Awards

INFORMS 2019 Data Mining Section Best Paper Competition

The Data Mining (DM) Section of INFORMS announces the DM Best Paper Competition to recognize excellence among its members. Four finalists for the Best Paper Award will be selected to make oral presentations in a DM refereed session at INFORMS Annual Conference to be held in Seattle, WA, Oct. 20-23, 2019.

The objective of the best paper competition is to recognize excellence among the high-quality research works of DM section members, and brings prestige to DM Section as well as to the recipients. Topics on methodological developments and applications related to data mining are welcome, including but not limited to:

• Large-Scale Data Analytics and Big Data – Data-Driven Decision-Making
• Visual Analytics
• Web Analytics / Web Mining
• Classification, Clustering, and Feature Selection – Text mining
• Reliability & Maintenance
• Bayesian Data Analytics
• Healthcare Analytics
• Simulation / Optimization in Data Analytics
• Interpretable data mining
• Longitudinal data analysis
• Causal Mining (Inference)
• Analytics in social Media & finance
• Anomaly Detection
• Other Industrial Applications of Data Science

Eligibility Requirements:

• Award nominees must be a member of the DM Section.
• The submitted paper should be unpublished work.
• Previous finalists who wish to compete again should submit an entirely different paper.
• The finalists will be announced before the conference and will present their papers in the session of DM Best Paper Competition at INFORMS 2019 Annual Conference.
• Paper considered for this competition MAY NOT be simultaneously submitted to other competitions in the INFORMS 2019 Annual Conference.
• Required paper format: maximum of 12 printed pages with 1 inch margins, single column, single-spaced.

To participate, please submit a blinded as well as an unblinded version of your paper in PDF format to the competition coordinators with the email subject “AuthorName-Affiliation-DM2019” prior to the deadline of July 15, 2019. Late submission will not be accepted. All submitted papers will be reviewed and ranked by external referees. The winner of the competition will be decided upon the review evaluation and oral presentation at the conference.

If you have any questions, please contact the competition coordinators Dr. Changqing Cheng ccheng@binghamton.edu and Dr. Evangelos Triantaphyllou trianta@csc.lsu.edu.

INFORMS 2019 Data Mining Section Best Student Paper Competition

The Data Mining (DM) Section of INFORMS announces the DM Best Student Paper Competition to recognize excellence among its student members. Four finalists for the Best Student Paper Award will be selected to make oral presentations in a DM refereed session at INFORMS Annual Conference to be held in Seattle, WA, Oct. 20-23, 2019.

The objective of the best paper competition is to recognize excellence among the high-quality research works of DM section student members, and brings prestige to DM Section as well as to the recipients. Topics on methodological developments and applications related to data mining are welcome, including but not limited to:

• Large-Scale Data Analytics and Big Data – Data-Driven Decision-Making
• Visual Analytics
• Web Analytics / Web Mining
• Classification, Clustering, and Feature Selection – Text mining
• Reliability & Maintenance
• Bayesian Data Analytics
• Healthcare Analytics
• Simulation / Optimization in Data Analytics
• Interpretable data mining
• Longitudinal data analysis
• Causal Mining (Inference)
• Analytics in social Media & finance
• Anomaly Detection
• Other Industrial Applications of Data Science

Eligibility Requirements and Application Process:

• Award nominees should be a student member of the DM Section by the time of submission, and should be the main author of the submitted work. A confirmation letter from the advisor or mentor is required.
• The submitted paper should be unpublished work.
• Previous finalists who wish to compete again should submit an entirely different paper.
• The finalists will be announced before the conference and will present their papers in the session of DM Best Student Paper Competition at INFORMS 2019 Annual Conference.
• Paper considered for this competition MAY NOT be simultaneously submitted to other competitions in the INFORMS 2019 Annual Conference.
• Required paper format: maximum of 12 printed pages with 1 inch margins, single column, single-spaced.

To participate, please submit a blinded as well as an unblinded version your paper in PDF format, along with the signed confirmation letter, to the competition coordinators with the email subject “AuthorName-Affiliation-DM2019-Student” prior to the deadline of July 15, 2019. Late submission will not be accepted. All submitted papers will be reviewed and ranked by external referees. The winner of the competition will be decided upon the review evaluation and oral presentation at the conference.

