2021 Prize Winner

INFORMS 2021 Data Mining and Decision Analytics Workshop Best Paper Competition Awards


Best Applied Paper Finalists

    • Ziyue Li

    Tensor Topic Models with Graphs and Their Applications on Individualized Travel Patterns

    •  Shenghan Guo

    Predicting Nugget Size of Resistance Spot Welds Using Infrared Thermal Videos With Image Segmentation and Convolutional Neural Network

    •  Guanzhou Wei

    Physics-informed Statistical Modeling for Wildfire Aerosols Propagation using Multi-source Geostationary Satellite Remote-sensing Image Streams

    •  Shixiang Zhu

    Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data



    The Best Applied Paper Award Winner:

    Guanzhou Wei, Venkat Krishnan, Manajit Sengupta, Yu Xie, Haitao Liao, Xiao Liu - Department of Industrial Engineering, University of Arkansas

    Physics-informed Statistical Modeling for Wildfire Aerosols Propagation using Multi-source Geostationary Satellite Remote-sensing Image Streams

    Best Theoretical Paper Finalists

    •  Naichen Shi

    Fed-ensemble: Improving Generalization through Model Ensembling in Federated Learning

    • Yinan Wang

    WOOD: Wasserstein-based Out-of-Distribution Detection

    • Botao Wang

    Attention-based Anomaly Detection for Time Series with Principal and Residual Space Monitoring

    •  Nurretin Dorukhan Sergin

    Low-rank and Sparse Tensor Decomposition with RidgeRegularized Subspace Clustering for Metro Passenger Flow Modeling


        The Best Theoretical Paper Award Winner:


        Yinan Wang, Wenbo Sun, Jionghua (Judy) Jin, Zhenyu (James) Kong, Xiaowei Yue - Virginia Tech

        WOOD: Wasserstein-based Out-of-Distribution Detection



        Data Mining Best Paper Awards: 
        Student / General Tracks

        Best Student Paper Finalists

        • Efficient Global Optimization of Two-layer ReLU Networks: Adversarial Training and Quadratic-time Algorithms

        Yatong Bai, Tanmay Gautam, Somayeh Sojoudi (UC Berkeley)


        • Sparse Plus Low Rank Matrix Decomposition: A Discrete Optimization Approach

        Ryan Cory-Wright & Nicholas A.G. Johnson, Dimitris Bertsimas (MIT)


        • A Sparsity-induced Active Anomaly Discovery Method and its Applications in Additive Manufacturing

        Bo Shen, James Kong (Virginia Tech)


        • Unbiased Subdata Selection for Fair Classification: A Unified Framework and Scalable Algorithms

        Qing Ye, Weijun Xie (Virginia Tech)

         


            The Winner

            • Sparse Plus Low Rank Matrix Decomposition: A Discrete Optimization Approach

            by Ryan Cory-Wright & Nicholas A.G. Johnson, Dimitris Bertsimas (MIT)


            Best  Paper Finalists

            • Prediction with Missing Data

            Dimitris Bertsimas (MIT) Arthur Delarue (MIT), Jean Pauphilet (London School of Business)

            • Acceptable Set Topic Modeling

            Lauren Berk Wheelock (Dyno Therapeutics), Dessislava A. Pachamanova (Babson College & MIT)

            • Online Learning via Offline Greedy Algorithms: Applications in Market Design and Optimization

            Rad Niazadeh (UC, Booth School of Business), Negin Golrezaei (MIT), Joshua Wang (Google), Fransisca Susan (MIT), Ashwinkumar Badanidiyuru(Google)

            • Bandit Learning for Proportionally Fair Allocations

            Tianyu Wang(Fudan Univ.), Cynthia Rudin (Duke University)

               
              The Winner

              • Acceptable Set Topic Modeling

              Lauren Berk Wheelock (Dyno Therapeutics), Dessislava A. Pachamanova (Babson College & MIT)