Zuheng(David) Xu
I am a Ph.D candidate in Statistics at University of British Columbia (UBC), under the supervision of Trevor Campbell. My research focuses on Bayesian inference and machine learning, particularly on the scalable Bayesian computation and generative modeling methods with theory guarantees. I have also been an intern with Jason Hartford at Valence Labs, where I developed my interest in causal representation learning and the general application in biology and drug discovery.
I'm also part of the Turing.jl community, which has kindly included me as a member despite my minuscule contribution. If you are looking for a simple yet flexible normalizing flow package in Julia that is suited for approximate Bayesian inference, feel free to checkout our pacakge NormalizingFlows.jl. The package is currently a work in progress, so we welcome you to open an issue should you have any questions or suggestions.
In my free time, I love to be busy at doing nothing. But you may find me in
{"boxing","basketballing","YouTubing", "Netflixing", "cooking"}
.
Preprints
Son Luu, Zuheng Xu, Nikola Surjanovic, Miguel Biron-Lattes, Trevor Campbell, Alexandre Bouchard-Côté
[arXiv]
Zuheng Xu*, Moksh Jain*, Ali Denton, Shawn Whitfield, Aniket Didolkar, Berton Earnshaw, Jason Hartford
[arXiv]
Publication
Xin Ding, Yongwei Wang, Zuheng Xu
AAAI Conference on Artificial Intelligence, 2024
[arXiv] [AAAI]
Zuheng Xu, Trevor Campbell
Advances in Neural Information Processing Systems, 2023
[arXiv] [NeurIPS] [poster] [slides]
Zuheng Xu, Naitong Chen, Trevor Campbell
International Conference on Machine Learning, 2023
[arXiv] [code] [ICML] [poster]
Naitong Chen, Zuheng Xu, Trevor Campbell
Advances in Neural Information Processing Systems (oral), 2022
[arXiv] [code] [NeurIPS]
Xin Ding, Yongwei Wang, Zuheng Xu, Z. Jane Wang, William J. Welch
Expert Systems with Applications, 2023
[arXiv] [code] [ESA]
Xin Ding, Yongwei Wang, Zuheng Xu, Z. Jane Wang, William J. Welch
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
[arXiv] [code] [TPAMI]
Zuheng Xu, Trevor Campbell
Statistics and Computing 32(63), 2022
[arXiv] [code] [Statistics and Computing] [Msc. Thesis] [slides]
Xin Ding, Yongwei Wang, Zuheng Xu, William J. Welch, Z. Jane Wang
International Conference on Learning Representations, 2021
[ICLR] [code]
Dionysis Manousakas, Zuheng Xu, Cecilia Mascolo, Trevor Campbell
Advances in Neural Information Processing Systems, 2020
[NeurIPS] [code]
Gianni Co, Zuheng Xu, Giorgio Sgarbi, Siqi Cheng, Ziqi Xu, Agnes d'Entremont, Juan Abelló
Proceedings of the Canadian Engineering Education Association Conference, 2019
[CEEA]
Teaching
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Teaching assistant of the Department of Statistics (UBC)
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STAT 306 (Finding Relationship in Data) 2024 Fall
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STAT 305 (Intro. to Stat. Inference) 2023 Spring
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STAT 200 (Elementary Stat.)---head TA 2022 Spring
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STAT 404 (Design of Experiment) 2021 Fall
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STAT 302 (Intro. to Prob.) 2021 Spring
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STAT 406 (Methods for Stat. Learning)---head TA 2020 Fall
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STAT 461/561 (Stat. Theory II)---grad. mandatory course 2020 Spring
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STAT 200 (Elementary Stat.) 2020 Spring
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STAT 200 (Elementary Stat.) 2019 Spring
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STAT 300 (Intermediate Stat.) 2018 Fall
Teaching assistant of School of Science (UBC)
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SCIE 300 (Communicating Science) 2019 Fall
Honors/Awards
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Marshall Prize (UBC Stat.)2024
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Top Reviewer Award (NeurIPS)2023
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Statistics Graduate Teaching Assistant Awards (UBC Stat.)2022
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2022
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Four-year Fellowship (FYF) For PhD students (UBC)2020-2024
Four-year Fellowship (4YF) Tuition Award (UBC) -
Faculty of Science Graduate Award (UBC) 2020-2023
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Excellence Initiaitive PhD Award (UBC) 2020-2021
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Meritorious Winner by COMAP (MCM) 2017
Education
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Ph.D. of Statistics, University of British Columbia 2020-present
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M.Sc. of Statistics, University of British Columbia 2018-2020
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B.Sc. of Statistics, Sichuan University 2014-2018