Bio. I’m currently interning at Google Brain Robotics working at the intersection of robotic perception and manipulation. My research centers around Deep Learning and its applications to Robotics and Computer Vision. In particular, I'm interested in creating machines that self-supervise and improve over time through their interaction with the physical world. I'm driven to build things that will have positive impact at scale.

Last summer, I interned at Nimble AI where I built the infrastructure for training and deploying various real-time grasping algorithms for suction and parallel-jaw grasping. Before that, I was a visiting researcher in the Khuri-Yakub Ultrasonics Group at Stanford University, applying machine learning to enhance ultrasonic transducers like a chemical nose and a touch screen.

Outside of work I enjoy contributing to open source and blogging.


April 2019 - I’ll be attending Stanford University in September 2019 to begin my master’s degree in Computer Science.
Feb 2019 - July 2019
Google Brain Robotics Intern
3D Perception and Manipulation
Summer 2018
Nimble AI Robotics Intern
Robotic Manipulation
Summer 2017
Stanford University Khuri-Yakub Group
Machine Learning for CMUTs
American University of Beirut
B.Eng. Electrical Engineering


A general-purpose library for robotics research.
Tune the hyperparameters of your PyTorch models with a HyperBand implementation.
A Python API for the PhoXi 3D stuctured light sensors.
A Tensorflow implementation of Spatial Transformer Networks accompanied by a two-part tutorial series.
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A processor in Verilog that computes the L2 norm of an N-dimensional complex vector stored in doubly-linked list. Features nifty Python scripts to automate the reading and writing of test benches.