AI for Mechanism Design and Strategic Decision Making

ICLR 2026 Workshop

News

    • [Mar 10] Paper decision is released: The deadline for camera-ready version is Mar 21.
    • [Feb 3] Submission Portal Reopened: The submission portal has been reopened after a temporary closure due to technical issues. Please note: The deadline is now slightly after Feb 3, 24:00 AOE.
    • [Jan 16] Deadline Adjusted: The submission deadline is slightly adjusted to 3 Feb, 2026.
    • [Dec 11] Submission Portal Now Open: The OpenReview venue is now live. Visit the venue and submit your paper!
    • [Dec 6] Call for Papers Released: We are inviting submissions for original research. Deadline: 30 Jan, 2026.
    • [Dec 6] Website Launched: Welcome to the official website of AIMS@ICLR2026.

About

Mechanism Design (MD) and Strategic Decision Making (SDM) are foundational pillars of economic theory with growing relevance to computer science and multi-agent systems. MD and SDM are profoundly interconnected: mechanism designers must anticipate strategic behaviors, while agents continuously adapt their strategies in response to mechanisms.

Recent advances in AI, including foundation models and generative AI, are introducing novel methodologies that enhance and redefine these fields. Modern data-driven techniques like multi-agent reinforcement learning (MARL) and differentiable economics offer greater scalability in complex environments.

This workshop aims to serve as a premier venue to catalyze interdisciplinary research. We aim to bridge distinct research communities by bringing together experts from machine learning, economics, theoretical computer science, and operations research.

Call for Papers

We invite submissions on how modern AI can redefine, extend, or automate core problems in Mechanism Design (MD) and Strategic Decision Making (SDM). We strongly encourage submissions from diverse fields, including machine learning, reinforcement learning, multi-agent systems, optimization, NLP, human-AI interaction, economics, operations research, and theoretical computer science.

Key Dates

  • Submission Open: 15 December, 2025
  • Submission Deadline: 3 February, 2026
  • Notification of Acceptance: 28 February, 2026
  • Camera-Ready Paper Due: 9 March, 2026
  • Workshop Time: 26 April, 2026

All deadlines follow the Anywhere on Earth (AoE) timezone.

Submission Site

Submit papers through the AI for Mechanism Design and Strategic Decision Making on OpenReview.

Scope

Topics of interest include, but are not limited to:

AI for Mechanism Design
  • Discovering optimal, robust, and adaptive mechanisms for auctions, matching, and voting.
  • Automating the validation of theoretical properties in novel mechanisms.
  • Extending classical mechanisms to high-dimensional or natural language settings.
  • Enhancing the interpretability and transparency of complex mechanisms.
AI for Strategic Decision Making
  • Assisting strategic decisions in complex, dynamic environments.
  • Characterizing and influencing dynamics and equilibria in multi-agent systems.
  • Improving human-machine collaboration in strategic settings.
Theory, Ethics, and Societal Impact
  • Formal models of AI agent interaction and evolution.
  • Theoretical analyses of benefits and pitfalls (e.g., efficiency, fairness, robustness).
  • Policy and governance frameworks for AI in MD/SDM.
  • Forecasting the societal impact of AI-assisted mechanisms and strategic interactions.
Applications and Case Studies
  • Real-world deployments and empirical insights (e.g., advertising, cloud markets).
  • Practical challenges in scaling AI for MD/SDM.
  • Novel benchmarks, datasets, and simulation platforms.
  • Blueprints for integrating AI into existing MD/SDM systems.

Submission Guidelines

Format:

All submissions must be a single PDF file. We welcome high-quality original papers in the following two tracks. References and appendices are not included in the page limit, but the main text must be self-contained. Reviewers are not required to read beyond the main text.

