About me

I love collecting and analyzing how all my personal data (including fitness, nutrition, sleep, location history, and more) interact with one another. To that end, my personal goal is to improve everyone’s daily lives by combining all their data and helping them make sense of it. To pursue this goal further, I am studying Computer Science (with a focus on Machine Learning) in the Master of Engineering program at UC Berkeley.

Over Summer 2019, I interned at a startup as a Machine Learning Engineering Intern and trained image classification models in TensorFlow to predict a hospital bed’s patient-occupancy score. I collected training data by scraping images and converting YouTube videos using my OpenCV-based video annotation tool. I also generated 40k randomized synthetic training images after learning to use Blender. I improved my model using computer vision techniques with transfer learning on InceptionV3.

The MEng program focuses extensively on technical leadership in the industry and so, I am taking courses about Machine Learning, Deep RL, and ML Systems. In Fall 2019, I am researching traffic light coordination using Deep RL.

In 2017, I published an iOS app called Drinks Tracker on the App Store based on an observation that I made a couple of years ago during my undergraduate years at The Ohio State University. In early 2018, I was working on integrating drink suggestions using machine learning in my app (to automatically suggest drinks to users based on their preferences and drink history) when Apple removed this category of apps from the App Store.

My current fitness goal is to complete a 7.5 mile run in an hour. Currently, I am two minutes away from making it!

In my spare time, I enjoy watching movies and TV, especially science fiction classics such as Star Trek and Doctor Who. 🖖

After I graduate in December 2019, I want to work as a Machine Learning Engineer, ideally in the Bay Area, to make better use of all the data that we generate every day.

Currently researching traffic light coordination using Deep Reinforcement Learning

with Prof. Alexandre Bayen

August 2019 – present

Artificial Intelligence to improve City-scale Traffic Flow

Researched how to reduce mixed-autonomy traffic congestion using Deep Reinforcement Learning

with my Capstone team and Prof. Alexandre Bayen

2018 – 2019

Optimized the behavior of autonomous vehicles to increase average traffic speed in a city-scale scenario

Worked in a team to use and improve an open-source traffic control framework called Flow that works with SUMO (traffic simulation software) and RLlib (reinforcement learning Library)
Drinks Tracker

Published an iPhone app on the iOS App Store

Drinks Tracker

2017 – 2018

App uses an algorithm to notify the user about their estimated Blood Alcohol Content (BAC) level

Created a custom algorithm that calculates the user’s BAC level based on multiple metrics

Installed by 3.9k+ users with 104k+ impressions

Completed the Machine Learning by Stanford course

Taught by Andrew Ng, Co-founder, Coursera and Adjunct Professor, Stanford University

Spring 2017

Meeting assistant

Created a voice-based meeting assistant as our Capstone team project

for PureCloud by Interactive Intelligence

Spring 2016, The Ohio State University

Analyzed speech during video calls to automatically create meetings in Google Calendar

Worked with the IBM BlueMix, Google Cloud Speech, and Google Calendar APIs

Analyzed and summarized the text of a diverse collection of Reuters articles in Python

Spring 2016, The Ohio State University

Used Beautiful Soup 4 and scikit-learn to implement several clustering and classification algorithms such as DBSCAN, Hierarchical Clustering, Naïve-Bayesian, and K-Nearest Neighbors

Calculated Jaccard Similarity scores and Mean Squared Error to accurately create association rules

Developed several Android apps as part of coursework

integrated with the Twitter, Google Calendar, and Google SafeSearch APIs

2015 – 2016, The Ohio State University

'Best Lifesaving Hack’'

Won Best Lifesaving Hack at Qualcomm’s intern hackathon for an Augmented Reality app

Summer 2015, Qualcomm

Created an Android app to visualize sound to assist the hearing impaired

Organized philanthropic and cultural events for 300+ people

as Webmaster and Chief of Staff (Indian Students Association)

2013 – 2016, The Ohio State University

Aaj Ka Dhamaka


Fall 2013, University of North Carolina

Advanced Energy Vehicle project

Model Monorail

Spring 2013, The Ohio State University

Machine Learning Engineering Intern

LookDeep Health

Summer 2019, Oakland, CA

Trained image classification models to predict a hospital bed’s patient-occupancy score

Built my model’s training pipeline in TensorFlow 2 and learned to use DVC, an open-source model versioning system

Collected training data by scraping images and converting YouTube videos using my OpenCV-based video annotation tool. Also used and contributed to Scalabel, an open-source annotation tool

Generated 40k randomized synthetic training images after learning to use Blender

Improved my model using computer vision techniques with transfer learning on InceptionV3 and ResNet-152

Assisted another intern in developing the end-to-end system from reading images off the camera to serving predictions using TensorFlow Serving and displaying the output inference in the browser

Software Engineer (Full Stack)

OCLC (Online Computer Library Center)

2016 – 2018, Columbus, OH

Wrote Java code while updating 7 legacy webapps, used by 15k+ administrators for library management (books, media, etc.), to use jQuery, PostgreSQL, and Apache Tomcat

Enhanced OAuth authentication services used by OCLC’s enterprise partners to support mobile apps

Supported a $3M+ contract by writing utilities to easily internationalize a webapp in 20+ languages

Optimized database handling and functionality for compliance with GDPR requirements

Built and deployed our webapps to several QA and Production environments

Interim Engineering Intern

Interim Engineering Intern

Summer 2015, San Diego, CA

Improved my internal webapp from 2014 and created new features to automate tasks for other team members

Automated tasks using C# to internalize SQL scripts into an ASP.NET application

Interim Technology Intern


Summer 2014, San Diego, CA

Overhauled an internal webapp used to manage a portal which simplified doctor-patient communication

Resolved and implemented requested user stories to increase operational productivity

Made extensive use of ASP.NET, SQL, HTML5, and JavaScript while collaborating with other team members using Team Foundation Server in Visual Studio

The Ohio State University

CSE Help Desk Operator

2014 – 2016, Columbus, OH

Assisted Computer Science professors, faculty, and students with their technical queries and issues

Replied to any queries sent to diligently and in a timely manner

Printed posters for graduate students

Ensured that all the CSE printers (~20) are working at all times with no paper and ink issues

ICICI Prudential AMC Ltd.

IT Intern

Summer 2010, Mumbai, India

Gained experience programming in work environment

Primarily programmed in ASP.NET and C#

Created websites for inputting and recalling user details

Worked in Microsoft Access to create databases to store user details
Drinks Tracker

Drinks Tracker

Drinks Tracker allows you to search a list of nearly 4,000 drinks and easily add drinks to track your Blood Alcohol Content (BAC) percentage.

Installed by 3.9k users with 104k impressions

Not currently available

Drinks Tracker Drinks Tracker Drinks Tracker Drinks Tracker Drinks Tracker Drinks Tracker Drinks Tracker Drinks Tracker Drinks Tracker Drinks Tracker


  • Search and easily add drinks. Favorite your frequent drinks for easy access!
  • Track your BAC using the Today View widget and the Apple Watch app. Complications and Dynamic Notifications are coming soon!
  • Easily add custom drinks and favorite them in a few taps.
  • Get notifications when your BAC is at 0.08% and 0% and a reminder to add your next drink.
  • Customize your profile to get an estimated BAC tailored to you!
  • 3D Touch the app icon to quickly add a drink and to see your BAC in the widget.
  • Suggest drinks so that they can be added to the list!