03/08/2018
ACM IIITB welcomes its alumni Ashish Gupta for our event "Koffee with Alumni".
Ashish is an ML enthusiast since his Btech and that's what drove him to IIITB. Where other students ended up for internships Ashish choose to go for thesis and learn more on ML.
As an outcome of his consistent learning attitude, his thesis work getting accepted at 'KDD Deep Learning Day 2018'.
He got calls from many tech giants for his work on ML and continues to get so.
Know more about Ashish Gupta and his life at IIITB here 👇 in his own words
My Journey of IIITB
Before IIITB I was working in TCS, and since that time I had a huge passion for Machine Learning. My B.Tech final year project was also in Machine Learning. I thought of continuing my passion for ML in TCS, but things didn’t work out. I asked my seniors and mentors there for any ML-related work but it seemed they didn’t know about it, so they ignored and told exciting stuff about their work. But being a CS grad I already did a decent amount of work in web development, so I was looking up for something exciting apart from this work(PS:- It depends on interest).
After probably working 1 year I knew that I’m stuck somehow at a place which I’m not enjoying and then I decided to give GATE. After qualifying it, I got admission in IIITB. During this time I also cleared ISRO Scientist/Engineer ‘SC’ exam with an impressive AIR 56.
In IIIT Bangalore where I met world class faculties and brilliant minded people. The first semester was full of Data Structures and Algorithms with some ML work then slowly I started participating in ML competitions in Hackerrank, Hackerearth, etc. Before coming to this college I didn’t have clear concepts about the Math which works behind the algorithms in ML. I’ve gone through many online videos in ML but they only told basic stuff and the implementation part. In 2nd semester, I took up FBDA(Foundations of Big Data Algorithms) course in my college which helped me clear my concepts to the depth and side by side I was also going through Andrew Ng’s Stanford videos in ML which were really an eye-opener for me. These videos made me believe I hardly know anything in ML. After completing the whole course I was confident enough of the Math and algorithms in classical ML.
Prof. Raghhavan’s(one of the best Prof.) course in FBDA and Machine Learning helped me to solidify the concepts more. I also took a research project under Prof. Raghavan and it was creating a Conversational AI agent for Ramyam Intelligence Lab. This project was a turning point for me indirectly as after this Prof. Raghavan wanted me to do thesis under him. But at that time I was reluctant and hadn’t made up my mind for the thesis.
Placements season starts(a tough time for everyone):
For placements, everyone needs to be strong in algorithms and data structures. I sat for placements in around 5-6 companies which visited our college and at that time I was open for internships. I cleared Amazon’s written test(3 times it will be described later) and went on for the interview. The interviewer saw my CV and asked me about the Conversational AI agent project, then he went on asking about some problems with algorithms. After this round, I was pretty happy as I gave up all his answers which were correct according to what I’ve till that date. But somehow after the 1st round, I got rejected-- Reason-- I don’t know till now, maybe they were looking for SDE role and most of the part of my CV had ML projects and ML competitions. After that, I was not able to clear preliminary coding rounds for the upcoming companies. Moreover, I applied only to those companies in which I was interested. After this, I had a clear vision of doing a thesis in a particular area, as now if I sat for placements I thought of getting lost. By this time Raghavan Sir, under whom I wanted to do my thesis, was also filled up. I got thesis opportunity under Prof. Manish Gupta(VideoKen).
I got FTE in Digite and since this semester I started reading about my thesis work. I had meetings near about every week with my supervisor discussing what I read and what needs to be done. By the end of this semester, I was sure what things I need to do.
In the 4th semester, I started with the implementation stuff and read multiple papers and followed many researchers work. At this time I was also the TA for the courses Maths for ML and ML 1(Practical Machine Learning) courses. This period had many difficulties as I needed resources and many other things required to finish up my work. After seeing many of my friends enjoying I felt demotivated and sometimes thought about why I’ve taken up the thesis. By there was something tinkering in my mind that if I do good work then surely I’ll be happy.
In the month of June 2018, the best month for me, as I got calls nearly from all the big names which one can think of in CS domains. Amazon made me fly to their onsite location for a F2F round. But alas I wasn’t able to convert it up and got rejected in the last round. I had 6(initially telephonic) rounds of interview with 5 being in a single day and each round was of 1 hour. I also interviewed with Microsoft but was not able to clear their interviews. Apart from these companies I had offers from nearly every company with better pay than Walmart Labs. After much thought and discussion with Profs and friends, Walmart Labs was the best one which I joined.
Finally, my thesis work got accepted in KDD Deep Learning Day 2018.
Profile Links:
LinkedIn: ashishgupta031
Kaggle: eashish
Hackerrank: MT2016026
Analyticsvidhya: eashish
