About Self

I am currently working as a Systems Engineer (CTO Developer) @ TCS Research & Innovation Labs, on AI-related research. I have work experience of about 8 months and have spent most of it, researching and learning new and upcoming AI algorithms and technologies. In college, I have spent my time working on ML, Frontend, Backend development ( Python, Flask frameworks ), thus having some experience in web and mobile app development as well.

What are you good at? What drives you?

These are some of my strengths:

• analyzing complex data in order to draw clear and simple conclusions
• coming up with innovative ideas to enhance or boost already existing algorithms
• meeting deadlines, targets or goals
• mentoring juniors
• being the leader of the team
  I am someone who does not give up very easily. I try to push myself to the greatest extent possible. I'm not the one who gets stagnated nor does failure demotivate me. On the other hand, I feel galvanized to perform even more. What drives me is, finding a way to solve a problem, or overcome a challenge. This never-give-up attitude drives me to success.

What’s the most complex project you have worked on? What did you learn?

The most complex project I have worked until now is actually implementing the Collaborative Filtering algorithm. The idea was to try and build a recommendation system, that recommends the hotspots (most popular places) that you can visit in a new city, given a set of preferences of places like malls, beaches, etc., and the time interval you specify in your day. The application tries to recommend hotspots that are closer and also according to the preferences of the user given initially as input, such that he/she reaches the start point by end of the interval. This project was quite challenging for me to implement as I had to try the CF algorithm without any experience in the field of Supervised Machine Learning. When I started implementing the algorithm, I didn't have much knowledge about Supervised Learning. So it only then that I learned that ML is not just about python inbuilt libraries or frameworks, but it's more about the mathematics behind it. And as I spent more time to learn backpropagation and it's derivations, implementing ML became much easier. I am really interested to participate in this hackathon, firstly, because I have always been and will always be a Hackathon enthusiast first, secondly, explore ideas of my fellow participants, and thirdly, to have fun and give myself a break from my routine activity. AI is a developing field and it is really interesting to learn something new every day. Let it be Dropout Regularization or Xavier Initialization, new algorithms keep evolving almost very often and to try learning and implementing such algorithms is what drives us Data Scientists, crazy. Currently working in AI, I have started to grow interests other technologies like Blockchain*, I am trying to get my hands dirty on Solidity to try and build Smart contracts. I am currently doing Blockchain Specialization.

Let the hackathon organizers know why they should accept you.

Learning newer things provokes me, and I mean it in a good way. I am someone who has an open mind to learn new things. The hackathon organizers should accept me because like I mentioned a million times above I love <3 learning new things, Blockchain is a new step and I am ready to dive deep inside. So accepting me in this hackathon will encourage me and open me to new ideas of other fellow participants, and getting to know the kind of projects they implement will widen my knowledge of this current technology. I believe that learning should never stop. Given the level of competition, it becomes imperative to constantly reinvent yourself and culminate knowledge to whatever extent possible.