INFORMS Joural on Data Science

2022 - 2026

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Volume 5, issue 2, 2026

Improved Local Indicators of Spatial Association Analysis for Zero-Heavy Crack Cocaine Seizure Data pp. 81-101

Eunseong Jang, Margrét V. Bjarnadóttir, Marcus Boyd and S. Raghavan

Quantifying Grid Resilience Against Extreme Weather Using Large-Scale Customer Power Outage Data pp. 102-118

Shixiang Zhu, Rui Yao, Yao Xie, Feng Qiu, Yueming (Lucy) Qiu and Xuan Wu

Network Analytics for Anti-money Laundering—A Systematic Literature Review and Experimental Evaluation pp. 119-154

Bruno Deprez, Toon Vanderschueren, Bart Baesens, Tim Verdonck and Wouter Verbeke

Toward Replication-Robust Analytics Markets pp. 155-170

Thomas Falconer, Jalal Kazempour and Pierre Pinson

Resolving Conflicts in Crowds: An Earnings Forecast Application pp. 171-190

Houping Xiao and Shiyu Wang

Volume 5, issue 1, 2026

Call for Papers— INFORMS Journal on Data Science Virtual Special Issue on Artificial Intelligence and Data Science for Healthcare pp. iii-iv

Chirantan Chatterjee, Julia Fleck, Yeming Gong and Shuai Huang

Making Operations Research More Accessible: Insights from the Rise of Machine Learning pp. 1-13

Tho V. Le, Laura A. Albert and Thibaut Vidal

Synergizing Artificial Intelligence and Operations Research: Perspectives from INFORMS Fellows on the Next Frontier pp. 14-23

Holly Wiberg, Tinglong Dai, Henry Lam and Radhika Kulkarni

Maximum Covariance Unfolding: A Novel Covariate-Based Manifold Learning Approach for Point Cloud Regression pp. 24-42

Qian Wang and Kamran Paynabar

Online Modeling and Monitoring for Dependent Dynamic Processes Under Resource Constraints pp. 43-64

Tanapol Kosolwattana, Huazheng Wang and Ying Lin

An Agglomerative Clustering Algorithm for Simulation Output Distributions Using Regularized Wasserstein Distance pp. 65-80

Mohammadmahdi Ghasemloo and David J. Eckman

Volume 4, issue 3, 2025

Call for Papers— INFORMS Journal on Data Science Virtual Special Issue on the Dual Edge of AI: Catalyzing and Challenging the Future of Energy Systems pp. iii-iv

Ahmed Aziz Ezzat, Merve Bodur, Ramteen Sioshansi, Zijun Zhang and Shixiang (Woody) Zhu

Observational vs. Experimental Data When Making Automated Decisions Using Machine Learning pp. 197-229

Carlos Fernández-Loría and Foster Provost

Estimating Hidden Epidemic: A Bayesian Spatiotemporal Compartmental Modeling Approach pp. 230-247

Che-Yi Liao, Peiliang Bai, Lance A. Waller and Kamran Paynabar

Stochastic Neighbourhood Components Analysis pp. 248-264

Graham Laidler, Lucy E. Morgan, Nicos G. Pavlidis and Barry L. Nelson

Graph-Based Feature Selection Method Under Budget Constraint for Multiclass Classification Problems pp. 265-282

David Levin and Gonen Singer

Volume 4, issue 2, 2025

Call for Papers— INFORMS Journal on Data Science Virtual Special Issue on Generative AI, Foundation Models, and Deep Learning with Applications to Business Analytics pp. iii-iv

Ahmed Abbasi, Ningyuan Chen, Xiaocheng Li and Xiao Liu

Call for Papers— INFORMS Journal on Data Science Virtual Special Issue on Data Science for Digital Twin Technologies pp. v-vi

Eunshin Byon, Jianhua Huang, Andrea Matta and Eunhye Song

Cost-Aware Calibration of Classifiers pp. 101-113

Mochen Yang and Xuan Bi

Nonstationary and Sparsely-Correlated Multioutput Gaussian Process with Spike-and-Slab Prior pp. 114-132

Xinming Wang, Yongxiang Li, Xiaowei Yue and Jianguo Wu

Detecting Multiple Changepoints by Exploiting Their Spatiotemporal Correlations: A Bayesian Hierarchical Approach pp. 133-153

Xian Chen, Kun Huang, Weichi Wu and Hai Jiang

Clustering and Representative Selection for High-Dimensional Data with Human-in-the-Loop pp. 154-172

Sheng-Tao Yang, Jye-Chyi Lu and Yu-Chung Tsao

Solar Radiation Ramping Events Modeling Using Spatio-Temporal Point Processes pp. 173-196

Chen Xu, Minghe Zhang, Yao Xie, Feng Qiu and Andy Sun

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