Where the Women Are: Gender Imbalance in Computing and Faculty Perceptions of Theoretical and Applied Research
S. Kleinberg and J. K. Marsh IEEE Access, 2025
Benchmarking Missing Data Imputation Methods for Time Series Using Real-World Test Cases
A. A. Toye, A. Celik, and S. Kleinberg Conference on Health, Inference, and Learning (CHIL), 2025
Causal Inference for Time Series Datasets with Partially Overlapping Variables
L. A. Gomez, J. Claassen, and S. Kleinberg Journal of Biomedical Informatics, 2025
Go Big or Go Hoax: Explanatory Scope and the Believability of Conspiracy Theories
J. K. Marsh and S. Kleinberg CogSci, 2025
Causal and Counterfactual Reasoning about Gradual and Abrupt Events
V. Cheung, C. Leone, D. Lagnado, and S. Kleinberg CogSci, 2025
Predicting Postprandial Glycemic Responses With Limited Data in Type 1 and Type 2 Diabetes
Y. Shen, E. Choi, and S. Kleinberg Journal of Diabetes Science and Technology, 2025 [html]
Personalized Blood Glucose Forecasting from Limited CGM Data Using Incrementally Retrained LSTM
Y. Shen and S. Kleinberg Transactions on Biomedical Engineering, 2025 [html]
2024
Food Records Show Daily Variation in Diet During Pregnancy: Results From the Temporal Research in Eating, Nutrition, and Diet during Pregnancy (TREND-P) Study
S. Kleinberg, J. D. Pleuss, and A. L. Deierlein The Journal of Nutrition, 2024 [html]
Perceived Penalties for Sharing Patient Beliefs with Healthcare Providers
J. K. Marsh, O. Asan, and S. Kleinberg Medical Decision Making, 2024 [html]
Simulation of Health Time Series with Nonstationarity
A. A. Toye, L. Gomez, and S. Kleinberg Conference on Health, Inference, and Learning (CHIL), 2024
Transforming Big Data into AI Ready Data for Nutrition and Obesity Research
D. M. Thomas, R. Knight, J. A. Gilbert3, M. C. Cornelis, M. G. Gantz, K. Burdekin, K. Cummiskey, S. C. J. Sumner, K. P. Sazonov, Edward Gabriel, E. E. Dooley, M. A. Green, A. Pfluger, and S. Kleinberg Obesity, 2024
Objective Determination of Eating Occasion Timing (OREO): Combining self-report, wrist motion and continuous glucose monitoring to detect eating occasions in adults with pre-diabetes and obesity
C. J. Popp, C. Wang, A. Hoover, L. A. Gomez, M. Curran, D. E. St-Jules, S. Barua, M. A. Sevick, and S. Kleinberg Journal of Diabetes Science and Technology, 2024
2023
Less is More: Information Needs, Information Wants, and What Makes Causal Models Useful
S. Kleinberg and J. K. Marsh Cognitive Research: Principles and Implications, 8, 2023 [html]
Simulating Realistic Continuous Glucose Monitor Time Series by Data Augmentation
L. A. Gomez, A. Toye, S. Hum, and S. Kleinberg Journal of Diabetes Science and Technology, 8, 2023 [html]
How Beliefs Influence Choice Perceptions
S. Kleinberg, E. Korshakova, and J. K. Marsh CogSci, 2023
Quantifying the Utility of Causal Models for Decision-Making
E. Korshakova, J. K. Marsh, and S. Kleinberg CogSci, 2023
Classification of Level of Consciousness in a Neurological ICU Using Physiological Data
L. A. Gomez, Q. Shen, K. Doyle, A. Vrosgou, A. Velazquez, M. Megjhani, S. Ghoshal, D. Roh, S. Agarwal, S. Park, J. Claassen, and S. Kleinberg Neurocritical Care, 38(1) 118-128, 2023 [html]
Artificial Intelligence for Predicting and Diagnosing Complications of Diabetes
J. Huang, A. Yeung, D. Armstrong, A. Battarbee, J. Cuadros, J. Espinoza, S. Kleinberg, N. Mathioudakis, M. Swerdlow, and D. Klonoff Journal of Diabetes Science and Technology, 17(1) 224-238, 2023 [html]
2022
Model Machine Learning Practices to Support the Principles of AI and Ethics in Nutrition Research
D. Thomas, S. Kleinberg, A. Brown, M. Crow, N. Bastian, N. Reisweber, R. Lasater, T. Kendall, P. Shafto, R. Blaine, S. Smith, D. Ruiz, C. Morrell, and N. Clark Nutrition and Diabetes, 12, 2022 [html]
Health Information Sourcing and Health Knowledge Quality: Repeated Cross-sectional Survey
E. Korshakova, J. K. Marsh, and S. Kleinberg JMIR Form Res 6(9):e39274, 2022 [html]
Absence Makes the Trust in Causal Models Grow Stronger
S. Kleinberg, E. Alay, and J. K. Marsh CogSci, 2022 [pdf]
The Compelling Complexity of Conspiracy Theories
J. K. Marsh, C. Coachys, and S. Kleinberg CogSci, 2022 [pdf]
