Haoyue BAI

I am a Ph.D. student at the Computer Sciences Department, University of Wisconsin-Madison. Prior to that, I obtained my bachelor's degree at Zhejiang University and my master's degree at The Hong Kong University of Science and Technology.

I'm interested in machine learning, open-world problems, AI safety and reliability. Most of my recent research is about enabling machine learning models to operate reliably in the wild, by enhancing robustness against distribution shifts and detecting out-of-distribution data.

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* Officially awarded the 2024 OpenAI Superalignment Fellowship!

* One (co)first-authored paper Provable Out-of-Distribution Generalization in Hypersphere accepted to ICLR 2024.

* One first-authored paper Exploiting Wild Data for Both OOD Generalization and Detection accepted to ICML 2023.

* One first-authored Long Survey Paper (23 pages) accepted to Neurocomputing 2022.

* One benchmarking paper Benchmarking and Understanding OOD Generalization (OoD-Bench) accepted to CVPR 2022 (oral).

This paper provably learns domain-invariant representations in a hyperspherical space for OOD generalization.

This paper bridges the gap between OOD generalization and OOD detection in one coherent framework.

This benchmark may serve as a strong foothold that can be resorted to by future OoD generalization research.

This work takes the first step to understand the OoD generalization of neural network architectures systematically.

This work designs a general OoD generalization framework to tackle possible correlation shift and diversity shift in the real world.

This paper provides an up-to-date review of recent crowd counting approaches, and educate new researchers in this field the design principles and trade-offs.

This work quantifies two dimension crowd counting challenges: large variation in object scale and isolated clusters of objects.

2022.9 -- 2023.12. University of Wisconsin-Madison, Madison.
Research Assistant.
Advisor: Prof. Sharon Yixuan Li.

2021.6 -- 2021.9. The Chinese University of Hong Kong, Centre for Perceptual and Interactive Intelligence, Hong Kong.
Research Assistant.
Advisor: Prof. Bolei Zhou.

2020.6 -- 2021.5. AI Theory Group, Noah's Ark Lab, Hong Kong.
Research Intern.
Mentor: Dr. Fengwei Zhou, Dr. Lanqing Hong. Advisor: Prof. Nanyang Ye.
Director: Dr. Zhenguo Li.

2017.7 -- 2017.8. The Hong Kong University, Hong Kong.
Summer Intern.
Advisor: Prof. Lucas C.K. Hui.

OpenAI Superalignment Fellowship
Research Travel Grant, The Hong Kong University of Science and Technology
Outstanding Graduates, Zhejiang University
First-Class Academic Scholarship, Zhejiang University   (Awarded to Top 3% Students on Academic Merit)
First-Class Scholarship for Outstanding Students, Zhejiang University
Outstanding Student Leader Awards, Zhejiang University

Internation Conference on Machine Learning (ICML) 2023, 2024.
International Conference on Learning Representations (ICLR) 2023, 2024.
Conference on Neural Information Processing Systems (NeurIPS) 2023.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022, 2023.
European Conference on Computer Vision (ECCV) 2022, 2024.
International Conference on Computer Vision (ICCV) 2023.
AAAI Conference on Artificial Intelligence (AAAI) 2022.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2024.

University of Wisconsin–Madison
COMP CS400: Data Science Programming III (Spring 2024)

University of Wisconsin–Madison
COMP CS220: Data Science Programming I (Fall 2022)

The Hong Kong University of Science and Technology
COMP2611: Computer Organization (Fall 2019, Spring 2019)

Thanks to Jon Barron for website template.