Experience

Amazon A9 Search: Rufus AI Shopping Assistant
(Jan 2023 - current)
• Large scale distributed training, training LLMs from scratch
• Optimizations for low-latency, high-throughput LLM inference
• Controllable text generation
• Official release video and official release announcement

Amazon A9 Search
(Jun 2021 - Dec 2022)
• Large scale multilingual, multimodal model training

Amazon Go: Dash Cart
(Jul 2019 - Jun 2021)
• Algorithms team for the Dash Cart project
• On-device machine learning: computer vision, sensor processing, indoor navigation
• Official product page and product review.

Master's in Computer Science at University of Massachusetts, Amherst
(2017 - 2019)
• Internship: Interaction and Analytics Lab at Xerox Parc
• (Summer, 2018) Techniques few-shot learning, training object detectors with limited labeled data
• Mentor: Bob Price

Bachelor's Degree in Computer Science at VIT University
(2013 - 2017)
• Internship: Intel, Bangalore
• (2017, 6 months) Real-time classification and segmention of hyperspectral images
• (Summer, 2016) Drive quality and event analysis with accelerometer, gyroscopic data
• Mentors: Anbumani Subramanian, Subramanian Chidambaram
• Internship: Stride AI
• (Summer, 2015): Anaphora, coreference resolution.

Papers

The Spectral Bias of the Deep Image Prior
Prithvijit Chakrabarty , Subhransu Maji
Bayesian Deep Learning Workshop, NeurIPS 2019 Code Poster

Automatic adaptation of object detectors to new domains using self-training
Aruni RoyChowdhury, Prithvijit Chakrabarty, Ashish Singh, SouYoung Jin, Huaizu Jiang, Liangliang Cao, Erik Learned-Miller
CVPR 2019 Project page Code

On Optimizing Human-Machine Task Assignments
Work done as a part of the Aspiring Researcher Program (2016), with Prof. James Davis at UC Santa Cruz and Rajan Vaish

Reading List

I like reading books: Reading List

Projects (old)

Codeberg

Course projects

Selectively Forgetting Tasks with Elastic Weight Consolidation for Continual Learning Report Code
Thompson Sampling for Contextual Bandits Report

Personal

Simulations on attractor networks for memory Code
Exercise: Annealed Importance Sampling Code Video
Hand tracking with autoencoders Demo Code
Graph centrality to find main movie characters Demo Code Blog post
CNN for face detection Demo Code
Human tracking with SVMs Demo Code
Sentiment analysis with Convolutional Neural Networks Code and documentation
3D mapping with ultrasonic sensors Video Code Documentation
Beeble: A collaborative Android drawing app Video Code
A visual music player in Processing Code
Po: Simple MapReduce in C Code
Graph plotter Code
Flashcards Code

GitHub gists

Fun (very old)

PC build
Music: I formally studied music theory and play the violin. I also play the guitar, piano and the harmonica.
The big bad bottle wheel! Video
Thoughts on TempleOS Video
Very old snippet on graphs
Emotional article I wrote in school