.D. in, i.e, physics or computer science is debatable, but I would still do a Ph.D. because Ph.D. has certain more value to it as well. The experience is nothing like it. You spend five years in grad school, you learn so much. You contribute to human knowledge, there is that philosophical aspect to it. You are interacting with the most brilliant minds in human history at that moment. I can't tell you about this experience till you live through it. There is nothing equal to it for sure. There are some additional benefits you gain. Ph.D. helps in immigration, basically gives me easier access to a green card. Folks who do Ph.D. in Canada directly get a green card. Folks doing their Ph.D. in Germany for 3-5 years get a green card. When you're applying for things, this might not be a major concern, but when you're approaching that stage of your life, where you have to be settled, these things play an important role. I personally would do a Ph.D. again. Even if you forget all the benefits, I’d do it just for the experience, the pleasure of doing research.
There are two internships. One is for member states and one is for non-member States. You’d have to check which category India falls into currently. The application requires you to write an SOP, and answer some questions like "what do you intend to do in physics? What's your goal?" You also have to submit recommendations.
To all my friends who are doing their Ph.D. and who want to switch, I’d say just keep doing some tiny bits of programming so that you don't do it all at the very end. It's not a hard switch, you just need to be prepared.
I have entrepreneurial dreams. College tuitions, here in the USA, are a pretty big deal like so if someone started a chain of something like FIITJEE just for college students, that is going to be insanely lucrative and kids need that. And right now, there is no such player in this market.
Maybe I should have joined the deep learning bandwagon a bit earlier. I realised I liked deep learning in the third year of my Ph.D. Maybe if I was more proactive, I could have gotten into it from my first year, It's a train, right? Like I missed that train and had I caught on to it like five years back, I would be in a much better place, but then you can't always have all the things you want.
Do not waste your summer, starting from the first year. Never, ever, ever waste your summer. Enjoy your time as well. No matter where you go, the time at BITS was the best years of my life. Obviously do your due diligence and your academics and whatnot, but then chill out. You don't have to slog or study all night. Just enjoy your time and everything else will fall into place