I am Yixuan Li (pronounced as "e-shwen-lee"). I am a Research Scientist at Facebook Research. Before joining Facebook, I finished my Ph.D. in ECE from Cornell University, advised by John E. Hopcroft. My thesis committee members are Kilian Q. Weinberger and Thorsten Joachims. A key focus of my research has been on computer vision and deep learning. Recent projects include deep learning interpretability, optimizing neural networks with efficient computational cost, adversarial training of deep generative models, improving neural network reliability, and theoretical aspect of deep learning.
Prior to Cornell, I graduated from Shanghai Jiaotong University with B.Eng in Information Engineering in 2013. I spent two summers at Google Research Mountain View in 2015 and 2016. I spend summer in 2017 as a machine learning scientist intern at GrokStyle, building cutting-edge visual search technologies with deep learning and computer vision.
I travel and occasionally take photos. Here is my pictorial Travel Memo.
Update (5/16/2018): Selected to speak at Grace Hopper Celebration (GHC) Artificial Intelligence track in September.
Update (5/12/2018): Paper on understanding the loss surface of neural networks accepted into ICML 2018.
Update (4/3/2018): Received CVPR'18 Doctoral Consortium travel award.
Update (3/13/2018): Served on a panel at Facebook's Women in Research Lean In (WiRL) Circle.
Update (1/29/2018): Paper on Neural Network Reliability accepted into ICLR 2018.
Update (11/25/2017): Received ACM-W Scholarship in 2017.
Update (10/16/2017): I will be presenting at Women in Machine Learning (WiML) workshop in December this year.
Update (10/2/2017): Successfully defended my thesis. Slides available here.
Update (9/6/2017): I will be joining Facebook as a full-time Research Scientist in October 2017.
Update (8/5/2017): Selected as one of the Rising Stars in EECS 2017.
Update (6/6/2017): Paper accepted for publication in Transactions on Knowledge Discovery from Data (TKDD).
Update (5/16/2017): I will be speaking at Grace Hopper Celebration (GHC) Artificial Intelligence track in October 2017.
Update (3/12/2017): Received ICLR 2017 Student Travel Award.
Update (2/27/2016): Paper on StackedGAN has been accepted into CVPR 2017.
Update (2/6/2017): Paper on Snapshot Ensembles has been accepted into ICLR 2017.
Update (12/20/2016): My summer internship paper at Google Research is invited to the industrial track in WWW 2017.
Update (2/5/2016): I will be interning at Machine Intelligence at Google Research (Mountain View) for the summer. I am very excited about it!
Update (2/4/2016): Paper on Convergent Learning has been accpeted for oral presentation (5.7%) in ICLR 2016! (check out preprint here)