Pingbang Hu

Q pbb@illinois.edu(+1) 734 882 7750

Research Interest

Machine Learning
Explainable Machine Learning, Trustworthy Machine Learning, Algorithmic Fairness, Graph Learning, Statistical Learning Theory

Theoretical Computer Science
Fast Graph Algorithm, Approximation Algorithm, Computational Complexity, Hardness of Approximation

Education
University of Illinois Urbana-Champaign
Ph.D. Student in Information Science, School of Information ScienceIllinois
Aug. 2023 – Present◦ Advisor: Jiaqi MaUniversity of Michigan
B.Sc. in Computer Science, College of Engineering

MichiganAug. 2021 – May 2023

◦ Graduate with Summa Cum Laude◦ Minor: Mathematics, College of Literature, Science, and the ArtsNational Yang Ming Chiao Tung University
Visiting Scholar

Shanghai Jiao Tong University
B.Eng. in Electrical and Computer Engineering, UM-SJTU Joint Institute

Hsinchu, Taiwan
Jan. 2020 – Jul. 2020

Shanghai, China
Aug. 2019 – Aug. 2023

◦ Minor: Computer Science, UM-SJTU Joint InstituteResearch and Industry ExperienceSugiyama Laboratory, National Institute of Informatics
Research InternTokyo, JapanMay 2024 – Aug. 2024

◦ Advisor: Mahito Sugiyama
Theory of Computation Laboratory, University of Michigan
Undergraduate ResearcherMichigan
Mar. 2022 – Present◦ Advisor: Thatchaphol Saranurak◦ Design the first almost linear time algorithm on finding minimal balanced separator.
SURE Program, University of Michigan
Undergraduate ResearcherMichigan
May 2022 – Apr. 2023

◦ Advisor: Wei Hu◦ Theoretical analysis on intrinsic dimension under isoperimetry assumptions.
FORESEER Research Group, University of Michigan
Undergraduate Research AssistantMichigan
Dec. 2021 – Jan. 2023

◦ Advisor: Jiaqi Ma◦ Prove the asymptotic separability of a 1-layer GCN on node classification tasks.
Chief Noob
Backend Developer

Pre-prints and Technical Reports

Shanghai, China
Oct. 2020 – June 2021(∗ denotes equal contribution)[P1] Pingbang Hu, Mahito Sugiyama, “Pseudo-Non-Linear Data Augmentation with Information Geometry”. Preprint[P2] Xinhe Wang, Pingbang Hu, Junwei Deng, Jiaqi Ma, “Adversarial Attacks on Data Attribution”. Preprint [P3] Yiwen Tu∗ , Pingbang Hu∗ , Jiaqi Ma, “Towards Reliable Empirical Machine Unlearning Evaluation: A Game-TheoreticView”. Preprint [P4] Yuzheng Hu∗ , Pingbang Hu∗ , Han Zhao, Jiaqi Ma, “Most Influential Subset Selection: Challenges, Promises, and Beyond”.
In submission[P5] Pingbang Hu, “Travel the Same Path: A Novel TSP Solving Strategy”. Preprint Teaching ExperienceInstructional Aide, University of Michigan◦ Introduction to Cryptography: An upper-level course on the main undergraduate CS track.
◦ Randomness and Computation: A graduate-level course on the M.S. CS theory track.

Michigan

Hold discussion and office hour weekly, design assignment and exam problems, grade and guide projects.

Teaching Assistant, Shanghai Jiao Tong University

Winter 2023
Fall 2022

Shanghai, China

Hold discussion and office hour weekly, design and grade assignments and exams.

◦ Honor Mathematics III: An undergraduate-level course on the main B.Eng. ECE track.

Summer 2021

∗ Competition: Hold the 1 UM-SJTU JIntegration Bee competition.
st◦ Honor Mathematics II: An undergraduate-level course on the main B.Eng. ECE track.

Fall 2020

Honors and Awards





Excellent Internship Evaluation
Best internship evaluation result in National Institute of Informatics

Hong Kong, Macao and Taiwan Overseas Chinese Student ScholarshipFirst Prize (Ranked #2) among all HK, MC and TW students in Shanghai Jiao Tong University

Undergraduate Excellent Scholarship
Third Prize among all students in UM-SJTU Joint Institute

Bao Gang Excellent ScholarshipAug. 2024

Shanghai, China
Oct. 2021

Shanghai, China
Nov. 2020

Shanghai, China

Second Prize (Ranked #3) among all Taiwan students in Shanghai Jiao Tong University

June 2020

Hong Kong, Macao and Taiwan Overseas Chinese Student Scholarship

Shanghai, China

First Prize (Ranked #1) among all HK, MC and TW students in UM-SJTU Joint Institute

Professional Service

Tokyo, Japan

Conference Reviewer
ICML 2024, IEEE BigData 2023, ICLR 2025

Dec. 2019