NeurIPS 2026 WORKSHOP
Second Workshop on ML×OR:
Mathematical Foundations and Operational Integration of Machine Learning for Uncertainty-Aware Decision-Making
Supported by
INFORMS Applied Probability Society
December 2026
NeurIPS 2026 · Atlanta, Georgia, USA

We are excited to invite submissions to the NeurIPS 2026 Second Workshop on MLxOR: Mathematical Foundations and Operational Integration of Machine Learning for Uncertainty-Aware Decision-Making, organized with support from the INFORMS Applied Probability Society. The workshop will be held in person on December 12 or 13 in Atlanta, GA, USA, as part of the NeurIPS 2026 conference.

Launched in 2025, the inaugural MLxOR workshop explored the growing synergy between Machine Learning (ML) and Operations Research (OR) and attracted a large number of high-quality submissions and attendees, fostering productive interactions in these interdisciplinary communities. Building on this momentum, MLxOR 2026 will continue to present recent developments, discuss challenges, and publicize emerging research opportunities in data-centric decision-making that leverage both the rapid advancement of ML and the principled methodological rigor of OR. In addition, MLxOR 2026 will emphasize a more focused and timely theme of “decision-making with GenAI+OR”.

We welcome submissions that develop new methodologies, provide theoretical insights, or present real-world applications at the intersection of ML and OR. This year’s workshop will feature a special emphasis on the integration of Generative AI into decision sciences. Relevant topics include, but are not limited to:

  • Policy design, learning, and evaluation powered by Generative AI and digital twins
  • Decision-focused training of generative models
  • Integration of Generative AI into data-driven optimization and operational decision-making
  • Evaluating catastrophic risks of Generative AI using OR techniques, and conversely addressing rare-event problems using generative modeling
  • Agentic AI for closed-loop decision-making and autonomous operational systems

We encourage submissions from researchers across ML, OR, applied probability, and statistics, as well as practitioners from industry and public sector organizations. Any works broadly relevant to decision-making via GenAI+OR, in subareas such as reinforcement learning, sequential and adaptive decision-making, stochastic control and optimization, distributional robustness, causal inference, foundation models, simulation and digital twins, and applications in healthcare, logistics, manufacturing, transportation, finance, energy systems, revenue management and other operational domains are all welcome.

In addition to the presentation of accepted papers, the workshop will feature keynote talks, panel discussions, and plenty of opportunities to interact among participants.

Like last year, we also plan to provide financial support for selected students and junior researchers who contribute to the workshop. More details on the application procedure will be available soon.

Call for Papers

Submission Guildlines

  • Submission site:
    https://openreview.net/group?id=NeurIPS.cc/2026/Workshop/MLxOR
  • Paper length: Maximum 4 pages for the main body, using the NeurIPS conference format. Unlimited references and supplemental materials are permitted beyond the page limit for the main body. However, reviewers are not obliged to review the supplemental materials.
  • Non-anonymity and formatting: Submissions are non-anonymous. Moreover, please use the NeurIPS 2026 paper format:
    https://neurips.cc/Conferences/2026/CallForPapers (in the provided latex template, please adopt the single-blind format by using the “sglblindworkshop” option, and you may drop the NeurIPS Paper Checklist expected for main conference submissions; this checklist is not required for our workshop’s submissions).
  • Eligibility policy: Workshop papers are non-archival. That is, submission to the workshop will not preclude future journal or conference publication. On the other hand, per this year’s NeurIPS conference policy, previously published works, including papers accepted to and presented at this year’s main NeurIPS conference, are not eligible to appear in a workshop, as the workshop goal is to facilitate dynamic discussion of work in progress and future directions.

All accepted papers will be presented in one of the poster sessions at the workshop. In addition, several selected papers will be chosen as “spotlight” for oral presentations.

Moreover, we will continue and expand the workshop-to-journal pipeline from our inaugural workshop last year, where selected outstanding workshop submissions will be invited to submit a full journal version. This year, we are coordinating with three journals, Stochastic Systems, Mathematics of Operations Research, and Operations Research, for workshop-to-journal conversion. Additional details will be announced as they become available.

Important Dates

  • Submission deadline: August 31, 2026 (AoE)
  • Paper Decision Notification: September 29, 2026 (AoE)
  • Workshop Date and Location: December 12 or 13, 2026, in Atlanta, GA, USA

If you have any questions or would like additional information, please feel free to reach out to us via: neurips.mlxor.workshop@gmail.com.

Schedule

The tentative schedule is shown below and will be updated soon.

