I am a senior robotics researcher at Waymo. I received my PhD in Computer Science from UCLA where I was a member of the Automated Reasoning Group. My doctoral dissertation introduced decomposition techniques to learn probabilistic graphical models from data more efficiently. I was honored to receive the Northrop-Grumman Outstanding Research Award. Before UCLA, I visited LAAS-CNRS France where I enjoyed working with Dr. Pierre Emmanuel Hladik on stochastic analysis of real-time systems. Before that, I completed a Masters in computer engineering at Cairo University Egypt where I was extremely lucky to work with Prof. Amir Atiya. I was also a teaching assistant and a part-time research engineer at IBM.
I have an opening for one research intern for summer 2018 to work on cutting-edge machine learning research for self-driving cars.
I gave a talk on self-driving cars at UCLA.January 2018
I am serving as a PC member for IJCAI 2018.November 2017
Waymo annouced the first self-driving fleet in the world: video.November 2017
I gave a talk on deep learning at UCLA.November 2016
A new paper is accepted for plenary presentation at UAI 2015.May 2015
I won the Northrop-Grumman Outstanding Research Award.May 2015
I defended my thesis.April 2015
A new paper is accepted at IJCAI 2015.April 2015
The slides of the ITA talk are now available here.February 2015
I gave a graduation day talk at ITA.January 2015
I am teaching cs32 this quarter.January 2015
A new paper is accepted at NIPS 2014.September 2014
I received a Student Ambassador honorarium from UCLA.February 2014
A new paper is accepted at NIPS 2013.September 2013
I received a masters from UCLA.Jan 2013
I am a winner of the first Procter & Gamble Graduate Seminar competition at UCLA.November 2012
A new paper is accepted at the Big Learning NIPS workshop 2012.November 2012
EDML was presented in SoCaML 2011.September 2011
A new paper is accepted at UAI 2011.July 2011
My research interests are in:
I am particularly interested in the design and analysis of highly efficient and accurate deep models which are trained using supervised, reinforcement or imitation learning. On the practical side, I focus on the development of efficient and theoretically sound reasoning algorithms that can work in real-time.