Publications 

Authorship Declaration: Author names are listed alphabetically by default, with my name omitted. All author names are listed otherwise.

Preprints:

• A Variational-Calculus Approach to Online Algorithm Design and Analysis. (Manuscript Under Development)

• Revisiting Karp, Vazirani, and Vazirani (STOC 1990): A Simple Yet Rigorous Fix to the 1−1/e Upper-Bound Analysis. 

• Bounding the Optimal Performance of Online Randomized Primal-Dual Methods.

• Online Matching under KIID: Enhanced Competitive Analysis through Ordinary Differential Equation Systems.

Stochastic Optimization and Applications: 

• Matching Policy Design for Gig Platforms with “Priority” Features, 

with Evan Xu. 

The 40th AAAI Conference on Artificial Intelligence (AAAI), 2026.

• Optimizing Relevance and Diversity in Online Matching Markets: A Time-Adaptive Attenuation Approach,

with Evan Xu. 

Journal of Artificial Intelligence Research (JAIR), 2025.

• A New Regret-Analysis Framework for Budgeted Multi-Armed Bandits,

with Evan Xu. 

Journal of Artificial Intelligence Research (JAIR), 2025.

• Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions,

with Will Ma.

The 38th Annual Conference on Neural Information Processing Systems (NeurIPS), 2024. 

• Promoting External and Internal Equities Under Ex-Ante/Ex-Post Metrics in Online Resource Allocation,

with Karthik Sankararaman and Aravind Srinivasan.

The 41st International Conference on Machine Learning (ICML), 2024. (Spotlight Paper.) 

• Parameter-Dependent Competitive Analysis for Online Capacitated Coverage Maximization through Boostings and Attenuations,

The 41st International Conference on Machine Learning (ICML), 2024.

• Design a Win-Win Strategy That Is Fair to Both Service Providers and Tasks When Rejection is Not an Option,

Yohai Trabelsi, Pan Xu, and Sarit Kraus.

The 33rd International Joint Conference on Artificial Intelligence (IJCAI), 2024.

• Matching Tasks and Workers under Known Arrival Distributions: Online Task Assignment with Two-sided Arrivals, 

with John Dickerson, Karthik Sankararaman, Aravind Srinivasan, and Yifan Xu.

ACM Transactions on Economics and Computation (TEAC), 2024.  A preliminary version appeared at the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2018.

• Tight Competitive and Variance Analyses of Matching Policies in Gig Platforms, 

The ACM Web Conference (formally known as WWW), 2024. Accepted as an oral presentation; Track: Economics, Online Markets, and Human Computation.

• Two-Sided Capacitated Submodular Maximization in Gig Platforms,  

The 19th Conference on Web and Internet Economics (WINE), 2023.

• Exploring the Tradeoff between System Profit and Income Equality Among Ride-hailing Drivers, 

with Evan Xu. 

Journal of Artificial Intelligence Research (JAIR), 2023. A preliminary version appeared at the 29th International Joint Conference on Artificial Intelligence (IJCAI), 2020.

• Improved Sample-Complexity Bounds in Stochastic Optimization, 

with Alok Baveja, Amit Chavan, Andrei Nikiforov, and Aravind Srinivasan.

Operations Research, 2023. 

• Allocation Problem in Remote Teleoperation: Online Matching with Offline Reusable Resources and Delayed Assignments, 

Osnat Ackerman Viden, Yohai Trabelsi, Pan Xu, Karthik Abinav Sankararaman, Oleg Maksimov, and Sarit Kraus.

The 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2023. 

• Equity Promotion in Public Transportation, 

with Anik Pramanik and Yifan Xu.

The 37th AAAI Conference on Artificial Intelligence (AAAI), 2023.

• Fairness Maximization among Offline Agents in Online-Matching Markets, 

with Will Ma and Yifan Xu.

ACM Transactions on Economics and Computation (TEAC), 2022. A preliminary version appeared at the 17th Conference on Web and Internet Economics (WINE), 2021.

• Exploring the Tradeoff between Competitive Ratio and Variance in Online-Matching Markets, 

The 18th Conference on Web and Internet Economics (WINE), 2022.

• Equity Promotion in Online Resource Allocation, 

with Yifan Xu.

The 36th AAAI Conference on Artificial Intelligence (AAAI), 2022.

• Group-level Fairness Maximization in Online Bipartite Matching, 

with Will Ma and Yifan Xu. 

The 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2022. 

• The Generalized Magician Problem under Unknown Distributions and Related Applications, 

with Aravind Srinivasan.

The 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2022.

• Online minimum matching with uniform metric and random arrivals, 

with Sharmila V. S. Duppala and Karthik A. Sankararaman.

Operations Research Letters, 2022.

• Allocation Problems in Ride-Sharing Platforms: Online Matching with Offline Reusable Resources, 

with John Dickerson, Karthik Sankararaman, and Aravind Srinivasan. 

ACM Transactions on Economics and Computation, 2020. A preliminary version appeared in AAAI Conference on Artificial Intelligence (AAAI), 2018. 

• A Unified Model for the Two-stage Offline-then-Online Resource Allocation, 

Yifan Xu, Pan Xu, Jianping Pan, and Jun Tao.

The 29th International Joint Conference on Artificial Intelligence (IJCAI), 2020.

• Online Stochastic Matching: New Algorithms and Bounds,

with Brian Brubach, Karthik A. Sankararaman, and Aravind Srinivasan. 

