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Summary

Graduate Student at the University of Minnesota with over 3 years of software development experience at Facebook, Amazon and Symantec, having primarily worked on Backend Systems, Machine Learning and Full-Stack Web Development.

SKILLS Python Java C/C++
SQL JavaScript Android CUDA

                                            

Education

9/20175/2019

MS in Computer Science

University of Minnesota Twin Cities

Specializing in Recommender Systems, Machine Learning and High Performance Computing, 4.00 GPA

8/20106/2014

BE in Computer Science & Engineering

Pune Institute of Computer Technology, University of Pune

Graduated First Class with Distinction, 3.55 GPA

Work Experience

5/20188/2018

Facebook - Software Engineer Intern

  • Working on improving the Entity Linking system used in Facebook Search as part of the NLP team.
8/20167/2017

Amazon - Software Development Engineer

  • Built and released an internal tool with scaleable web services for tracking potential large scale issues with Amazon Digital Services and Devices 100x faster and more easily.
  • Owned the development of the Help app on all variants of the Fire TV and Fire Tablets, including the Click-To-Call feature.
12/20158/2016

Symantec Research Labs - Research Associate

  • Developed a classification model to predict risk factor based on users’ web browsing behavior with an accuracy of up to 87%, for risk evaluation in Cyber Insurance.
  • Extracted over 30 features from a big data set of telemetry obtained from 100,000 anonymous users for profiling their web browsing behavior over a 3 month span.
10/20148/2016

Symantec - Associate Software Engineer

  • Worked in the Security Response Content Engineering team, primarily on Information Extraction from over 400 Android and Windows App Stores to supply data that powers all of Symantec's security software and solutions.
  • Designed, developed and maintained web harvesting systems which gathered >10,000 new units of metadata and >5,000 accompanying physical software archives daily. 
  • Came up with a Man-In-The-Middle approach to intercept and decode API calls made by handheld devices to be able to  automate the crawling of app based marketplaces.
  • Devised a more scaleable architecture, making use of Message Queues and a NoSQL database that let us increase our throughput by ~75x.

Highlighted Projects

  • 3D Object Symmetry Detection - C++ with STL, VCG Library, MFC - A Mesh Processing system for detecting intrinsic symmetries within 3D Objects using a skeleton based approach.
  • Head Pose Estimation - Python, OpenCV, dlib, dbus - Pose Estimation of a viewer's head using Face Detection, Facial Landmark Extraction and PnP for pausing a video being played on VLC Player when the viewer looks away.
  • GPU Parallel Movie Recommender System - CUDA C - A GPGPU User-User Collaborative Filtering system used to recommend movies using the MovieLens dataset with a 45x speedup over CPU implementations.
  • Paradise-GL - Java, LWJGL - A mini game engine supporting water simulation used to render a beautiful forest scene.
  • Audiophile - Feature-packed Android Music Player application.
  • Fray Tracer - C++ - Ray Tracer capable of rendering scenes with local illumination, reflection and refraction, etc.
  • Popular Movies - Android application that shows listings of the most popular movies and their details using the TMDB API.
  • Hangman and Cows & Bulls - Python, SQLite, Qt4, Beautiful Soup 4 - Word and Movie guessing games that use data scraped from IMDB and Barron's GRE Wordlists.