Industry Experience

Twitter, Timelines Quality, PhD Intern, Summer 2016

Worked on Timelines team responsible for ranking tweets in the timeline. Developed deep learning models to predict user engagement with tweets using history of user interaction.

Facebook, Data Infrastructure, PhD Intern, Summer 2014

Worked on Scuba, a real-time analytics system at Facebook with write rate >1M/s. Developed and evaluated multiple solutions that scaled to high write rates to make the accounting service used by Scuba persistent and reliable.

Google, Dynamic Search Ads, Software Engineering Intern, Summer 2013

Develop prototype geo-targeting system that used 2-level classification based on page-clicks to predict whether webpages required geo-targeting and for those requiring geo-targeting, to predict the location of targeting.

Microsoft, Automation and Accessiblity, Software Engineer, 2010-2011

Extended and maintained UI Accessibility and Automation framework. Drove part of new accessibility module for Internet Explorer. Received promotion in six months

Leadership Experience and Service

Project Lead, ModelDB. MIT CSAIL, 2016 - 2017

Envisioned and led development of open-source ModelDB tool to manage machine learning models. Supervised team of 6 students to build and release an end-to-end tool.

MEng thesis mentor, ModelDB. MIT CSAIL, 2016 - 2017

Mentored three MIT EECS MEng students on their master theses.

Mentor, Open-source Entrepreneurship. MIT CSAIL, 2017

Mentoring a team of three students on developing ModelDB into a widely used open-source tool.

Peer Mediator, REFS @ MIT EECS, 2017

Peer mediator and informal counsellor trained in conflict management. Serve at first line of resources for various personal and professional situations for graduate students in EECS.

Teaching Assistant, CSAIL, MIT 6.830, Fall 2015

Responsible for creating and grading problem sets and labs, holding office hours and answering questions on Piazza.

UROP Mentor, MIT CSAIL, Summer 2015, Spring 2014

Mentored undergraduate students doing research on data visualization, in particular, SeeDB.

Mentor, MIT Media Lab ReDX Workshop, 2015

Mentored a team of 8 undergraduate and graduate students for building a next generation waste sampling device.

Organizing Team Member, MIT Global Startup Workshop 2015, Guatemala

Organizing Team Member and Event lead for panels on Entrepreneurship in Agriculture and Hacking Politics. Worked with a co-lead to identify and invite speakers and manage event logistics.

Co-President, Graduate Women in EECS (GW6) 2014

Responsible for organizing career development events and social activities for graduate women in EECS. Started a coffee hour series involving a diverse set of women in technical roles.

Teaching Assistant, Tackling Challenges of Big Data, MIT Professional Education 2014

Responsible for monitoring online forums and answering student queries for this 400-student online course.

Executive Board Member, Conference Co-chair, Graduate Women at MIT (GWAMIT) 2011-2013

As executive board member in 2013, managed the marketing, publicity and branding of GWAMIT including social media, blog, website and publicity for conferences. In 2012 and 2013, co-chaired the Spring Empowerment Conference. Led team of 15 for planning all events, talks and logistics for GWAMIT’s flagship 5-day conference with 550+ attendees.

Side Projects and Startup Experience

Core Team Member, EveryBiome, 2014-2015

Part of an interdisciplinary team (bioengineering, mechanical engineering, EECS, design and computer science) at MIT building devices for continous and longitudinal monitoring on GI diseases, specifically IBD. Our team designed and built two (patent-pending) devices and companion apps to passively collect stool samples in the home and monitor GI health. Along with contributions to device and app design, performed primary market research and customer interviews to understand problems faced by patients with Ulcerative Colitis and how our device could enable better management of the disease.

Core Team Member, Asorti, 2012-2013

Led 3-person all-MIT team to develop clothing recommendation software based on the combination-based recommendation research. Built web and mobile prototype using clothing data from three retailers. Ran user study showing that combination-based recommendations increase conversion for clothing purchases, and that shoppers explore more items with these recommendations. Conducted market research to understand needs of both, customers and retailers, to design the best recommendation system.