  • Short papers: Up to 4 pages + references for in-progress ideas, modest theoretical results, follow-up experiments, or fresh perspectives on existing work.
  • Long Papers: Up to 9 pages + references for novel theoretical results, algorithms, empirical studies, surveys, or real-world applications.
ICLR Official

Since 2025, ICLR has discontinued the separate “Tiny Papers” track, and is instead requiring each workshop to accept short (3–5 pages in ICLR format, exact page length to be determined by each workshop) paper submissions, with an eye towards inclusion; see ​​https://iclr.cc/Conferences/2025/CallForTinyPapers for a history of the ICLR tiny papers initiative. Authors of these papers will be earmarked for potential funding from ICLR, but need to submit a separate application for Financial Assistance that evaluates their eligibility. This application for Financial Assistance to attend ICLR 2026 will become available on https://iclr.cc/Conferences/2026/ at the beginning of February and close early March.

Style file:

You must format your submission using the ICLR 2026 LaTeX style file. For your convenience, we have modified the main conference style file to refer to our workshop: iclr_aims.sty. Please include the references and supplementary materials in the same PDF. The maximum file size for submissions is 50MB. Submissions that violate the ICLR style (e.g., by decreasing margins or font sizes) or page limits may be rejected without further review.

Dual-submission and non-archival policy:

We welcome ongoing and unpublished work. We will also accept papers that are under review at the time of submission, or that have been recently accepted, provided they do not breach any dual-submission or anonymity policies of those venues. The workshop is a non-archival venue and will not have official proceedings. Workshop submissions can be subsequently or concurrently submitted to other venues.

Visibility:

Submissions and reviews will not be public. Only accepted papers will be made public.

Double-blind reviewing:

All submissions must be anonymized and may not contain any identifying information that may violate the double-blind reviewing policy. This policy applies to any supplementary or linked material as well, including code. If you are including links to any external material, it is your responsibility to guarantee anonymous browsing. Please do not include acknowledgements at submission time. If you need to cite one of your own papers, you should do so with adequate anonymization to preserve double-blind reviewing. Any papers found to be violating this policy will be rejected.

Oral and Best Paper Awards:

We plan to select approximately five papers from the Long Papers track to be presented as oral talks. In addition, we will give out one Best Paper Award for the Long Papers track, one Best Paper Award for the Short Papers track, and a Best Poster Award determined by on-site voting.

Contact:

For any questions, please contact us at aims_iclr2026@alibaba-inc.com.

