I graduated from Stanford University with an MS in Computer Science and an MS in Management Science & Engineering. At Stanford, I had the chance to work in the AI labs of Professors Andrew Ng and Silvio Savarese, as well as in the Bioengineering lab of Professor Manu Prakash. When not in the lab, I spend my time working on startup projects and teaching. I care about improving the way people get informed about what’s happening in the world. If you share this interest, let’s connect!

Research Publications

Octopi: Open configurable high-throughput imaging platform for infectious disease diagnosis in the field
Hongquan Li, Hazel Soto-Montoya*, Maxime Voisin*, Lucas Fuentes Valenzuela*, Manu Prakash.
In submission
preprint

Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning
Maxime Voisin*, Yichen Shen*, Alireza Aliamiri, Anand Avati, Awni Hannun, Andrew Ng
Accepted at KDD 2019 (oral presentation)
blogpost, paper

CAR-Net: Clairvoyant Attentive Recurrent Network
Amir Sadeghian, Ferdinand Legros*, Maxime Voisin*, Alexandre Alahi, Silvio Savarese
Accepted at ECCV 2018
paper

An Improved Training Procedure for Neural Autoregressive Data Completion
Maxime Voisin, Daniel Ritchie
Accepted at NIPS 2017 Workshop for Bayesian Deep Learning
paper

Industry Experience

Deep Learning intern, Apple, 2017
Worked on deep reinforcement learning applications

Data Science intern, Dataiku, 2016
Implemented machine learning models to classify human activity based on accelerometer data
Awarded 2nd prize in online machine learning competition (DrivenData, 580 participants)
blogpost

Teaching

Teaching Assistant for graduate students in Computer Science at Stanford University.
CS229: Machine Learning (Fall 2017) with Professors Andrew Ng and Dan Boneh
CS161: Algorithms (Winter 2016) with Professor Gregory Valiant
CS265/CME309: Randomized Algorithms and Probabilistic Analysis (Fall 2016) with Professor Gregory Valiant