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Chicheng Zhang

Learning Theory Machine Learning Privacy In Machine Learning
University of Arizona Department of Computer Science

About

I am an assistant professor at the Computer Science Department, the University of Arizona. From September 2017 to June 2019, I was a postdoctoral researcher at the machine learning group of Microsoft Research NYC. I got my PhD in Computer Science at UCSD, where I was lucky to have Prof. Kamalika Chaudhuri as my advisor. Before this, I was an undergraduate student at Peking University, studying learning theory with Prof. Liwei Wang.

Research Performance Summary

56
Total Papers
2278
Total Citations
20
H-Index
2012-2025
Active Research Span

First Recorded Paper

Tensor Decomposition for Topic Models: An Overview and Implementation

Year: 2012

Citations: 0

Venue: N/A

Latest Recorded Paper

Interactive and Hybrid Imitation Learning: Provably Beating Behavior Cloning

Year: 2025

Citations: 0

Venue: The Thirty-ninth Annual Conference on Neural Information Processing Systems

Last 10 Years Publication Activity

This timeline shows the professor's yearly publication activity.

2025
7
2024
8
2023
4
2022
6
2021
7
2020
4
2019
6
2018
2
2017
4
2016
2
2015
2

Publication Venues and Collaboration

Journal, Conference, and Book Publication Breakdown

Conference 18
Journal 2
Book 1

Top Coauthors

Zhang Chaudhuri Langford

Research Impact by Period

2025-2026

Period Stats
Papers 7
Citations 3
Avg. Citations / Paper 0.4
H-Index 1

2020-2024

Period Stats
Papers 29
Citations 516
Avg. Citations / Paper 17.8
H-Index 12

2015-2019

Period Stats
Papers 16
Citations 1646
Avg. Citations / Paper 102.9
H-Index 9

2010-2014

Period Stats
Papers 4
Citations 113
Avg. Citations / Paper 28.2
H-Index 2

Contact and Professional Links

Contact Information

chichengz@arizona.edu

Detected Research Keywords

Efficient Active Learning Probabilistic Armed Bandit Contextual Bandits Continuous Bandits Continuous Actions Active Learning Sparse Learning Sparse Halfspaces Active Learning Halfspaces Efficient Online Bandit Online Bandit Multiclass Bandit Multiclass Learning