If you have any questions, please contact the competition coordinators Dr. Changqing Cheng ccheng@binghamton.edu and Dr. Evangelos Triantaphyllou trianta@csc.lsu.edu.

• Di Wang, Xi Zhang, Kaibo Liu, title: A Spatiotemporal Prediction Approach for A 3D Thermal Field from Sensor Networks

• Feng Liu, Li Wang, Yifei Lou, Ren-Cang Li, Patrick L. Purdon, titled: Probabilistic Structure Learning for EEG/MEG Source Imaging with Hierarchical Graph Prior

• “Graphical Lasso and Thresholding: Equivalence and Closed- Form Solutions” 
by Salar Fattahi (student) and Somayeh Sojoudi, University of California Berkeley.
• “Learning Valuation Distributions from Bundle Sales” 
by student: Will Ma (student) and David Simchi-Levi, MIT
• “Confounding-Robust Policy Improvement”, Angela Zhou (student) and Nathan Kallus, Cornell University

• “Optimizing Objective Functions Determined from Random Forests”, Max Biggs (student) and Rim Hariss, MIT
• “Multiple Tensor-on-Tensor Regression: An Approach for Modeling Processes with Heterogeneous Sources of Data”, Mostafa Reisi Gahrooei (student), Hao Yan, Kamran Paynabar, and Jianjun Shi, Georgia Institute of Technology 

• INFORMS 2017 Data Mining Best Paper Awards: The information on the four finalists and their papers (presenting student's name is highlighted in bold) are as follows:

  Applied Track 

  • "Data Science Based Simulation and Optimization of Soybean Variety Selection" by Durai Sundaramoorthi (non-student), Washington University in Saint Louis.

  • "Dynamic Multivariate Functional Data Modeling via Sparse Subspace Learning" by Chen Zhang (student), National University of Singapore   

• Theoretical Track  
  

  • "Wasserstein Distributional Robustness and Regularization in Statistical Learning" by Rui Gao  (student), Georgia Institute of Technology.

  • "Frequentist Consistency of Variational Bayes" by Yixin Wang (student), Columbia University

Here is the photo of the finalists: 
 

  
2017 DMA Workshop Non-Student Paper Award Winner


 Changqing Cheng, State University of New York at Binghamton
 "Multi-scale Gaussian Process for Dynamic Evolution Prediction of Complex Systems "

PAST AWARDS

INFORMS 2016  Data Mining Best Paper Awards: The information on the four winners and their papers (presenting person's name is highlighted in bold) are as follows:

• "Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery" by Tuo Zhao from John Hopkins University.

  
  
  

• "Robust PCA via L1-Norm Line Fitting" by Paul Brooks and Jose Dula from Virginia Commonwealth University.

  

• "Sequence Graph Transform (SGT): A Feature Extraction Function for Sequence Data Mining" by Chitta Ranjan from Georgia Tech.

  

• "Residual Useful Lifetime Prediction Using a Degradation Image Stream" by Xiaolei Fang from Georgia Tech

  

   

• INFORMS 2015 Data Mining Best Student Paper Finalists: The information on the four finalists and their papers (presenting student's name is highlighted in bold) are as follows:

  • "Sparse Precision Matrix Selection for Fitting Gaussian Random Field Models to Large Data Sets" by Sam Davanloo Tajbakhsh, Enrique Del Castillo and Necdet Serhat  Aybat from Penn State University.

  • "Falling Rule Lists" by Fulton Wang and Cynthia Rudin from MIT.

  • "Sensor-Driven Condition-Based Generation Maintenance and Operations Scheduling" by Murat Yildirim and Nagi Gebraeel from Georgia Tech.

  • Winner: "When Wind Meets Turbines: A New Statistical Approach for Characterizing the Heterogeneous Wake Effects in Multi-turbine Wind Farms" by Mingdi You and   Eunshin Byon from University of Michigan.

Here are some photos of the finalists: