Samvit Jain

I am a graduate student in computer science at UC Berkeley. I am part of the RISE Lab, where I am advised by Professor Joseph Gonzalez. My research centers on large-scale visual inference, spanning both computer vision (fast image/video recognition) and computer systems (resource-efficient video analytics).

In recent summers, I have interned at Microsoft Research and Databricks. I'm also the founder of video link messaging service LinkMeUp, a mobile app with users in over 70 countries.

I received a BSE with highest honors in computer science from Princeton in 2017.

GitHub / LinkedIn / Twitter
Papers
Scaling Video Analytics Systems to Large Camera Deployments
Samvit Jain, Ganesh Ananthanarayanan, Junchen Jiang, Yuanchao Shu, Joseph Gonzalez
summary / arXiv link

We discuss the potential of spatio-temporal correlations -- content correlations between geographically proximate cameras in wide-area enterprise camera deployments -- to improve cost efficiency and inference accuracy in large-scale video analytics operations. Our template application is real-time person re-identification and tracking.

Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video
Samvit Jain, Xin Wang, Joseph Gonzalez
summary / arXiv link

We present Accel, a novel corrective fusion network that combines two network branches -- a expensive reference branch, executed only on keyframes, and a lightweight, modular, per-frame update branch. Accel achieves the state-of-the-art accuracy-throughput tradeoff curve on semantic video segmentation.

Fast Semantic Segmentation on Video Using Motion Vector-Based Feature Interpolation
Samvit Jain, Joseph Gonzalez
summary / arXiv link

We exploit video compression techniques (in particular, the block motion vectors in H.264 video) and feature similarity across frames to accelerate a classic image recognition task, semantic segmentation, on video.

Determining an Optimal Threshold on the Online Reserves of a Bitcoin Exchange
Samvit Jain, Edward Felten, Steven Goldfeder
Journal of Cybersecurity (JCS), 2018
summary / pdf / github

We investigate the fundamental tradeoff between exposure to online (network-based) and offline threats faced by a Bitcoin exchange that must store Bitcoin across online and offline storage, while guaranteeing availability to customers. Parameterizing deposit, withdrawal, and theft events as Poisson processes, we are able to model the financial dynamics of the exchange, and solve for the optimal threshold on online storage.


Technical Reports
Portal: Micropayments on the Paywalled Internet
Samvit Jain
Princeton Senior Thesis (Advisor: Brian Kernighan), 2017
summary / slides

Portal is a payment protocol and software system that enables one-click purchases of long-form news content on the Internet, without requiring a user to sign up for a subscription or login to a content provider's website.

The payment protocol enables clients to purchase a digital good (e.g. a single news article) via a standard payment mechanism, such as PayPal or a credit card, and then claim the good from the content provider over an unauthenticated HTTP channel by providing a valid proof-of-payment. This proof demonstrates that 1) a payment transaction of sufficient value was issued for the particular good being claimed (article id verification), and 2) the identity of the payer matches the identity of the client claiming the good (user id verification). Our proposed client-side software handles the construction and provision of this proof, taking the place of manual, password-based authentication.

Monetization on the Modern Web: Automated Micropayments From Bitcoin-Enabled Browsers
Samvit Jain
Princeton Junior Independent Work (Advisor: Arvind Narayanan), 2016
summary / pdf / github

We propose and evaluate a software implementation of a Bitcoin micropayments-based revenue system for online businesses, which enables users to make small payments to access web content on a per-use basis, in lieu of viewing ads or signing up for a credit card subscription.