INFORMS Joural on Data Science

2022 - 2025

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Volume 4, issue 1, 2025

Rethinking Cost-Sensitive Classification in Deep Learning via Adversarial Data Augmentation pp. 1-19

Qiyuan Chen, Raed Al Kontar, Maher Nouiehed, X. Jessie Yang and Corey Lester

Spatio-Temporal Time Series Forecasting Using an Iterative Kernel-Based Regression pp. 20-32

Ben Hen and Neta Rabin

Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling pp. 33-50

Nurretin Dorukhan Sergin, Jiuyun Hu, Ziyue Li, Chen Zhang, Fugee Tsung and Hao Yan

Hierarchical Multilabel Classification for Fine-Level Event Extraction from Aviation Accident Reports pp. 51-66

Xinyu Zhao, Hao Yan and Yongming Liu

Fair Collaborative Learning (FairCL): A Method to Improve Fairness amid Personalization pp. 67-84

Feng Lin, Chaoyue Zhao, Xiaoning Qian, Kendra Vehik and Shuai Huang

A Reduced Modeling Approach for Making Predictions with Incomplete Data Having Blockwise Missing Patterns pp. 85-99

Karthik Srinivasan, Faiz Currim and Sudha Ram

Volume 3, issue 2, 2024

Registration-Free Localization of Defects in Three-Dimensional Parts from Mesh Metrology Data Using Functional Maps pp. 105-123

Xueqi Zhao and Enrique del Castillo

An Optimization-Based Order-and-Cut Approach for Fair Clustering of Data Sets pp. 124-144

Su Li, Hrayer Aprahamian, Maher Nouiehed and Hadi El-Amine

Thompson Sampling-Based Partially Observable Online Change Detection for Exponential Families pp. 145-161

Jie Guo, Hao Yan and Chen Zhang

A Statistical Model for Multisource Remote-Sensing Data Streams of Wildfire Aerosol Optical Depth pp. 162-178

Guanzhou Wei, Venkat Krishnan, Yu Xie, Manajit Sengupta, Yingchen Zhang, Haitao Liao and Xiao Liu

Conjecturing-Based Discovery of Patterns in Data pp. 179-202

J. Paul Brooks, David J. Edwards, Craig E. Larson and Nico Van Cleemput

Multivariate Functional Clustering with Variable Selection and Application to Sensor Data from Engineering Systems pp. 203-218

Zhongnan Jin, Jie Min, Yili Hong, Pang Du and Qingyu Yang

Volume 3, issue 1, 2024

Chronicles of a New Journal: Reflections by the Inaugural Editor-in-Chief pp. 1-5

Galit Shmueli

The Interplay Between Individual Mobility, Health Risk, and Economic Choice: A Holistic Model for COVID-19 Policy Intervention pp. 6-27

Zihao Yang, Ramayya Krishnan and Beibei Li

Sparse Density Trees and Lists: An Interpretable Alternative to High-Dimensional Histograms pp. 28-48

Siong Thye Goh, Lesia Semenova and Cynthia Rudin

Cost Patterns of Multiple Chronic Conditions: A Novel Modeling Approach Using a Condition Hierarchy pp. 49-67

Lida Anna Apergi, Margrét Vilborg Bjarnadóttir, John S. Baras and Bruce L. Golden

Adaptive Exploration and Optimization of Materials Crystal Structures pp. 68-83

Arvind Krishna, Huan Tran, Chaofan Huang, Rampi Ramprasad and V. Roshan Joseph

A Supervised Tensor Dimension Reduction-Based Prognostic Model for Applications with Incomplete Imaging Data pp. 84-104

Chengyu Zhou and Xiaolei Fang

Volume 2, issue 2, 2023

A Nonparametric Subspace Analysis Approach with Application to Anomaly Detection Ensembles pp. 99-115

Irad Ben-Gal, Marcelo Bacher, Morris Amara and Erez Shmueli

Multiblock Parameter Calibration in Computer Models pp. 116-137

Cheoljoon Jeong, Ziang Xu, Albert S. Berahas, Eunshin Byon and Kristen Cetin

Modeling Financial Products and Their Supply Chains pp. 138-160

Margrét Vilborg Bjarnadóttir and Louiqa Raschid

Diversity Subsampling: Custom Subsamples from Large Data Sets pp. 161-182

Boyang Shang, Daniel W. Apley and Sanjay Mehrotra

Interpretable Hierarchical Deep Learning Model for Noninvasive Alzheimer’s Disease Diagnosis pp. 183-196

