Devashish Prasad



About me



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Hi there

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I have strong enthusiasm for Machine Learning, Deep Learning, and Computer Vision.

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Pursuing Master of Science in Computer Science from Purdue University. Completerd my Bachelor of Engineering in Information Technology with an overall CGPA of 9.6.

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Published two research papers both in the ML/DL domain, one of which published at the CVPR 2020 conference (the topmost computer science conference in the world).

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One of my open-sourced Github repositories has 1000+ stars and 350+ forks. Planning to build more such projects.

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Completed six internships, all of which in the ML/DL domain. Consistently worked on solving challenging industry and business problems with ML/DL.

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Reached three times at the Smart India Hackathon (India's largest Hackathon) grand finale. Built ML/DL-based projects of ISRO, ITC ltd, and DRDO (India's esteemed organizations).

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Recently started with Kaggle. Trying to gain experience and medals.

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Spend my free time on stackoverflow.com and datascience.stackexchange.com. And write some blogs (feynman technique).







Work Experience



Research Assistant

Kihara Lab @ Purdue University

Aug 2022 – Present, West Lafayette, Indiana, USA

  • Deploying deep learning models for analyzing protein structure information from cryo-EM maps.
  • Working closely with Professor Daisuke Kihara and his students to build better deep learning models.

Machine Learning Engineer Intern

Snap Inc.

May 2022 – Aug 2022, Los Angeles, California, USA

  • Researched and developed an Optical Flow-based solution to get pseudo labels for videos.
  • Built a single model that works with all key-point prediction tasks (face tracking, hand tracking, etc.).
  • Enhanced the algorithm using self ensemble techniques to generate jitter-free (smooth motion) labels.
  • Novel fine-tuning resulted in 2x accuracy and 15% faster labeling.
  • Deployed the solution in Snap’s internal (web app) using GCP-based Kubernetes backend and TF JS.

Graduate Data Science Researcher

Viasat (The Data Mine)

Aug 2021 – May 2022, West Lafayette, Indiana, USA

  • Investigated and researched various techniques for Image and Video Super-Resolution (SR).
  • Carried out experiments to compare various recent and past prominent works in Blind Image SR.
  • Thoroughly studied and prepared a detailed literature survey of various seminal works in Blind Image SR.

Machine Learning Intern

Pirimid Fintech

Nov 2020 – Mar 2021, Ahmedabad, Gujarat, India

  • Built robust Credit Scoring System using AI called Early Warning System (EWS) for banks.
  • EWS predicts various kinds of risk signals associated with a Loan throughout its life cycle.
  • EWS is trained on financial, news, social media, economic, industrial, historical, etc data.
  • Developed NLP based system (POC) that predicts company insolvency with an accuracy of 30 days.

Research and Development Intern

OrbitShifters

Jun 2020 – Aug 2020, Pune, Maharashtra, India

  • (www.sportsvision.ai) Computer Vision-based Sports Analysis for combat sports like boxing.
  • Built models for Pose tracking and Fine-grained Action recognition in boxing match videos.
  • Trained models on the USA Olympics boxing match video dataset and deployed the system.

Research Assistant (Dr. R. B. Ingle)

VEM Tooling Group

Jul 2019 – May 2020, Pune, Maharashtra, India

  • Used Computer Vision-based techniques to extract 3D dimensions of objects.
  • Designed and developed a working prototype system.
  • Carried out the research that involved exploring and implementing various approaches.
  • Also developed a solution to reconstruct a 3D model from the given 2D images of an object.

Deep Learning Intern

AP Analytica

Oct 2019 – Jan 2020, Pune, Maharashtra, India

  • Built an Automatic Image-based Invoice Parsing System.
  • Used deep learning-based techniques to extract information from images of invoices.
  • Developed text recognition algorithms to extract various invoice fields from the invoice image.
  • Developed deep learning-based robust table detection and recognition algorithm.

Machine Learning Intern

Tribbinanis Software Solutions

Jun 2019 – Aug 2019, Ahmedabad, Gujarat, India

  • Real-time face recognition-based automatic attendance system.
  • Automatic License plate detection and recognition system
  • Benchmarked and tested various deep learning-based techniques.

Software Intern

Kneo Automation

Apr 2017 – Aug 2018, Pune Area, India

  • Designed Image processing and ML/DL-based solutions for the manufacturing industry.
  • Contributed to IoT, Full-stack development, and hybrid mobile application projects.
  • Designed web-based frontends for applications.


Education



Purdue University

Master of Science in Computer Science

2021 – 2023, West Lafayette, Indiana, USA

GPA - 3.43/4.0

  • Worked on as a Graduate Data Science Reseacher for Viasat (The Data Mine).
  • Worked on as a Research Assistant under Prof. Daisuke Kihara

Pune Institute of Computer Technology

Bachelor of Engineering in Information Technology

2018 – 2021, Pune, Maharashhtra, India

CGPA - 9.6/10.0

  • Published 2 international research papers
  • 2 Times Smart India Hackathon Finalist
  • Presented ideas at Google DevFest and Startup and Innovation cell
  • Served as Technical Head at PICT CSI Student Branch
  • College Football Team (Reliance Cup)

Government Polytechnic Pune

Diploma in Computer Engineering

2015 – 2018, Pune, Maharashhtra, India

Percentage - 90.5/100.0

  • Smart India Hackathon Finalist
  • College badminton team (State level winner)
  • College Football team (Zone Runner Up)
  • Department Basketball team (Inter dept Runner Up)



Achievements



Winner D. K. Bhave Scholarship worth USD 6700, by Savitribai Phule Pune University 2021

Finalist Smart India Hackathon 2020, 2019 and 2018 (India’s Biggest Hackathon)

Winner PICT Internal hackathon for SIH 2020

Winner Kaggle in-class competition, Credenz Datawiz 2019 at PICT

Runner Up Paper presentation competition, INC (Pratibha) 2019 at PICT

Runner Up Social Hackathon, Pasckathon 2019 at PICT

Winner Web App development competition, Pulzion 2018 at PICT

Top 2 from PICT in SPPU's cluster level i-2-e startup and innovation competition 2019