Yichen Li

I am a Computer Science Master's student at Guibas Lab at Stanford University, where I have been fortunate to worked with Prof. Leonidas Guibas, Kaichun Mo, and Dr.Or Litany.

I received my B.S. in Computer Science and B.S. in Mathematics and Economics from Boston University, where I worked with Prof. Emily Whiting and Prof. Kate Saenko, as well as Prof. Bryan Plummer on various computer vision and graphics research. Previously, I was a research intern at NVIDIA, working with Dr.Bryan Catanzaro, Dr.Ben Eckart, Dr.Kevin Shih, Dr.Or Litany, and Andrew Tao.

My research interests lie in the areas of 3D computer vision, graphics, and machine learning. I am fascinated by building intelligent systems for 3D content understanding through representation learning, object interactions and physics-based geometry analysis.

Email / Google Scholar / GitHub

News

[new] [June, 2020] Our paper Learning 3D Part Assembly from A Single Image is accepted to ECCV 2020.
[new] [June, 2020] Our paper Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation is accepted to ECCV 2020.

Publications
	Learning 3D Part Assembly from A Single Image Yichen Li, Kaichun Mo, Lin Shao, Minhyuk Sung, Leonidas Guibas, European Conference on Computer Vision (ECCV), 2020 [paper] [project page] [code]
	Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation Yichen Li, Xingchao Peng, Kate Saenko, European Conference on Computer Vision (ECCV), 2020 [paper] [project page] [code]
	NASDA: Neural Architecture Search for Domain Adaptation Yichen Li, Xingchao Peng, Preprint (in submission), 2020 [paper]
	Revisiting Image-Language Networks for Open-ended Phrase Detection Bryan Plummer, Kevin Shih, Yichen Li, Ke Xu, Svetlana Lazebnik, Stan Sclaroff, Kate Saenko TPAMI, 2019 [paper]
	Lifelong Domain Adaptation with Interpolated Feature Alignment Yichen Li, Xingchao Peng, Ping Hu Preprint , 2019 [paper]
	Learning Domain Adaptive Features with Unlabeled Domain Bridges Xingchao Peng, Yichen Li, preprint, 2019 [paper]

Academic Services

Conference Reviewer: CVPR, ICML, NeurIPS, ICCV, WACV, AAAI, IEEE-TIP

Teaching
	CS468: Topics in Geometric Algorithms: Non-Euclidean Methods in Machine Learning (Fall 2020) Course Assistant (CA)
	CS231n: Convolutional Neural Networks for Visual Recognition (Spring 2021) Course Assistent (CA)

Awards

College Prize For Excellence in Computer Science (GPA Rank: 1st)
Summa Cum Laude
BU Arts Initiative Research Award
UROP Summer Research Award
Dean's List 4 Years

This guy makes a nice webpage.