Maryam Zokaeinikoo, Pooyan Kazemian and Prasenjit Mitra

Credit Risk Modeling with Graph Machine Learning pp. 197-217

Sanjiv Das, Xin Huang, Soji Adeshina, Patrick Yang and Leonardo Bachega

Volume 2, issue 1, 2023

How Can IJDS Authors, Reviewers, and Editors Use (and Misuse) Generative AI? pp. 1-9

Galit Shmueli, Bianca Maria Colosimo, David Martens, Rema Padman, Maytal Saar-Tsechansky, Olivia R. Liu Sheng, W. Nick Street and Kwok-Leung Tsui

GIFAIR-FL: A Framework for Group and Individual Fairness in Federated Learning pp. 10-23

Xubo Yue, Maher Nouiehed and Raed Al Kontar

Sequential Adversarial Anomaly Detection for One-Class Event Data pp. 45-59

Shixiang Zhu, Henry Shaowu Yuchi, Minghe Zhang and Yao Xie

Compressed Smooth Sparse Decomposition pp. 60-80

Shancong Mou and Jianjun Shi

Covariate Dependent Sparse Functional Data Analysis pp. 81-98

Minhee Kim, Todd Allen and Kaibo Liu

Volume 1, issue 2, 2022

Weakly Supervised Multi-output Regression via Correlated Gaussian Processes pp. 115-137

Seokhyun Chung, Raed Al Kontar and Zhenke Wu

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem pp. 138-155

Mochen Yang, Edward McFowland, Gordon Burtch and Gediminas Adomavicius

A Robust Approach to Quantifying Uncertainty in Matching Problems of Causal Inference pp. 156-171

Marco Morucci, Md. Noor-E-Alam and Cynthia Rudin

Visualization in Operations Management Research pp. 172-187

Rahul Basole, Elliot Bendoly, Aravind Chandrasekaran and Kevin Linderman

Commentary on “Visualization in Operations Management Research”: Incorporating Statistical Thinking into Visualization Practices for Decision Making in Operational Management pp. 188-191

Emi Tanaka, Jessica Wai Yin Leung and Dianne Cook

Commentary on “Visualization in Operations Management Research” pp. 192-193

Ben Shneiderman

Commentary on “Visualization in Operations Management Research” pp. 194-195

Ran Jin

Volume 1, issue 1, 2022

Congratulations, It’s Our Inaugural Issue! pp. 1-3

Galit Shmueli

Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters pp. 4-16

Carlos Fernández-Loría and Foster Provost

Commentary on “Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters”: On Loss Functions and Bias–Variance Tradeoffs in Causal Estimation and Decisions pp. 17-18

Dean Eckles

Commentary on “Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters” pp. 19-20

Uri Shalit

Commentary on “Causal Decision Making and Causal Effect Estimation Are Not the Same… and Why It Matters” pp. 21-22

Edward McFowland

Rejoinder to “Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters” pp. 23-26

Carlos Fernández-Loría and Foster Provost

Adapting Reinforcement Learning Treatment Policies Using Limited Data to Personalize Critical Care pp. 27-49

Matt Baucum, Anahita Khojandi, Rama Vasudevan and Robert Davis

STR: Seasonal-Trend Decomposition Using Regression pp. 50-62

Alexander Dokumentov and Rob Hyndman

Constructing Prediction Intervals Using the Likelihood Ratio Statistic pp. 63-80

Qinglong Tian, Daniel J. Nordman and William Q. Meeker

HeBERT and HebEMO: A Hebrew BERT Model and a Tool for Polarity Analysis and Emotion Recognition pp. 81-95

Avihay Chriqui and Inbal Yahav

The Future of Forecasting Competitions: Design Attributes and Principles pp. 96-113

Spyros Makridakis, Chris Fry, Fotios Petropoulos and Evangelos Spiliotis