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IIT Bombay Admission Experience for PhD 2019

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I got a call for Ph.D. Test & Interview on around 26th April and Interview was scheduled for 18th May so there was enough time for me to revise my topics. On 18th May, sharp at 9:15 a.m. orientation started and around 9:45 exam started for 2 hours. First was a written test which is of the type Fill in the Blank. It consisted of around 45 questions (sub-questions included) and I did around 33 correctly (believe me if you’re a gate aspirant you can do it in the first 30 minutes only). Minimum cutoff criteria -> they will only select a maximum of 50 people but instead only 30+ students were selected for the advanced test and I was on the list. The same day around 4 p.m. advance test started which was a totally subjective test and 7 questions from every gate subject like Algorithms, Compiler, Networks, TOC, Machine Learning, etc. were asked. We had to solve any 2 of the given questions and this was a bit more difficult than the previous one. The subject in which you answer the question will decide your Interview panel. I answered from Algorithms, TOC, and networking (It was not an elimination round but questions were asked in the interview from it). Next-Day morning at 9 I was there and Interview started. Remember we had to choose 2 out 7 questions i.e we have to give 2 different interviews. My area of specialization was Algorithms and TOC so my first Interview happened in TOC something like this: Scenario: Two professors were taking interviews one was young and the other was experienced.
  • Prof: Tell me something about yourself?
  • Me: Told.
  • Prof: Then he started asking me about my project since I was 2018 (recently graduated).
  • Me: Told but I was interrupted in between
  • Prof: So why did you select TOC and in what area you want to specialize in. Also tell us why not machine learning?
  • Me: I told I want my area of interest is algorithms and TOC is base of algorithms. In short Optimization and Complexity Theory. Machine learning can is on top of Algorithms i.e for one to pursue machine learning must have a very good foot in algorithms and mathematics. (Quite impressed and said good)
  • Prof: Then he started asking questions from tests on optimization like how did you solved some question and in which I was stuck in one part of the section. Interviewers were quite helpful so after sometime I was able to give them proper answer.
  • Prof: Okay you can go now.
  • Me: (while I was leaving) …
  • Experienced prof: You did very good in networking tests then why not networking?
  • Me: I explained them that my area of interest is in algorithms where networking is completely a different field in which algorithm is only one part of it other is like system architecture, maintenance, etc.
  • Prof: Okay you can go now.
Overall it was going nice and after sometime I was called in Algorithms panel for interview. Scenario:  Same as previous two professors one young and other will sit and judge your skills.
  • Prof: Introduce yourself.
  • Me: Told.
  • Prof: Okay so you’ve chosen algorithms as area of specialization so in which domain you want to work in?
  • Me: Complexity Theory and Optimization.
  • Prof: So, what do you mean by complexity?
  • Me: I told them that computer cannot have infinite no. of resources or cannot run infinitely so when we create an algorithm to solve some problem, we want to know how much resources it will consume and how much time it will take to solve our problem. Thus, complexity is a measure understand the nature of solutions(algorithms) for a given problem.
  • Prof: (Impressed) So how will you measure them?
  • Me: Told about asymptotic notations.
  • Prof: What are asymptotic notations explain in brief. (Like write every condition for each case)
  • Me: Was writing and after 2 notations was interrupted
  • Prof: Okay now you tell me was is time complexity for binary search?
  • Me: O(log to be base 2 n)
  • Prof: Write recurrence relation
  • Me: I explained them how I generated recurrence relation.
  • Prof: What about ternary or n-ary search. Write recurrence for that also?
  • Me: wrote.
  • Prof: (Still impressed) Now tell me which one is faster binary or ternary?
  • Me: I told binary because in worst case ternary might look for 2n/3 element every time which is greater than n/2.
  • Prof: Compare both of them and tell me which one is greater.
  • Me: As a normal gate aspirant, I started cancelling log on both sides (taking exp obviously) and she interrupted.
  • Prof: This is not how we compare show me mathematically how to do it?
  • Me: Here I was stuck first time. After few minutes I gave up.
  • Experienced Prof: (Now the tricky question comes) Okay now you tell me why you want to do PhD?
  • Me: I explained them I want to do some research on my project and want to optimize it for commercial use and some other stuffs.
  • Prof: That’s okay but I want you to assure me that you’re mentally ready for this task.
  • Me: I told about my past like I am gate 2019 pass out with so and so rank, my knowledge and capability on understanding is good, but still I have incomplete knowledge and I have 5 years of time to clear things.
  • Prof: Then why not do Master’s program (R.A.)?
  • Me: I told him in Masters we have to do many other subjects which might not be of our domain to earn credits. And some other drawbacks of master’s degree
  • After few minutes that prof indirectly said to me that, “I would advice an aspirant like you to do masters first and then only join PhD” and interview was over. Overall, I was not selected because there were few candidates who had master’s degree and were in teaching field for 3-5 years whereas I was a fresh graduate but the experience I got over there was quite good and unforgettable. Interview lasted for about 25 minutes + 45 minutes   About me: I was AIR 1406 Gate 2019 aspirant currently pursuing masters from NITK Surathkal. After Gate 2019 results came around 16th March that year. Applications for IIT’s/IISc will start immediately after gate result announcement so make sure you check respective institute’s website regularly.

    Last Updated : 06 Jun, 2023
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