TimeEvent
8:30 – 9:00Keynote Talk 1
9:00 – 10:00Poster Session 1
10:00 – 10:30Coffee Break
10:30 – 11:15Panel Discussion 1
11:15 – 11:55Spotlight Presentations
11:55 – 12:45Lunch
12:45 – 13:45Poster Session 2
13:45 – 14:15Keynote Talk 2
14:15 – 14:45Coffee Break
14:45 – 15:45Poster Session 3
15:45 – 16:15Keynote Talk 3
16:15 – 17:00Panel Discussion 2

The program and times are tentative and subject to change. Speakers will be announced.

Speakers & Panelists

The following speakers and panelists are confirmed so far.

Organizers

Program Committee Members

Alessandro Arlotto (Duke Univ.), Jackie Baek (New York Univ.), Mohsen Bayati (Stanford Univ.), Sem Borst (Eindhoven Univ. of Technology), Prakash Chakraborty (Pennsylvania State Univ.), Xinyun Chen (The Chinese Univ. of Hong Kong, Shenzhen), Yi Chen (Hong Kong Univ. of Science and Technology), Yudong Chen (Univ. of Wisconsin-Madison), Zaiwei Chen (Purdue Univ.), Andrew Daw (Univ. of Southern California), Souvik Dhara (Georgia Institute of Technology), Vassilis Digalakis (Boston Univ.), Eugene A. Feinberg (Stony Brook Univ.), Yiding Feng (Hong Kong Univ. of Science and Technology), Michael Fu (Maryland), Rui Gao (Univ. of Texas at Austin), Xuefeng Gao (The Chinese Univ. of Hong Kong), Julia Gaudio (Northwestern Univ.), Soumyadip Ghosh (IBM Research), Varun Gupta (Univ. of Utah), X.Y. Han (Univ. of Chicago Booth School of Business), David Holtz (Columbia Univ.), Chamsi Hssaine (Univ. of Southern California), Yuchen Hu (Columbia Univ.), Dongyan Lucy Huo (Hong Kong Univ. of Science and Technology), Yanwei Jia (The Chinese Univ. of Hong Kong), Jiashuo Jiang (Hong Kong Univ. of Science and Technology), Yash Kanoria (Columbia Univ.), Sajad Khodadadian (Virginia Tech), Lihua Lei (Stanford Univ.), Marc Lelarge (Inria), Andrew A. Li (Carnegie Mellon Univ.), Hannah Li (Columbia Univ.), Mo Liu (Univ. of California, Berkeley), Sheng Liu (Univ. of Toronto), Weiliang Liu (The Chinese Univ. of Hong Kong), Yueyang Liu (Stanford Univ.), Jiaqi Lu (The Chinese Univ. of Hong Kong, Shenzhen), Thodoris Lykouris (Massachusetts Institute of Technology), Yu Ma (Univ. of Wisconsin-Madison), Xiaojie Mao (Tsinghua Univ.), Gal Mendelson (North Carolina State Univ.), Wenlong Mou (Univ. of Toronto), Viet Anh Nguyen (The Chinese Univ. of Hong Kong), Tianyi Peng (Columbia), Chara Podimata (Massachusetts Institute of Technology), Meng Qi (Cornell Univ.), Chao Qin (Stanford Univ.), Luc Rey-Bellet (Univ. of Massachusetts Amherst), Ilya Ryzhov (Univ. of Maryland), Roshni Sahoo (Stanford Univ.), Vahid Sarhangian (Univ. of Toronto), Neha Sharma (Univ. of Pennsylvania), Cong Shi (Univ. of Miami), Pengyi Shi (Purdue Univ.), David Simchi-Levi (MIT), Wenpin Tang (Columbia Univ.), Bruno Tuffin (Inria), Kaizheng Wang (Columbia Univ.), Tianyu Wang (Columbia Univ.), Weina Wang (Carnegie Mellon Univ.), Wentao Weng (Massachusetts Institute of Technology), Ruoyu Wu (Iowa State Univ.), Yao Xie (Georgia Tech), Linwei Xin (Cornell), Yunbei Xu (National Univ. of Singapore), Chen Yan (Univ. of Michigan), Zixian Yang (Univ. of Michigan), David D. Yao (Columbia Univ.), Lei Ying (Univ. of Michigan), Christina Yu (Cornell Univ.), Assaf Zeevi (Columbia), Emily Zhang (Massachusetts Institute of Technology), Jingwei Zhang (Cornell Univ.), Wenxin Zhang (Columbia Univ.), Xiaowei Zhang (Hong Kong Univ. of Science and Technology), Jinglong Zhao (Boston Univ.), Angela Zhou (Univ. of Southern California), Xunyu Zhou (Columbia Univ.), Ruihao Zhu (Cornell Univ.), Bert Zwart (CWI and Eindhoven Univ. of Technology)

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