Ph.D. @ MIT IDSS & CSAIL
I am a Ph.D. student majoring in Social and Engineering Systems at MIT IDSS and CSAIL. 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.
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
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
(* indicates equal contribution)
Uncertainty Quantification with Pre‑trained Language Models: A Large‑Scale Empirical Analysis
Yuxin Xiao, Paul Pu Liang, Umang Bhatt, Willie Neiswanger, Ruslan Salakhutdinov, Louis-Philippe Morency. EMNLP, 2022.
(findings)
[Paper] [Code]
SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction
Yuxin Xiao, Zecheng Zhang, Yuning Mao, Carl Yang, Jiawei Han. NAACL, 2022.
(oral presentation)
[Paper] [Code]
Discovering Strategic Behaviors for Collaborative Content-Production in Social Networks
Yuxin Xiao, Adit Krishnan, Hari Sundaram. WWW, 2020.
(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.
(140+ citations, 250+ 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.
(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]