Experience
DoorDash - Member of Technical Staff
August 2024 - Present. Gen AI & Voice AI.
Booth AI - Co-Founder & CEO
April 2022 - August 2024. Founded the Gen AI startup Booth.ai & raised $3M+ from Y-Combinator & other top VCs. Built cutting-edge generative AI solutions for professional product photography.
Standard Cognition - Director of Engineering
May 2018 - April 2022. Joined as employee #7 and helped scale to unicorn status. Led Machine Learning teams, drove key ML product launches, and landed 10+ models in production for autonomous retail.
Symantec - Deep Learning Consultant
November 2016 - November 2017. Built deep learning systems for dynamic cyber threat and insurance modeling.
MIT - Graduate Researcher
July 2016 - June 2017. Published 2 Machine Learning papers and founded/lectured MIT’s Deep Learning course, 6.S191.
Pinterest - Machine Learning Engineer
Worked on Recommendations team building machine learning models with big data pipelines. Ran user-facing experiments on Re-Ranking Homefeed using Facebook data signals. Built internal debug tool for our machine learning ranking models.
Fitbit - Software Engineer
Worked on iOS team. Leveraged runtime meta programming to implement property-based wrapper for NSUserDefaults. Worked on experimental Notifications Center Widget.
Publications
Fundamentals of Deep Learning (O’Reilly Book)
With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts in this complicated field.
Large companies such as Google, Microsoft, and Facebook have taken notice, and are actively growing in-house deep learning teams. For the rest of us however, deep learning is still a pretty complex and difficult subject to grasp. If you have a basic understanding of what machine learning is, have familiarity with the Python programming language, and have some mathematical background with calculus, this book will help you get started.
Journal of Radiology 2017. Paper here. MIT News.
Neural Generation of Regular Expressions from Natural Language with Minimal Domain Knowledge
First Author, EMNLP 2016. Designed and trained novel Deep RNN for generating Regular Expressions given natural language descriptions of the user’s intent. Paper here. Code+Data here.
Teaching
6.S191: Intro to Deep Learning
Founded and taught MIT’s first course on Deep Learning and TensorFlow with sponsorship from Google Brain, NVIDIA, Amazon Echo, and IBM Watson. Website here. Lecture videos here.
Machine Learning with Scikit-Learn and Tensorflow
Created online video course about Machine and Deep Learning with Packt Publishing. Features full coverage of machine learning concepts from core fundamentals to working implementation.