Shreyas Chaudhari

Shreyas Chaudhari

PhD Student in Computer Science

University of Massachusetts Amherst

About Me

I am a first-year PhD student in Computer Science at UMass Amherst advised by Bruno Castro da Silva and Phil Thomas at the Autonomous Learning Lab. I received my master’s degree at Carnegie Mellon University from the Electrical and Computer Engineering Department. I completed my undergraduate studies from the Department of Electrical Engineering at the Indian Institute of Technology Madras.

My research interests lie broadly in the field of reinforcement learning and various machine and deep learning tools and concepts. I have also worked on various related areas like natural language processing and multi-armed bandits amongst others, details about which can be found in the Projects section. My interests motivated me to acquire industrial experience in autonomous-driving and financial sectors through internships at Uber ATG and Goldman Sachs respectively.

In my free time, I love to read, run and play soccer. As an undergraduate student, I was a member of the institute athletics team at IIT Madras.


  • Artificial Intelligence
  • Reinforcement Learning
  • Deep Learning


  • PhD in Computer Science, Ongoing

    University of Massachusetts Amherst

  • MS in Electrical and Computer Engineering, 2020

    Carnegie Mellon University

  • B.Tech. in Electrical Engineering, Minor: Machine Learning, 2019

    Indian Institute of Technology Madras

Professional Experience


Software Engineering Intern

Uber ATG, Perception/Prediction Team

Jun 2020 – Aug 2020 Pittsburgh
  • Derived loss functions for confidence-calibrated neural network predictions for image classification and object detection
  • Shifted from two-step post-processing calibration methods, benchmarking one-stage object detectors (FAIR’s RetinaNet)
  • Achieved improved calibration scores on image classification along with occasional improvement in model performance [informal report]

Securities Strategist Intern

Goldman Sachs, Franchise Analytics Strategy & Technology Team

May 2018 – Jul 2018 Bengaluru, India
  • Analyzed the trade data for European markets post MiFID II regulation, gauging the monetary value of the dataset
  • Conducted trade volume and market share driven analysis indicating ∼40% increase in market coverage by the data
  • Modeled quoting patterns with GMMs using pre-trade data feed to draw correlations across aggressiveness of quoting

Machine Learning Intern

DeTect Technologies, Machine Learning Team

May 2016 – Jul 2016 Bengaluru, India
  • Developed code for the flagship product GUMPS which detects defects and their growth rate in oil refinery pipelines
  • Implemented idea analyses reflected waveforms of ultrasound waves for defect detection



Off-Dynamics Reinforcement Learning

Research project, CMU

Multi-Armed Bandits with Correlated Arms

OPAL lab, Carnegie Mellon University

Classical Bandit Algorithms to the Structured Bandit Setting

OPAL lab, Carnegie Mellon University

Energy-Delay-Distortion Problem

Tata Institute of Fundamental Research, Mumbai