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Scientific American


Andre Esteva is a researcher and entrepreneur in deep learning and computer vision. He has co-founded two startups and obtained four advanced degrees.

He obtained his PhD in Artificial Intelligence at Stanford, advised by Sebastian Thrun and co-advised by Stephen Boyd, authoring 11 publications which have been cited over 2300 times and covered by over 200 news outlets. His research was in deep learning and computer vision, with applications built for dermatology, drug screening, neuroscience, and psychiatry.

Notably, his work showed that computer vision algorithms could match the performance of dermatologists at classifying skin cancer from images. His work has made the cover of Nature, as well as Cell, Nature Medicine, NeurIPS, and other venues. It has been widely covered by the WSJ, Fortune, BBC, The Economist, and similar news outlets. He interned at Google Research, Sandia National Labs, and GE Healthcare.

He finished undergraduate degrees with highest honors in Electrical Engineering and Pure Math from UT-Austin and was awarded Engineering Valedictorian (formally, the Outstanding Scholar-Leader Award).


A Guide to Deep Learning in Healthcare
Andre Esteva*, Alexandre Robicquet*, Bharath Ramsundar#, Volodymr Kuleshov#, Katherine Chou#, Mark DePristo#, Claire Cui, Greg Corrado, Sebastian Thrun, Jeff Dean
*equal contribution authors
#equal contribution authors
equal contribution authors
In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images
Eric Christiansen*, Samuel Yang, Dale Ando#, Ashkan Javaherian#, Gaia Skibinski#, Scott Lipnick,#, Elliot Mount, Alison O’Neil, Kevan Shah, Alicia K. Lee, Piyush Goyal, Liam Fedus, Ryan Poplin, Andre Esteva, Lee Rubin, Philip Nelson*, Steven Finkbeiner*
#These authors made comparable contributions
These authors made comparable contributions
Artificial Intelligence in Healthcare and Medicine: Enhancing the Expert
Andre Esteva
PhD Thesis
Dermatologist-level Classification of Skin Cancer with Deep Neural Networks
Andre Esteva*, Brett Kuprel*, Rob Novoa, Justin Ko, Susan M. Swetter, Helen Blau, Sebastian Thrun
*equal contribution authors
Skin Cancer Detection and Tracking using Data Synthesis and Deep Learning
Yunzhu Li*, Andre Esteva*, Brett Kuprel, Rob Novoa, Justin Ko, Sebastian Thrun
*equal contribution authors
Vision-Based Classification of Developmental Disorders using Eye Movements
Guido Pusiol, Andre Esteva, Scott Hall, Michael Frank, Arnold Milstein, Li Fei-Fei

Visual Scenes are Categorized by Function
Michelle Greene, Christopher Baldassano, Andre Esteva, Diane M. Beck, Li Fei-Fei

Two Distinct Scene Processing Networks Connecting Vision and Memory
Christopher Baldassano, Andre Esteva, Diane M. Beck, Li Fei-Fei

On the Technology Prospects and Investment Opportunities for Scalable Neuroscience
Thomas Dean, Biafra Ahanonu, Mainak Chowdhury, Anjali Datta, Andre Esteva, Daniel Eth, Nobie Redmon, Oleg Rumyantsev, Ysis Tarter

Metamaterial Structural Design
Andre Esteva, Dean Neikirk, Andrea Alu
Undergraduate Thesis

Invited Talks



Co-Founder @ Cresta Intelligence
Oct 2017 - Jan 2019
Cresta is an enterprise AI startup with a mission of building AI coaches (using NLP & RL) designed to turn normal sales agents into experts very quickly, by coaching them on what to do and say as they're speaking with customers.
Entrepreneur-in-Training @ Venture Capital Firms
May 2017 - September 2017
Charles River Ventures
Sequoia Capital
Greylock Partners
Participated in various summer programs with venture capital firms, designed to train PhD students in entrepreneurship.
Innovation Scholar @ Accel Ventures
September 2015 - September 2016
Startup Consultant, Entrepreneur-in-Training
Hosted by Accel Partners
Led by the Stanford Technology Ventures Program
Intern @ Google Research
June 2015 - September 2015
Accelerated Science Team
Deep Learning applied to image-to-image regression for large-scale drug screening
Intern @ Sandia National Laboratories
May 2011 - July 2012
Computational Nuclear Fusion
Computational Metamaterials for Invisibility Cloaking
Intern @ GE Healthcare
May 2009 - August 2009
X-ray Imaging Team
UI Design for X-ray data analysis