Accepted Papers (click to expand)
  • CoopEval: Benchmarking Cooperation-Sustaining Mechanisms and LLM Agents in Social Dilemmas Long Paper
    Emanuel Tewolde, Xiao Zhang, David Guzman Piedrahita, Vincent Conitzer, Zhijing Jin
  • AI Realtor: Towards Grounded Persuasive Language Generation for Automated Copywriting Long Paper
    Chenghao Yang, Jibang Wu, Yi Wu, Simon Mahns, Chaoqi Wang, Hao Zhu, Fei Fang, Haifeng Xu
  • Post-Training LLMs as Better Decision-Making Agents: A Regret-Minimization Approach Long Paper
    Chanwoo Park, Ziyang Chen, Asuman E. Ozdaglar, Kaiqing Zhang
  • Test-Time Compute Games Long Paper
    Ander Artola Velasco, Dimitrios Rontogiannis, Stratis Tsirtsis, Manuel Gomez Rodriguez
  • Automating Forecasting Question Generation and Resolution for AI Evaluation Long Paper
    Lawrence Gabriel Phillips, Nikos I. Bosse, Peter Mühlbacher, Jack Wildman, Dan Schwarz
  • SAC-Opt: Semantic Anchors for Iterative Correction in Optimization Modeling Long Paper
    Yansen Zhang, Qingcan Kang, Yujie Chen, Yufei Wang, Xiongwei Han, Tao Zhong, Mingxuan Yuan, Chen Ma
  • Toward a Dynamic Stackelberg Game-Theoretic Framework for Agentic AI Defense Against LLM Jailbreaking Long Paper
    Zhengye Han, Quanyan Zhu
  • Large Language Model (LLM) as an Excellent Reinforcement Learning Researcher in both Single-Agent and Multi-Agent Scenarios Long Paper
    Tianhao Fu, Xinxin Xu, Weichen Xu, Ruilong Ren, Bowen Deng, Jue Chen, Xinyu Zhao, Jian Cao, Xixin Cao
  • Agentic Large Language Models for Decentralized Multi-agent Games Long Paper
    Dom Huh, Prasant Mohapatra
  • Agents for Experiment, Experiments for Agents: A Topological Framework for Automated Mechanism Discovery Long Paper
    Yingjie Zhang, Weizhang Zhu, Chun Feng, Tianshu Sun
  • C2: Cenerative learning module enhanced decision transformer with Constraint-aware loss for auto-bidding Long Paper
    Jinren Ding, Xuejian Xu, Shen Jiang, Zhitong Hao, Jinhui Yang, Peng Jiang
  • Explicit Budget Optimization: Activating Traffic under Budget Constraints in Cold-Start Ad Bidding Long Paper
    Hongchang Wu, Size Wang, Weitong Ou, Zixin Shao, Feihong Liu, Yang Liu, Hongyan Xue, Nianhua Xie
  • Continuous RTS-PnO: Constraint-Aware Training for Robust Rolling-Horizon Budget Allocation Long Paper
    Rassul Magauin, Fuyuan Lyu, Lu Han, Xue Liu
  • SEGB: SELF-EVOLVED GENERATIVE BIDDING WITH LOCAL AUTOREGRESSIVE DIFFUSION Long Paper
    Yulong Gao, Wan Jiang, Mingzhe Cao, Xuepu Wang, Zeyu Pan, Haonan Yang, Ye Liu, Xin Yang
  • Persona Vectors in Games: Measuring and Steering Strategies via Activation Vectors Long Paper
    Johnathan Sun, Andrew Zhang
  • A Robust Multi-Item Auction Design with Statistical Learning Long Paper
    Jiale Han, Xiaowu Dai
  • Towards Predictive Models of Strategic Behaviour in Large Language Model Agents Long Paper
    Jennifer Za, Aristeidis Panos, Jan Cuhel, Samuel Albanie
  • On the Edge of Core (Non-)Emptiness: An Automated Reasoning Approach to Approval-Based Multi-Winner Voting Long Paper
    Ratip Emin Berker, Emanuel Tewolde, Vincent Conitzer, Mingyu Guo, Marijn Heule, Lirong Xia
  • How LLMs Reshape Equilibrium: A Study of Human-AI Competition in Auctions Long Paper
    Yuehu Zhao, Ruoran Chen, Yuxuan Zhang, Simin Huang
  • Equilibrium Structure of High-Resolution Differential Equations for Min–Max Optimization Short Paper
    Federico Praolini, Tatjana Chavdarova
  • Keep Everyone Happy: Online Fair Division of Numerous Items with Few Copies Long Paper
    Arun Verma, Indrajit Saha, Makoto Yokoo, Bryan Kian Hsiang Low
  • Personalization Aids Pluralistic Alignment Under Competition Long Paper
    Natalie Collina, Surbhi Goel, Aaron Roth, Mirah Shi
  • Decision Making under Imperfect Recall: Algorithms and Benchmarks Long Paper
    Emanuel Tewolde, Brian Hu Zhang, Ioannis Anagnostides, Tuomas Sandholm, Vincent Conitzer
  • Leaderboard Incentives: Model Rankings under Strategic Post-Training Long Paper
    Yatong Chen, Guanhua Zhang, Moritz Hardt
  • The Clumsy Liar: Evaluating Incentive-Driven Deception in LLM Agents Long Paper
    Jerick Shi, Terry Jingchen Zhang, Vincent Conitzer, Zhijing Jin
  • Fine-tuning Large Language Model for Automated Algorithm Design Long Paper
