
News
- [May 22] Started summer internship at Amazon Fashion as an Applied Scientist.
- [Jan 22] Working with Prof Zsolt Kira on label-efficient frameworks.
- [Nov 21] ‘Recommendation of Compatible Outfits Conditioned on Style’ accepted for presentation for the ECIR’22 Full Paper track!
- [Oct 21] Fashion Compatibility accepted for demo at CODS-COMAD 2022!
- [Aug 21] Working as Graduate Research Assistant with Prof. Devi Parikh.
- [Aug 21] Starting MS in CS (Specialization in Machine Learning) at Georgia Tech.
- [Jul 19] Starting as a Data Scientist at Flipkart responsible for recommendations.
Bio
I am a second year MS Student in the department of Computer Science at Georgia Institute of Technology, advised by Prof. Zsolt Kira and Prof. Devi Parikh. Before that I was a Data Scientist at Flipkart in the Recommendations team supervised by Dr. Aditya Rachakonda, Dr. Arnab Bhattacharya and previously by Samik Datta. Prior to joining Flipkart, I completed my undergrad at IIT Delhi advised by Dr. Prathosh AP.
Broadly my interest lies in Computer Vision, Vision + Text, Creative AI. I strongly believe that technology benefits human society and has a lot of potential to improve human lives.
For about an year, I also volunteered my time with DSIndiaVsCovid mentored by Dr. Srujana Merugu, Dr. Mohit Kumar and Dr. Alpan Raval.
My CV is available here.
I am looking for full time research or applied ML roles starting May 2023
Publications and Preprints
* Equal contribution
Recommendation of Compatible Outfits Conditioned on Style
ECIR'22 (oral)
CODS-COMAD 2022 Demo track
Project Page
ECIR Paper
arXiv
CODS-COMAD Demo Paper
CoSIR: Optimal control of SIR epidemic dynamics by mapping to Lotka-Volterra System
ICLR'21 MLPCP Workshop, CHIL'21 Workshop
Paper
Code
Demo
Poster
A Flexible Data- Driven Framework for COVID-19 Case Forecasting Deployed in a Developing- world Public Health Setting
AI for Social Impact book
Paper
Complete Book
Adaptive COVID-19 Forecasting via Bayesian Optimization
Audience Creation for Consumables - Simple and Scalable Precision Merchandising for a Growing Marketplace
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