Sahil Yerawar

Sahil Yerawar

About

Hi! I am Sahil Yerawar. I have done my B.Tech in Computer Science Engineering from IIT-Hyderabad. I have worked in various projects related to Natural Language Processing, Machine Learning, Information Retrieval and Compilers in my undergraduate years and after graduation. I am interested to work on open-source projects and in research environments, both focused on core areas of Computer Science.

In my free time, I enjoy running, playing music, cooking and learning new languages on Duolingo.

Download my C.V.

Education

  • M.S in Computer Science

    University of Massachusetts, Amherst

  • B.Tech in Computer Science Engineering, 2019

    Indian Institute of Technology, Hyderabad

Experience

 
 
 
 
 
Backend Software Engineer
Snazzy (YCombinator W21)
Jul 2021 – Jul 2022 Bangalore, India
Designed and implemented a microservice-based backend for user-website, internal admin portal and doctor/patient android apps of Snazzy.
 
 
 
 
 
Research Assistant
IIT-Hyderabad
Mar 2021 – Jun 2021 Hyderabad, India
Along with Prof Maunendra Desarkar and Prof. Srijith P.K., worked on projects related to machine learning using alternate data sources using knowledge distillation techniques.
 
 
 
 
 
Research Assistant
IIT-Kharagpur
Sep 2020 – Feb 2021 Kharagpur, India
Under guidance of Prof. Pawan Goyal, contributed to projects related to Explainablity in Recommender Systems (Information Retrieval) and creation of Indic Datasets (NLP).
 
 
 
 
 
Software Engineer
Honeywell
Jul 2019 – Jul 2020 Hyderabad, India
Member of Displays and Graphics Team in Aerospace Domain. Responsible for developing display applications for Aircraft Cockpit Systems

Accomplish­ments

Coursera
Natural Language Processing Specialization
Coursera Sep 2020
See certificate
EuroLLVM 2019
LLVM Foundation Apr 2019
Presented the work and findings of 2018 GSoC project as a poster in EuroLLVM 2019 at Brussels, Belgium.
Got Selected for Google Summer of Code (GSoC) internship as a part of Polly organization
Apr 2018
Secured rank of 805 and 4397 in JEE-Mains and JEE-Advanced (out of 1.3 million students)
Jun 2015

Projects

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All Deep Learning Systems Information Retrieval Machine Learning
Digital Flight Manual
Built a QA based tool to relate every question regarding particular flight manual towards an appropriate paragraphs which contains it’s answer.
Explainability of Post Hoc Algorithms
Analyzed the various post hoc models used on top of Recommender systems to provide detailed reasoning behind the predictions. A metric based on existing statistical correlation methods is being developed to quantify the degree of it’s explainability.
Parallel Indic Datasets
Collected government documents to build a parallel English-Hindi dataset on sentence level for Neural Machine Translation tasks.
Integrating Polly Loop Optimizer with Chapel Compiler
As a part of GSoC project, I have successfully integrated polly loop optimizer of LLVM within Chapel Compiler framework and demonstrated several examples demonstrating the huge speedups gained from these organizations.
Report Poster
Reputation Score Prediction using Alternate data
With the uneven distribution of privileged features among the users, we are developing semi-supervised models to predict reputation scores for Community QA site users using only commonly available data with the help of teacher model having access to privileged features as well.

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