Jay Moghariya, EE1
Interned at: Nanyang Technological University, Singapore
I am an undergraduate student in the electrical department. Before this internship, I was sure I wasn't interested in my core, so I applied for internships in ML and bagged an internship at NTU under Professor Anupam Chattopadhyay, which happened online due to the pandemic.
Application Procedure
I started mailing quite late, in December. Though I had started working on my CV early, I didn't find anything substantial to write in it until December. I waited for COL106 to be over and completed the digital electronics project by then; hence it looked good. I had a good CG at the end of the first year, but it took a hit in the third semester. (Something I think is true for most students in the electrical department.) Due to the lower CGPA, I didn't get any replies even though I sent out many emails. Then I found out that a friend of mine had an internship under this professor and had received confirmation quite early, in Jan/Feb itself, but she didn't want to do it. So I emailed the same professor around February end, and fortunately, he replied and said to mail him around March end or April start, and he'll see. I took that as denial and rejection; nevertheless kept mailing. Unfortunately, I received no new responses. But I had snoozed the mail for NTU, and it came up around the time. I mailed the professor again but got no response for a week. Then out of nowhere, I received an email from him saying he had no problem working with me and to schedule an interview. During the interview, I was questioned regarding the projects on the CV and about the languages I used in the projects in COL100 and COL106. The digital electronics core project was put in focus because the professor himself worked in the core. His primary interest was Verilog, and he asked how much of it I knew and maximum how many lines of code I had written. Not very tough, but entirely based on the CV.
The Project
The professor was from electrical and the field has got many domains. I got four topics to choose from, which was lucky because usually, nobody receives any option. The research internship involved predicting the maintenance of industrial equipment. Heavy machinery has more repair costs, and production can be delayed if the machine fails. The aim was to determine the point of failure in advance so that when no production is ongoing, repairs and maintenance can be done accordingly.
The Internship and Experience
The professor was super chill. He said on the first day itself that he doesn't expect much out of 2nd-year interns. It was eight weeks long; two weeks of preparation, four weeks of work, and two weeks of compulsory report and presentation.
The topic was related to ML, and I knew I was interested in ML as I had explored this field during the vacations. We did a lot of work, the field we were working on is still developing. Weekly tasks were assigned, every week, a meeting would be held with the prof, TAs, and interns. We'd discuss progress, improvements and then they'd assign next week's work. 3-4 tasks were assigned per week, and 30+ hours of input a week was required.
The experience for me was enjoyable; I was doing the project with my friend, the TA assigned to us was super friendly, and he'd share memes on the group chat we had. All the TAs were extremely helpful, we could ask them anything, and they'd also give us tips on what the professor would ask so we'd be able to prepare beforehand. There was no stipend, but it was still an incredible experience. Beyond technical, I learned a lot from the people I interacted with.
Interviewed by: Priyanshi Gupta
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