    Fei Liu, Rui Zhang, Xi Lin, Zhichao Lu, Qingfu Zhang
  • Iterative Scarcity-Guided Exploration: Bootstrapping Generative Auto-bidding from Narrow Support Long Paper
    Qingmao Yao, Guangzheng Hu, Yusen Huo, Zhilin Zhang, Chuan Yu, Jian Xu, Bo Zheng, Xiaotie Deng
  • CASCADE: Cascaded Scoped Communication for Multi-Agent Re-planning in Disrupted Industrial Environments Long Paper
    Mingjie Bi
  • Calibrating Behavioral Parameters with Large Language Models Long Paper
    Brandon Yee, Krishna Sharma
  • DIRECTING THE UNSCRIPTED: ALT-MIRAGE FOR EMERGENT SOCIAL DECEPTION DRAMA Long Paper
    Liu Yan, Baoyang Chen, Zhao Yang, Huamin Qu, Zhai Lidong
  • COBRA: Contextual Bandit Algorithm for Ensuring Truthful Strategic Agents Long Paper
    Arun Verma, Indrajit Saha, Makoto Yokoo, Bryan Kian Hsiang Low
  • Optimal Aggregation Mechanisms for AI Benchmarking and Platinum Benchmarks Short Paper
    Andreas Haupt, Anka Reuel, Mykel Kochenderfer, Sanmi Koyejo
  • LLM-Auction: Generative Auction towards LLM-Native Advertising Long Paper
    Chujie Zhao, Qun Hu, Shiping Song, Dagui Chen, Han Zhu, Jian Xu, Bo Zheng
  • GT-HarmBench: Benchmarking AI Safety Risks Through the Lens of Game Theory Long Paper
    Pepijn Cobben, X. Angelo Huang, Thao Amelia Pham, Isabel Dahlgren, Terry Jingchen Zhang, Zhijing Jin
  • Steering LLMs for Multi-agent Decision-making using Representation Learning Short Paper
    Dom Huh, Prasant Mohapatra
  • Adaptive Bandit Algorithms for Contextual Matching Markets Long Paper
    Shiyun Lin, Simon Mauras, Vianney Perchet, Nadav Merlis
  • Code Driven Game Theoretic Evolution of LLM Agents as Holistic Strategy Generators Short Paper
    Siwei Li, Xin Wang
  • Learning Revenue-Maximizing Auctions with Neural Affine Maximizer Long Paper
    Yunxuan Ma
  • DecisionLLM: Large Language Models for Long Sequence Decision Exploration Long Paper
    Xiaowei Lv, Zhilin Zhang, Yijun Li, Yusen Huo, Siyuan Ju, Xuyan Li, Hong Chunxiang, Tianyu Wang, Yongcai Wang, Peng Sun, Chuan Yu, Jian Xu, Bo Zheng
  • Prices, Bids, Values: One ML-Powered Combinatorial Auction to Rule Them All Long Paper
    Ermis Soumalias, Jakob Heiss, Jakob Weissteiner, Sven Seuken
  • AIGP: An LLM-Based Framework for Long-Term Value Alignment in E-Commerce Pricing Long Paper
    Chennan Ma, Yanning Zhang, Siqi Hong, Xiuchong Wang, Fei Xiao, Keping Yang, Bo Zheng
  • Computing Equilibria in Games with Stochastic Action Sets Long Paper
    Thomas Schwarz, Ryann Sim, Chun Kai Ling
  • Robust Trust Long Paper
    Piotr Dworczak, Alex Smolin
  • SOK: A Taxonomy of Attack Vectors and Defense Strategies for Agentic Supply Chain Runtime Long Paper
    Shiqi Yang, Wenting Yang, Xiaochong Jiang, Cheng Ji, Yichen Liu
  • MaRCA: Multi-Agent Reinforcement Learning for Dynamic Computation Allocation in Large-Scale Recommender Systems Long Paper
    Wan Jiang, Xinyi Zang, Yudong Zhao, Yusi Zou, Yunfei Lu, Junbo Tong, Yang Liu, Ming Li, Jiani Shi, Xin Yang
  • Allocate Marginal Reviews to Borderline Papers Using LLM Comparative Ranking Long Paper
    Elliot L Epstein, Rajat Vadiraj Dwaraknath, John Winnicki, Thanawat Sornwanee
  • GoT: Robust Information Seeking with LLMs using Game Theory Long Paper
    Langyuan Cui, Chun Kai Ling, Hwee Tou Ng
  • Avoiding the Tragedy of the Commons in AI Regulation via Dynamic Licensing Short Paper
    Rajeev Verma, Anurag Singh, Christian A. Naesseth, Eric Nalisnick, Krikamol Muandet
  • Prompt Optimization Enables Stable Algorithmic Collusion in LLM Agents Short Paper
    Yingtao Tian
  • Performative Personalization Incentivizes Truthfulness in Federated Learning Short Paper
    Kumar Kshitij Patel, Aniket Murhekar
  • Make an Offer They Can't Refuse: Grounding Bayesian Persuasion in Real-World Dialogues without Pre-Commitment Long Paper
    Buwei He, Yang Liu, Zhaowei Zhang, Zixia Jia, Huijia Wu, Zhaofeng He, Zilong Zheng, Yipeng Kang
  • Very Credible Auction Short Paper
    Thanawat Sornwanee
  • Text as the Richest Preference Signal Long Paper
    André F Cruz, Jon Kleinberg, Rediet Abebe
  • Agentic Federated Learning: The Future of Distributed Training Orchestration Long Paper
    Rafael O. Jarczewski, Gabriel Ukstin Talasso, Leandro Aparecido Villas, Allan M. De Souza
