Shibo Li

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School of Computing
University of Utah

 

Email : shibo at cs.utah.edu


About Me

I am a fourth-year Ph.D. student in Computer Science at SoC and SCI, University of Utah. I received my M.S. degree at University of Pittsburgh and my B.E. degree at South China University of Technology(SCUT). I also spent time at Schlumberger-Doll Research as research intern and at Amazon as Applied Scientist Intern working on Privacy-preserving learning algorihtms and incontext few-shots learning with pretrained large language/multi-modality models.

 

My principal research interests lie in developing flexible and scalable algorithms that can learn from complex, structural, and high-dimensional data within the Bayesian framework. I am advised by Dr. Shandian Zhe and Dr. Mike Kirby. Currently, we are working on multi-fidelity, multi-task active learning/Bayesian optimization problems with deep models. Prior to joining UofU, I spent some time working on reinforcement learning problems that help automatic agents make rational decisions from temporal data under uncertainties.

 

Preprints

Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks
Shibo Li*, Michael Penwarden*, Robert M. Kirby, Shandian Zhe

arXiv

Meta-Learning with Adjoint Methods
Shibo Li, Zheng Wang, Akil Narayan, Robert Kirby, Shandian Zhe

arXiv

Publications

Infinite-Fidelity Coregionalization for Physical Simulation
Shibo Li, Zheng Wang, Robert Kirby, Shandian Zhe

NeurIPS 2022

arXiv | code (to appear) 

Batch Multi-Fidelity Active Learning with Budget Constraints
Shibo Li*, Jeff Phillips*, Xin Yu, Robert M. Kirby, and Shandian Zhe

NeurIPS 2022

arXiv | code (to appear) 

Decomposing Temporal High-Order Interactions via Latent ODEs
Shibo Li, Mike Kirby, Shandian Zhe

ICML 2022

paper | code | video

Nonparametric Embeddings of Sparse High-Order Interaction Events
Zheng Wang, Yiming Xu, Conor Tillinghast, Shibo Li, Akil Narayan, Shandian Zhe

ICML 2022

paper | code | video

Deep Multi-Fidelity Active Learning of High-Dimensional Outputs
Shibo Li, Zheng Wang, Mike Kirby, Shandian Zhe

AISTATS 2022

arXiv | code | video

Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks
Shibo Li, Mike Kirby, Shandian Zhe

NeurIPS 2021

arXiv | code | video

Multi-Fidelity Bayesian Optimization via Deep Neural Networks
Shibo Li, Wei Xing, Robert M. Kirby, Shandian Zhe

NeurIPS 2020

arXiv | code | supplementary | video

Scalable Variational Gaussian Process Regression Networks
Shibo Li, Wei Xing, Robert M. Kirby, Shandian Zhe

IJCAI 2020

arXiv | code

Analysis of Multivariate Scoring Functions for Automatic Unbiased Learning to Rank
Tao Yang, Shikai Fang, Shibo Li, Yulan Wang, Qingyao Ai

CIKM 2020

arXiv

Academic Service

Program Committee Member: AISTATS 2023, UAI 2022, AISTATS 2022, ICMLA 2022

Conference Reviewer: NeurIPS 2022, NeurIPS 2022 MetaLearn Workshop, ICML 2022, AISTATS 2021, ICMLA 2021, UAI 2021, AAAI 2020

Last updated on Oct 2022.
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