张晓今

Xiaojin Zhang

Computer Science and Technology

Huazhong University of Science and Technology

Wuhan,China

xiaojinzhang@hust.edu.cn

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I am an assistant professor at Huazhong University of Science and Technology (HUST). My hometown is Xiangyang, Hubei, known as “the first city of the Huaxia”. I was a Postdoctoral Fellow at CSE, HKUST. I am very fortunate to be advised by Prof. Qiang Yang and co-advised by Prof. Kai Chen. In 2021, I completed my PhD at CSE, CUHK. My advisors were Prof. Shengyu Zhang and Prof. Siu On Chan. Before that, I obtained my M.S. in Computer Application Technology from the Institute of Computing Technology, the Chinese Academy of Sciences, with the supervision of Prof. Si-Min He. I obtained my B.S. in Statistics and Economics (Elite Class) from the School of Mathematics and Statistics, Shandong University, Weihai.

I like designing efficient algorithms. I have broad interests in classical theoretical computer science and modern machine learning.

Please feel free to email me if you are interested in working with me on trustworthy machine learning. Working on one project at a time with the same partner is my preferred way of collaboration.

My principle: You gotta do what you love. My belief: A good character is the best tombstone. Those who loved you and were helped by you will remember you when forget-me-nots have withered. Carve your name on hearts, not on marble.

Reinforcement Learning as a Catalyst for Robust and Fair Federated Learning: Deciphering the Dynamics of Client Contributions

Jialuo He, Wei Chen, Xiaojin Zhang.

Rethinking Deep Leakage from Gradients for Trustworthy Federated Learning

Xiaojin Zhang, Yan Kang, Qiang Yang.

Theoretically Principled Federated Learning for Balancing Privacy and Utility

Xiaojin Zhang, Wenjie Li, Kai Chen, Shutao Xia, Qiang Yang.

A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning

Yan Kang, Jiahuan Luo, Yuanqin He, Xiaojin Zhang, Lixin Fan, Qiang Yang.

Near-optimal Algorithm for Distribution-free Junta Testing

Xiaojin Zhang.

Blurb on Property Testing Review. We made progress on a series of works published at STOC/FOCS/SODA.
Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning

Xiaojin Zhang, Kai Chen, Qiang Yang.

Transactions on Intelligent Systems and Technology [TIST] [JCR Q1] (accept with revision).
Probably Approximately Correct Federated Learning

Xiaojin Zhang, Anbu Huang, Lixin Fan, Kai Chen, Qiang Yang.

Journal of Machine Learning Research [JMLR 2023] (accept with revision).
A Meta Framework for Tuning Hyperparameters of Protection Mechanisms in Trustworthy Federated Learning

Xiaojin Zhang, Yan Kang, Lixin Fan, Kai Chen, Qiang Yang.

Transactions on Intelligent Systems and Technology [TIST] [JCR Q1].
A Game-theoretic Framework for Federated Learning

Xiaojin Zhang, Lixin Fan, Siwei Wang, Wenjie Li, Kai Chen, Qiang Yang.

Transactions on Intelligent Systems and Technology [TIST 2023] [JCR Q1].
Improved Algorithm for Permutation Testing

Xiaojin Zhang.

Theoretical Computer Science [TCS 2023] [CCF B]. We made progress on a series of works published at STOC/FOCS/SODA..
Trading Off Privacy, Utility and Efficiency in Federated Learning

Xiaojin Zhang, Yan Kang, Kai Chen, Lixin Fan, Qiang Yang.

Transactions on Intelligent Systems and Technology [TIST 2023] [JCR Q1].
No Free Lunch Theorem for Security and Utility in Federated Learning

Xiaojin Zhang, Hanlin Gu, Lixin Fan, Kai Chen, Qiang Yang.

Transactions on Intelligent Systems and Technology [TIST 2022] [JCR Q1]. PDF
Variance-Dependent Best Arm Identification

Pinyan Lu*, Chao Tao*, Xiaojin Zhang*. [alphabetic ordering]

In Proceedings of the Conference on Uncertainty in Artificial Intelligence [UAI 2021] [CCF B]. PDF
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously

Chung-Wei Lee*, Haipeng Luo*, Chen-Yu Wei*, Mengxiao Zhang*, Xiaojin Zhang*. [alphabetic ordering]

In Proceedings of the 36th International Conference on Machine Learning [ICML 2021] [CCF A]. PDF
Adaptive Double-Exploration Tradeoff for Outlier Detection

Xiaojin Zhang, Honglei Zhuang, Shengyu Zhang, Yuan Zhou.

The Thirty-Fourth AAAI Conference on Artificial Intelligence [AAAI 2020] [CCF A]. PDF
pGlyco 2.0 enables precision N-glycoproteomics with comprehensive quality control and one-step mass spectrometry for intact glycopeptide identification

Ming-Qi Liu#, Wen-Feng Zeng#, Pan Fang#, Wei-Qian Cao#, Chao Liu#, Guo-Quan Yan, Yang Zhang, Chao Peng, Jian-Qiang Wu, Xiao-Jin Zhang, Hui-Jun Tu, Hao Chi, Rui-Xiang Sun, Yong Cao, Meng-Qiu Dong, Bi-Yun Jiang, Jiang-Ming Huang, Hua-Li Shen, Catherine C. L. Wong, Si-Min He, Peng-Yuan Yang.

Nature Communications, 8, 438, 2017. PDF
Trends in Mass Spectrometry-Based Large-Scale N-Glycopeptides Analysis

Wen-Feng Zeng, Yang Zhang, Ming-Qi Liu, Jian-Qiang Wu, Xiao-Jin Zhang, Hao Yang, Chao Liu, Hao Chi, Kun Zhang, Rui-Xiang Sun, Peng-Yuan Yang, Si-Min He.

Progress in Biochemistry and Biophysics, 2016, 43(6):550-562. PDF
2017-2021 Postgraduate Studentship, CUHK
06/2017 Excellent Master's Thesis
04/2013 The Mathematical Contest in Modeling (MCM), Honorable Mentions
10/2012 China Undergraduate Mathematical Contest of Modeling (CUMCM), National First Prize
11/2011 National Scholarship
05/2011 Aerobic Gymnastics, Second Prize in College
A comprehensive system for constructing N-glycan databases based on linear canonical representations

Xiao-Jin Zhang, Wen-Feng Zeng, Jian-Qiang Wu, Rui-Xiang Sun, Si-Min He.

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A comprehensive system for intact glycopeptide identification

Wen-Feng Zeng, Ming-Qi Liu, Xiao-Jin Zhang, Jian-Qiang Wu, Yang Zhang, Rui-Xiang Sun, Peng-Yuan Yang, Si-Min He.

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I am fortunate to be working with the following excellent students:

Tongtian Zhu, Zhejiang University
Kang Sun, Shanghai Jiao Tong University
Wenjie Li, Tsinghua University
Suheng Yao, Toronto University
Jialuo He, Chongqing University
Yulin Fei, Huazhong University of Science and Technology
N糖结构数据库的构建算法研究及其应用

张晓今.

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