  • Learning Against a Strategic Agent in Principal-Agent Games Short Paper
    Raj Kiriti Velicheti, Subhonmesh Bose, Tamer Basar
  • Credibility Governance: A Social Mechanism for Collective Self-Correction under Weak Truth Signals Long Paper
    Wanying He, Lin Yanxi, Zhou Ziheng, Xue Feng, Min Peng, Qianqian Xie, Zilong Zheng, Yipeng Kang
  • Optimal Treatment Assignment from Observational Data: A Decision-focused Learning Approach via Pseudo Labels Long Paper
    Jiaqi Yang, Zicheng Su, Zhichao Zou, Zhen Peng, Wanjing Ma, Kun An
  • Pacing with ROI: Budget Allocation in Sponsored Search Long Paper
    Mohamed A. Abd-Elmagid, Djordje Gligorijevic, Arnob Ghosh, Andrew Perrault, Xinxin Shu, Ness Shroff, Abraham Bagherjeiran
  • Who to Ask and What to Ask: Adaptive Multi-Turn Group Elicitation with LLMs Long Paper
    Ruomeng Ding, Tianwei Gao, Thomas P Zollo, Eitan Bachmat, Richard Zemel, Zhun Deng
  • LLM-as-a-Prophet: Understanding AI's Predictive Intelligence with Prophet Arena Long Paper
    Qingchuan Yang, Simon Mahns, Sida Li, Anri Gu, Jibang Wu, Haifeng Xu
  • GraphScholar: Compositional Strategic Decision Making for Knowledge Graph Reasoning via Relation-Dependency Graphs Long Paper
    Zhonglin Jiang, Hange Zhou, Enjun Du, Xuefeng, Sihaochen, Yingjie Cui, Jingcheng Sha, Yong Chen, Yongqi Zhang
  • Do LLMs Act Like Rational Agents? Measuring Belief Coherence in Probabilistic Decision Making Long Paper
    Khurram Yamin, Jingjing Tang, Santiago Cortes-Gomez, Amit Sharma, Eric Horvitz, Bryan Wilder
  • Learning to Staff: Offline Reinforcement Learning and Fine-Tuned LLMs for Warehouse Staffing Optimization Long Paper
    Kalle Kujanpää, Yuying Zhu, Kristina Lisa Klinkner, Shervin Malmasi
  • Selling Data as a Digital Good with Scaling Valuations Long Paper
    Xiaotie Deng, Yanru Guan, Ningyuan Li, Zihe Wang, Wu Xin, Jie Zhang
  • Optimal Control Meets Online Mechanism: Adaptive Policy Learning with Strategic Agent Response Long Paper
    Juan P. Madrigal Cianci
  • What-If Analysis of Large Language Models: Explore the Game World Using Proactive Thinking Long Paper
    Yuan Sui, Yanming Zhang, Yi Liao, Yu Gu, Guohua Tang, Zhongqian Sun, Yang Wei, Bryan Hooi
  • Influence-Salient Coordination Shaping for Scalable Cooperative MARL Long Paper
    Wei Sheng, Rohan Paleja
  • Visualizing Coalition Formation: From Hedonic Games to Image Segmentation Short Paper
    Pedro Henrique De Paula Franca, Lucas Lopes Felipe, Daniel Sadoc Menasche
  • Understanding Agent Scaling in LLM-Based Multi-Agent Systems via Diversity Long Paper
    Yingxuan Yang, Chengrui Qu, Muning Wen, Laixi Shi, Ying Wen, Weinan Zhang, Adam Wierman, Shangding Gu
  • Belief Estimation as Probabilistic Constraints for Performing Strategic Dialogue Acts Long Paper
    Hengli Li, Zhaoxin Yu, Qi Shen, Chenxi Li, Mengmeng Wang, Tinglang Wu, Yipeng Kang, Yuxuan Wang, Song-Chun Zhu, Zixia Jia, Zilong Zheng
  • Optimally Curating an Event Long Paper
    Mohammadtaghi Hajiaghayi, Sebastien Lahaie, Mohammad Mahdavi, Suho Shin
  • Miscalibrated Belief Updates in LLM Agents under Strategic Uncertainty Short Paper
    Harry Ilanyan, Krish Jain
  • A Comparative Study of Deep Reinforcement Learning Algorithms for Dynamic Option Hedging Long Paper
    Andrei Neagu, Frédéric Godin, Leila Kosseim
  • Pay for The Second-Best Service: A Game-Theoretic Approach Against Dishonest LLM Providers Long Paper
    Yuhan Cao, Yu Wang, Sitong Liu, Miao Li, Yixin Tao, Tianxing He
  • Strategic Hypothesis Testing Long Paper
    Yatong Chen, Safwan Hossain, Yiling Chen
  • AgenticPay: A Multi-Agent LLM Negotiation System for Buyer–Seller Transactions Long Paper
    Xianyang Liu, Shangding Gu, Dawn Song
  • CAFE-RL: Counterfactual Augmented Reinforcement Learning for Mechanism-Aware Onboarding Fraud Detection in E-Commerce Long Paper
    Linfeng Cao, Hang Yin, Yang Zhao, Xinze Guan, Qiang Wang, Ming Ouyang
  • Agent Exchange: An Auction Platform for AI Agent Marketplaces Long Paper
    Yingxuan Yang, Ying Wen, Jun Wang, Weinan Zhang
  • Advancing Regulation in Artificial Intelligence: An Auction-Based Approach Long Paper
    Marco Bornstein, Zora Che, Suhas Julapalli, Abdirisak Mohamed, Amrit Singh Bedi, Furong Huang
Program Committee (click to expand)

