Favyen Bastani

Contact: favyen@perennate.com
Github: uakfdotb

About: I am a PhD student in computer science at the Massachusetts Institute of Technology working with Sam Madden in the data systems research group. [currently on the job market!]

Research: Most recently, my research interests have revolved around the broad goal of empowering more users to be able to leverage machine learning techniques to analyze video. Commercialized or otherwise deployed use cases of ML in video analytics today are typically focused on a narrow range of applications, often of questionable utility, such as privacy-intrusive surveillance and facial recognition. My (perhaps misguided) hope is that, by reducing the effort and expertise needed to implement ML pipelines, we can enable more applications that are beneficial (or at least not detrimental) to society.

Here are some examples of applications of computer vision which people are in fact actively working on that I find compelling, which I think showcase the diversity of what's possible:

Under this goal, my general research interests include:

Publications

MultiScope: Efficient Video Pre-processing for Exploratory Video Analytics. Favyen Bastani, Sam Madden. In submission. [pdf]

Self-Supervised Learning for Multi-Object Tracking. Favyen Bastani, Songtao He, Sam Madden. In submission. [pdf]

SkyQuery: Optimizing Video Queries over UAVs. Favyen Bastani, Osbert Bastani, Songtao He, Arjun Balasingam, Ziwen Jiang, Radhika Mittal, Mohammad Alizadeh, Hari Balakrishnan, Tim Kraska, Sam Madden. In submission. [pdf]

A Self-Supervised Approach for Recognizing Street Map Changes using Satellite Imagery. Favyen Bastani, Songtao He, Satvat Jagwani, Edward Park, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Mohamed Elshrif, Sam Madden, Mohammad Amin Sadeghi. In submission. [pdf]

Vaas: Video Analytics at Scale. Favyen Bastani, Oscar Moll, Sam Madden. VLDB 2020, Demonstration. [web]

MIRIS: Fast Object Track Queries in Video. Favyen Bastani, Songtao He, Arjun Balasingam, Karthik Gopalakrishnan, Mohammad Alizadeh, Hari Balakrishnan, Michael Cafarella, Tim Kraska, Sam Madden. SIGMOD 2020. [pdf] [web]

Sat2Graph: Road Graph Extraction through Graph-Tensor Encoding. Songtao He, Favyen Bastani, Satvat Jagwani, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Mohamed Elshrif, Sam Madden, Mohammad Amin Sadeghi. ECCV 2020. [arxiv]

BeeCluster: Drone Orchestration via Predictive Optimization. Songtao He, Favyen Bastani, Arjun Balasingam, Karthik Gopalakrishnan, Ziwen Jiang, Mohammad Alizadeh, Hari Balakrishnan, Michael Cafarella, Tim Kraska, Sam Madden. MobiSys 2020. [pdf] [web]

RoadTagger: Robust Road Attribute Inference with Graph Neural Networks. Songtao He, Favyen Bastani, Satvat Jagwani, Edward Park, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden, Mohammad Amin Sadeghi. AAAI 2020. [arxiv]

Machine-Assisted Map Editing. Favyen Bastani, Songtao He, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden. SIGSPATIAL 2018. [pdf] [web] [code]

RoadTracer: Automatic Extraction of Road Networks from Aerial Images. Favyen Bastani, Songtao He, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden, David DeWitt. CVPR 2018. [pdf] [web] [code]

RoadRunner: Improving the Precision of Road Network Inference from GPS Trajectories. Songtao He, Favyen Bastani, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden. SIGSPATIAL 2018. [pdf] [web]

Large Scale Real-time Ridesharing with Service Guarantee on Road Networks. Yan Huang, Favyen Bastani, Ruoming Jin, Xiaoyang Sean Wang. VLDB 2014. [pdf] [code]

A Greener Transportation Mode: Flexible Routes Discovery from GPS Trajectory Data. Favyen Bastani, Yan Huang, Xing Xie, Jason Powell. SIGSPATIAL 2011. [pdf]

Code

Vaas is an interactive web application for efficiently analyzing large-scale video datasets. It incorporates tools to annotate video, train machine learning models, and build data flow graphs that implement analytics tasks by composing diverse ML and pre/post-processing operations. See the project website for more details.

RoadTracer aims to improve the accuracy of inferring road networks from satellite imagery through an iterative graph construction procedure. The code is available in Github, with an improved version available here.

gobearmon is a simple but reliable distributed uptime monitoring system that can send alerts over e-mail and SMS when services go offline.