Algorithmica, 2020. A preliminary version appeared in the 24th Annual European Symposium on Algorithms (ESA), 2016.

• Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours, 

Vedant Nanda, Pan Xu, John Dickerson, Karthik A. Sankararaman, and Aravind Srinivasan.

The 34th AAAI Conference on Artificial Intelligence (AAAI), 2020. Extended Abstract appeared in the 3rd AAAI/ACM Conference on Artificial Intelligence, Ethics and Society (AIES), 2020. 

• Mix and Match: Markov Chains and Mixing Times in Matching for Rideshare, 

with Mike Curry, John Dickerson, Karthik Sankararaman, Aravind Srinivasan, and Yuhao Wan.

The 15th Conference on Web and Internet Economics (WINE), 2019. 

• Algorithms to Approximate Column-Sparse Packing Programs, 

with Brian Brubach, Karthik A. Sankararaman, and Aravind Srinivasan. 

ACM Transactions on Algorithms, 2019. A preliminary version appeared in the ACM-SIAM Symposium on Discrete Algorithms (SODA) 2018.

• Attenuate Locally, Win Globally: Attenuation-Based Frameworks for Online Stochastic Matching with Timeouts, 

with Brian Brubach, Karthik A. Sankararaman, and Aravind Srinivasan. 

Algorithmica, 2019. A preliminary version appeared in the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2017.

• Online Resource Allocation with Matching Constraints,

with John Dickerson, Karthik A. Sankararaman, Kanthi Sarpatwar, Aravind Srinivasan, Kun-Lung Wu.

International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2019.

• Balancing Relevance and Diversity in Online Bipartite Matching via Submodularity, 

with John Dickerson, Karthik A. Sankararaman, and Aravind Srinivasan. 

 AAAI Conference on Artificial Intelligence (AAAI), 2019. 

• A Unified Approach to Online Matching with Conflict-Aware Constraints, 

Pan Xu, Yexuan Shi, Hao Cheng, John Dickerson, Karthik A. Sankararaman, Aravind Srinivasan, Yongxin Tong, and Leonidas Tsepenekas.

 AAAI Conference on Artificial Intelligence (AAAI), 2019. 

• Preference-Aware Task Assignment in On-demand Taxi Dispatching: An Online Stable Matching Approach, 

Boming Zhao, Pan Xu, Yexuan Shi, Yongxin Tong, Zimu Zhou, and Yuxiang Zeng. 

 AAAI Conference on Artificial Intelligence (AAAI), 2019. 

• A PTAS for a Class of Stochastic Dynamic Programs, 

with Hao Fu and Jian Li. 

International Colloquium on Automata, Languages and Programming (ICALP) 2018.

• Improved Bounds in Stochastic Matching and Optimization, 

with Alok Baveja, Amit Chavan, Andrei Nikiforov, and Aravind Srinivasan. 

Algorithmica 2017. A preliminary version appeared in the International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX) 2015.

• Budgeted Online Assignment in Crowdsourcing Markets in Crowdsourcing Market: Theory and Practice, 

Pan Xu, Aravind Srinivasan, Kanthi K. Sarpatwar, and Kun-Lung Wu.

International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2017.

Database Theory and Applications:

• Adaptive Dynamic Bipartite Graph Matching: A Reinforcement Learning Approach, 

Yansheng Wang, Yongxin Tong, Cheng Long, Pan Xu, Ke Xu, and Weifeng Lv.

IEEE International Conference on Data Engineering (ICDE) 2019.  

• Interaction-aware Arrangement for Event-based Social Networks,

Feifei Kou, Zimu Zhou, Hao Cheng, Junping Du, Yexuan Shi, and Pan Xu.

IEEE International Conference on Data Engineering (ICDE) 2019.    

• Onion Curve: A Space Filling Curve with Near-Optimal Clustering, 

Pan Xu, Cuong Nguyen, and Srikanta Tirthapura. 

IEEE International Conference on Data Engineering (ICDE) 2018.  

• Enumeration of Maximal Cliques from an Uncertain Graph, 

Arko Provo Mukherjee, Pan Xu, and Srikanta Tirthapura. 

IEEE Transactions on Knowledge and Data Engineering (TKDE) 2017. A preliminary version appeared in ICDE 2015 and was invited to TKDE for the best papers of ICDE 2015.

• Optimality of Clustering Properties of Space Filling Curves, 

Pan Xu and Srikanta Tirthapura. 

ACM Transactions on Database Systems (TODS) 2014. A preliminary version appeared in the ACM Symposium on Principles of Database Systems (PODS) 2012. 

• A Lower Bound On Proximity Preservation by Space Filling Curves, 

Pan Xu and Srikanta Tirthapura. 

IEEE International Parallel and Distributed Processing Symposium (IPDPS) 2012.

Bilevel Optimization and Applications:

• The Watermelon Algorithm for the Bilevel Integer Linear Programming Problem, 

with Lizhi Wang. 

SIAM Journal on Optimization (SIOPT), 2017.

• An Exact Algorithm for the Bilevel Mixed Integer Linear Programming Problem under Three Simplifying Assumptions, 

Pan Xu and Lizhi Wang. 

Computers & Operations Research (COR), 2013.

• An Optimization Approach to Gene Stacking, 

Pan Xu, Lizhi Wang, and William Beavis. 

European Journal of Operational Research (EJOR), 2011.