We thank the following colleagues for their valuable service as program committee members and reviewers.

The names are listed in alphabetical order.

Nurmyrat Amanmadov, Oluwatoni Akintola, André F Cruz, Bryan Cheng, Juan P. Madrigal Cianci, Lu Chen, Xiaowei Chen, Yatong Chen, Yuhan Cao, Yuwei Cheng, Huanzhang Dou, Jinren Ding, Ruomeng Ding, Yuejia Dou, Zhen Dong, Zhijian Duan, Tianhao Fu, Yiding Feng, Arnob Ghosh, Djordje Gligorijevic, Jingwei Guo, Yanru Guan, Jason Hartline, Lu Han, Meng Hou, Mingming Ha, Qun Hu, Zhengye Han, Harry Ilanyan, Prateek Jalan, Xiaochong Jiang, Yipeng Kang, Changjian Liu, Chenxi Li, Hanbing Liu, Hongtao Lv, Ningyuan Li, Ping Li, Ruohong Liu, Siwei Li, XueJian Li, Yangsu Liu, Yichen Liu, Zhai Lidong, Zhang Lvyang, Anurag Malik, Chennan Ma, Daniel Sadoc Menasche, Shentong Mo, Yi Ma, Yuchao Ma, Yunxuan Ma, Junwei Pan, Lehilton Lelis Chaves Pedrosa, Shang Qin, Gili Rusak, Mahule Roy, Sai Srivatsa Ravindranath, Subhas Roy, Vethavikashini Chithrra Raghuram, Alex Smolin, Johnathan Sun, Krishna Sharma, Manoj Saravanan, Meiqi Sun, Rohit Kumar Salla, Sheng-jie Sun, Thanawat Sornwanee, Wei Sheng, Bin Tong, Jiakai Tang, Jingjing Tang, Yifeng Teng, Yixin Tao, Anoushka Vyas, Raj Kiriti Velicheti, Venkatesh Velugubantla, Bingzhe Wang, Chenyang Wu, Lulu Wen, Mengmeng Wang, Steven Wang, Xingjian Wu, Zirui Wei, Zongqi Wan, Xuanzhi Xia, Yichong Xia, Yidan Xing, Yuwei Xu, Zhibo Xiao, Brandon Yee, Chunwei YANG, Fan Yao, Manoj Yadav, Tian-Le Yang, Wenting Yang, Xiang Yan, Yasuhiro Yoshida, Yeqiu Yang, Yifu Yuan, Yingxuan Yang, Yutong Yin, Boyang Zhou, Chujie Zhao, Dengji Zhao, Hanrui Zhang, Haodong Zhao, Hengyang Zhou, Jue Zhang, Liang Zhang, Muyang Zhao, Ruitao Zhu, Wenxuan Zhang, Yansen Zhang, Yu Zhu, Zhifei Zheng, 2410196@tongji.edu.cn, boses@illinois.edu, chenyu.cw@alibaba-inc.com, cpuligun@asu.edu, dimin.wdm@alibaba-inc.com, huguangzheng2019@ia.ac.cn, krishjain@ucsb.edu, poojitha.vkl@gmail.com, ruiwang0630@gmail.com, tongbin.tb@alibaba-inc.com, wanying.he@alumni.schwarzmanscholars.org,

