About me

Hello, I am Zhijian Duan (段志健), a Ph.D. student in CFCS at Peking University, where I am supervised by Professor Xiaotie Deng in daGAME lab. Prior to this, I received my Bachelor’s degree from Turing Class in the School of EECS at Peking University. During my undergraduate studies, I had the privilege of working with Professor Ming Zhang and Professor Hao Dong at Peking University, as well as Professor Jian Tang at Mila.

Research Interests

My research focuses on the intersection of algorithmic game theory and machine learning, with a particular emphasis on the following topics:

• Machine learning-based mechanism design.
• Equilibrium computation leveraging machine learning techniques.
• Online advertising, including ad auction design and auto-bidding.

For more information, please refer to my publication list.

Publications

• Zhijian Duan, Yusen Huo, Tianyu Wang, Zhilin Zhang, Yeshu Li, Chuan Yu, Jian Xu, Bo Zheng, Xiaotie Deng. An Adaptable Budget Planner for Enhancing Budget-Constrained Auto-Bidding in Online Advertising. In KDD 2025.
• Jian Xu, Zhilin Zhang, Zongqing Lu, Xiaotie Deng, Michael P. Wellman, Chuan Yu, Shuai Dou, Yusen Huo, Zhiwei Xu, Zhijian Duan, Shaopan Xiong, Chuang Liu, Ningyuan Li, Kefan Su, Wei Gong, Bo Zheng. Auto-Bidding in Large-Scale Auctions: Learning Decision-Making in Uncertain and Competitive Games. In NeurIPS 2024 Competition Track.
• Hanyu Li, Wenhan Huang, Zhijian Duan, David Henry Mguni, Kun Shao, Jun Wang, Xiaotie Deng. A Survey on Algorithms for Nash Equilibria in Finite Normal-Form Games. In Computer Science Review, 2024. [arXiv]
• Zhijian Duan, Haoran Sun, Yurong Chen, Xiaotie Deng. A Scalable Neural Network for DSIC Affine Maximizer Auction Design. In NeurIPS 2023, spotlight (top 5\%). [arXiv][Code]
• Zhijian Duan, Yunxuan Ma, Xiaotie Deng. Are Equivariant Equilibrium Approximators Beneficial? In ICML 2023. [arXiv]
• Yurong Chen*, Qian Wang*, Zhijian Duan, Haoran Sun, Zhaohua Chen, Xiang Yan, Xiaotie Deng. Coordinated Dynamic Bidding in Repeated Second-Price Auctions with Budgets. In ICML 2023. [arXiv]
• Ningyuan Li, Yunxuan Ma, Yang Zhao, Zhijian Duan, Yurong Chen, Zhilin Zhang, Jian Xu, Bo Zheng, Xiaotie Deng. Learning-Based Ad Auction Design with Externalities: the Framework and A Matching-Based Approach. In KDD 2023.
• Zhijian Duan, Wenhan Huang, Dinghuai Zhang, Yali Du, Jun Wang, Yaodong Yang, Xiaotie Deng. Is Nash Equilibrium Approximator Learnable? In AAMAS 2023. [arXiv]
• Zhijian Duan, Jingwu Tang, Yutong Yin, Zhe Feng, Xiang Yan, Manzil Zaheer, Xiaotie Deng. A Context-Integrated Transformer-Based Neural Network for Auction Design. In ICML 2022. [arXiv][code]
• Yixu Gao, Kun Shao, Zhijian Duan, Zhongyu Wei, Dong Li, Bin Wang, Mengchen Zhao, Jianye Hao. Efficient Dual-Process Cognitive Recommender Balancing Accuracy and Diversity. In DASFAA 2022.
• Weiping Song, Chence Shi, Zhiping Xiao, Zhijian Duan, Yewen Xu, Ming Zhang, Jian Tang. Autoint: Automatic feature interaction learning via self-attentive neural networks. In CIKM 2019. [arXiv][code]

Preprints

• Zhijian Duan*, Haoran Sun*, Yichong Xia, Siqiang Wang, Zhilin Zhang, Chuan Yu, Jian Xu, Bo Zheng, Xiaotie Deng. Automated Deterministic Auction Design with Objective Decomposition. 2024. [arXiv]

• Yunxuan Ma, Yide Bian, Hao Xu, Weitao Yang, Jingshu Zhao, Zhijian Duan, Feng Wang, Xiaotie Deng. Large-Scale Contextual Market Equilibrium Computation through Deep Learning. 2024. [arXiv]

• Jie Fu*, Xue Geng*, Zhijian Duan, Bohan Zhuang, Xingdi Yuan, Adam Trischler, Jie Lin, Chris Pal, Hao Dong. 2020. Role-Wise Data Augmentation for Knowledge Distillation. [arXiv][Code]

• Weiping Song*, Zhijian Duan*, Ziqing Yang, Hao Zhu, Ming Zhang, Jian Tang. Ekar: An Explainable Method for Knowledge Aware Recommendation. 2019. [arXiv]

( * denotes equal contribution)

Education

• Ph.D. in Computer Software and Theory, CFCS, Peking University, 2020-2025 (expected). Advisor: Xiaotie Deng.
• B.S. in Computer Science, Turing Class, Peking University, 2016-2020, GPA 3.72/4.0 (Top 15%).

Academic Service

• Invited Reviewer (Conference): WWW’22, AAMAS’23’25, NeurIPS’23’24, ICLR’24’25, KDD’25.
• Invited Reviewer (Journal): TCS, ACML.

Teaching

• TA of ALgorithmic Game Theory by Prof. Xiaotie Deng, Fall 2023.
• TA of Mathematics in AI by Prof. Xiaotie Deng, Spring 2022.
• TA of Discrete Math (II) and Interactions by Prof. Xiaotie Deng, Spring 2021.
• TA of Deep Generative Models by Prof. Hao Dong, Spring 2020.
• TA of Algorithm Design and Analysis (Honor Track) by Prof. Ming Zhang, Spring 2019.

Miscellaneous

• I like playing badminton. In 2016, I was part of the winning team in the freshman badminton competition at Peking University.