Yuxin Xiao

Ph.D. @ MIT IDSS

Profile Pic

About me

I am a Ph.D. student majoring in Social and Engineering Systems at MIT IDSS. I have been fortunately working with Prof. Marzyeh Ghassemi on Machine Learning for Healthcare.

Previously, I received my M.S. in Machine Learning at CMU where I was advised by Prof. Eric P. Xing and Prof. Louis-Philippe Morency. I received my B.S. in Computer Science, Statistics, and Mathematics at UIUC where I was advised by Prof. Jiawei Han and Prof. Hari Sundaram.

Here are some highlights of my experience. Please refer to my CV for more details.

Education

Massachusetts Institute of Technology, 2022/06~2027/05.
Ph.D. in Social and Engineering Systems. GPA: N.A./5.00

Carnegie Mellon University, 2020/08~2021/12.
M.S. in Machine Learning. GPA: 4.12/4.33

University of Illinois at Urbana-Champaign, 2016/08~2020/05.
B.S. in Computer Science; B.S. in Statistics, Mathematics. GPA: 3.93/4.00

Awards & Honors

2020 C. W. Gear Outstanding Undergraduate Award, UIUC (2 at UIUC)
2020 CRA Outstanding Undergraduate Researcher Award Honorable Mention, Computing Research Association (4 at UIUC)
2019 IEEE BigData 2019 Student Travel Award, IEEE BigData
2012-2015 Senior-Middle 1 (SM1) Scholarship, Ministry of Education, Singapore

Publications

(* indicates equal contribution)

SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction
Yuxin Xiao, Zecheng Zhang, Yuning Mao, Carl Yang, Jiawei Han. NAACL, 2022.
(full paper, oral presentation)
[Paper] [Code]

Discovering Strategic Behaviors for Collaborative Content-Production in Social Networks
Yuxin Xiao, Adit Krishnan, Hari Sundaram. WWW, 2020.
(full paper, oral presentation)
[Paper] [Code]

Heterogeneous Network Representation Learning: A Unified Framework with Survey and Benchmark
Carl Yang*, Yuxin Xiao*, Yu Zhang*, Yizhou Sun, Jiawei Han. TKDE Journal, 2020.
(survey paper, 100+ citations, 240+ GitHub stars and forks)
[Paper] [Code]

Non-local Attention Learning on Large Heterogeneous Information Networks
Yuxin Xiao*, Zecheng Zhang*, Carl Yang, Chengxiang Zhai. IEEE BigData, 2019.
(full paper, oral presentation)
[Paper] [Code]

Amortized Auto-Tuning: Cost-Efficient Transfer Optimization for Hyperparameter Recommendation
Yuxin Xiao, Eric P. Xing, Willie Neiswanger. Preprint, 2021.
[Paper] [Code]