Schedule

This is the tentative schedule of the workshop. All slots are provided in local time.

Morning Session

9:00 – 9:10 Opening Remarks
9:10 – 9:40 Invited Talk 1
9:40 – 10:10 Invited Talk 2
10:10 – 10:40 Coffee Break
10:40 – 11:40 Oral Presentations
(5 talks, 10 min presentation + 2 min Q&A each)
11:40 – 13:00 Lunch Break

Afternoon Session

13:00 – 13:30 Invited Talk 3
13:30 – 14:00 Invited Talk 4
14:00 – 14:40 Coffee Break
14:40 – 15:10 Invited Talk 5
15:10 – 15:50 Poster Session
15:50 – 16:00 Best Paper Awards & Closing Remarks

Invited Speakers

Song Zuo

Song Zuo

Google

Tuomas Sandholm

Tuomas Sandholm

Carnegie Mellon University

Vijay V Vazirani

Vijay V. Vazirani

University of California, Irvine

Zhenzhe Zheng

Zhenzhe Zheng

Shanghai Jiao Tong University

Workshop Organizers

Xiaotie Deng

Xiaotie Deng

Peking University

Jian Xu

Jian Xu

Alibaba Group

Bo Zheng

Bo Zheng

Alibaba Group

Fabrizio Silvestri

Fabrizio Silvestri

University of Rome

Alireza Fallah

Alireza Fallah

Rice University

Yurong Chen

Yurong Chen

INRIA Paris

Haoran Sun

Haoran Sun

Peking University

QiQi

Qi Qi

Renmin University of China

Zhilin Zhang

Zhilin Zhang

Alibaba Group

Dagui Chen

Dagui Chen

Alibaba Group

Chuan Yu

Chuan Yu

Alibaba Group

Han Zhu

Han Zhu

Alibaba Group