I am currently enrolled in my 2nd year as a master’s student in Computational and Mathematical Engineering (ICME) at Stanford University, specializing in AI. I also have a MS in Applied Mathematics from the Ecole polytechnique (France) where I minored in physics.
I am particularly interested in Natural Language Processing and AI. I have a lot of experience in python and TensorFlow (see for instance my seq2seq implementation).
I worked with the SLAC machine learning group during Winter 17 on applying computer vision techniques for cluster-splitting in ATLAS. I also did a research internship on NER at Proxem and a research project with Riminder on chatbots. Since September 17, I’m working with the Stanford Machine Learning Group on the Error-Correction task.
During Winter 17, I was a TA for CS224n: Natural Language Processing with Deep Learning taught by Christopher Manning and Richard Socher. I was in charge of lecture notes, accessible here.
During Spring 17, I was a TA for CS234: Reinforcement Learning taught by Emma Brunskill. In particular, I developed the assignment on Deep Reinforcement Learning.
During Fall 17, I was a TA for CS229: Machine Learning taught by Andrew Ng and Dan Boneh. In particular, I wrote the lecture note on Linear Quadratic Regulation.
I am currently TAing CS230: Deep Learning, taught by Andrew Ng and Kian Katanforoosh, that follows deeplearning.ai to which I contributed by writing one of the assignment.