August 23-24, 2024
Carnegie Mellon University
10-Minute Flash Talk Competition
Registration
Registrations for the Flash Talk Competition are closed!
Prizes, Rules, Judges, and Logistics
Prizes:
- First Place: $200
- Second Place: $150
- Third Place: $100
- Fan Favorite: $50
Rules: The competition has the following rules:
- Each participant will have 10 minutes to present their work.
- Each talk will receive scores from the judges.
- Slides or whiteboard can be used to present visuals or math expressions.
The competition will be judged by three faculty judges who will award the top three presenters. We will also have a fan favorite presentation voted by general attendees.
Judges: Fatma Kilinc-Karzan, Emily Diana, Paul Gölz.
Fan Ballot Link: Vote for your favorite talk!
Logistics: Provide PowerPoint slides beforehand. Minimum one week before the conference.
The CMU INFORMS chapter will provide accommodation for one night if needed for accepted flash talk presenters. Hotel rooms will be shared with one other person. We cannot provide travel reimbursements.
YinzOR 2024 Flash Talks
Below are the details for YinzOR 2024 Flash Talks!
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The Whiplash Effect: Congestion Dissipation in a Disrupted Circulatory System
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Chaoyu Zhang, University of Toronto
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Adjusted Wasserstein Distributionally Robust Estimator in Statistical Learning
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Yiling Xie, Georgia Institute of Technology
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Integrative Artificial Intelligence for System Medicine: a Multimodal, Multitask Framework
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Yu Ma, MIT
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A Method for Diagnosing Vulnerability in Supply Chains that have High Uncertainty
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Anthony Cheng, Carnegie Mellon University
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From Submodular Flows to Planar Graphs: A Planarity Criterion Inspired by an OR Question
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Yuchong Pan, MIT
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On the Trade-Off Between Distributional Belief and Ambiguity: Conservatism, Finite-Sample Guarantees, and Asymptotic Properties
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Man Yiu Tsang, Lehigh University
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Ranking Quality and User Engagement on an Online B2B Platform
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Rakesh Allu, Cornell University
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Stochastic Interior-Point method for Inequality constrained optimization
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Qi Wang, Lehigh University
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Optimizer’s Information Criterion: Dissecting and Correcting Bias in Data-Driven Optimization
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Tianyu Wang, Columbia University
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