We are pleased to announce the finalists of the 2025 QSR Best Referred Paper Competition, who have been selected out of a very competitive pool. We would like to thank all 30 reviewers who carefully reviewed the submissions.
Here are the finalisted papers and authors in alphabetical order:
CrowdLLM: A Synthetic Crowd Simulator for Crowdsourcing with LLM Workers Augmented with Lightweight Generative Models.
Ryan (Feng) Lin, Hanming Zheng, Keyu Tian, Congjing Zhang, Li Zeng, and Shuai Huang. University of Washington; City University of Hong Kong.
Domain-Informed Reinforcement Learning for Multi-Component Preventive Maintenance Planning under Economic Dependence.
Jaesung Lee, Tatthapong Srikitrungruanga, and Salman Jahani. Department of Industrial and Systems Engineering, Texas A&M University; SAP Labs, LLC.
Physics-Augmented Multi-Task Gaussian Process for Modeling Spatiotemporal Dynamics.
Xizhuo Zhang and Bing Yao. The University of Tennessee.
Scalable First-Order Method for Certifying Optimal k-Sparse GLMs.
Jiachang Liu, Soroosh Shafiee, and Andrea Lodi. Cornell University; Cornell Tech.
We would like to thank all participants and congratulate the finalists!
The finalists will present their works during a competition session at the INFORMS Annual Meeting in Atlanta (Sunday, October 26 | 11:00 AM - 12:15 PM). The winner will be announced and awarded at the QSR business meeting.
Best regards,
QSR Best Referred Paper Competition co-chairs
Jia Liu, Shancong Mou, Xiaochen Xian
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Xiaochen Xian
Assistant professor
Georgia Institute of Technology
Atlanta GA
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