Using Momentary Assessment and Machine Learning to Identify Barriers to Self-management in Type 1 Diabetes: Observational Study
P. Zhang, C. Fonnesbeck, D.C. Schmidt, J. White, S. Kleinberg, and S.A. Mulvaney JMIR mHealth and uHealth 10(3), 2022 [html]
2021
Hierarchical Information Criterion for Variable Abstraction
M. Mirtchouk, B. Srikishan, and S. Kleinberg Machine Learning for Healthcare, 2021 [pdf]
Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare
C. Lu, C. K. Reddy, P. Chakraborty, S. Kleinberg, and Y. Ning IJCAI, 2021 [pdf]
Detecting Granular Eating Behaviors From Body-worn Audio and Motion Sensors
M. Mirtchouk and S. Kleinberg BHI, 2021 [pdf]
It's Complicated: Improving Decisions on Causally Complex Topics
S. Kleinberg and J. K. Marsh CogSci, 2021 [pdf]
2020
Comparing Machine Learning Techniques for Blood Glucose Forecasting Using Free-living and Patient Generated Data
H. Hameed and S. Kleinberg Machine Learning for Healthcare, 2020 [pdf]
Tell me something I don't know: How perceived knowledge influences the use of information during decision making
S. Kleinberg and J. K. Marsh CogSci, 2020 [pdf]
Investigating potentials and pitfalls of knowledge distillation across datasets for blood glucose forecasting
H. Hameed and S. Kleinberg Workshop on Knowledge Discovery in Healthcare Data, 2020 [pdf][code on github]
How Causal Information Affects Decisions
M. Zheng, J. K. Marsh, J. V. Nickerson, and S. Kleinberg Cognitive Research: Principles and Implications (CRPI) 5(6), 2020 [pdf]
Automated Meal Detection from CGM Data Through Simulation and Explanation
M. Zheng, B. Ni, and S. Kleinberg JAMIA 26(12):1592-1599, 2019 [pdf]
Lagged Correlations among Physiological Variables as Indicators of Consciousness in Stroke Patients
T. T. Yavuz, J. Claassen, and S. Kleinberg AMIA Annual Symposium, 2019 [pdf][code on github] Homer R. Warner Award (best paper)
Using Domain Knowledge to Overcome Latent Variables in Causal Inference from Time Series
M. Zheng, and S. Kleinberg Machine Learning for Healthcare, 2019 [pdf][code on github]
Automated Estimation of Food Type from Body-worn Audio and Motion Sensors in Free-Living Environments
M. Mirtchouk, D. L. McGuire, A. L. Deierlein, and S. Kleinberg Machine Learning for Healthcare, 2019 [pdf][code on github]
2018
Automated Identification of Causal Moderators in Time-Series Data
M. Zheng, J. Claassen, and S. Kleinberg ACM SIGKDD Causal Discovery Workshop, 2018 [pdf]
2017
Multi-Scale Change Point Detection in Multivariate Time Series
Z. Ebrahimzadeh and S. Kleinberg NIPS Time Series Workshop, 2017 [pdf]
Replicability, Reproducibility, and Agent-based Simulation of Interventions
R. S. Hum and S. Kleinberg AMIA Annual Symposium, 2017 [pdf]
Recognizing Eating from Body-Worn Sensors: Combining Free-living and Laboratory Data
M. Mirtchouk, D. Lustig, A. Smith, I. Ching, M. Zheng, and S. Kleinberg IMWUT 1 (3) (previously UbiComp), 2017 [pdf][data]
A Method for Automating Token Causal Explanation and Discovery
M. Zheng and S. Kleinberg FLAIRS, 2017 [pdf]
2016
Using Uncertain Data from Body-Worn Sensors to Gain Insight into Type 1 Diabetes
N. Heintzman and S. Kleinberg Journal of Biomedical Informatics (JBI) (63):259-268, 2016 [pdf]
Automated Estimation of Food Type and Amount Consumed from Body-worn Audio and Motion Sensors
M. Mirtchouk, C. Merck, and S. Kleinberg UbiComp, 2016 [pdf][data] Best Paper Honorable Mention
Multimodality Sensing for Eating Recognition
C. Merck, C. Maher, M. Mirtchouk, M. Zheng, Y. Huang, and S. Kleinberg Pervasive Health, 2016 [pdf][data]
Causal Structure of Brain Physiology after Brain Injury from Subarachnoid Hemorrhage
J. Claassen, S. A. Rahman, Y. Huang, H. P. Frey, J. M. Schmidt, D. Albers, C. M. Falo, S. Park, S. Agarwal, E. S. Connolly, and S. Kleinberg PLoS ONE, 11(4), 2016 [PLoS]
Causal Explanation Under Indeterminism: A Sampling Approach
C. Merck and S. Kleinberg AAAI, 2016 [pdf][code on github]
2015
Combining Fourier and lagged k-nearest neighbor imputation for biomedical time series data
S. A. Rahman, Y. Huang, J. Claassen, N. Heintzman and S. Kleinberg Journal of Biomedical Informatics (JBI) (58):198-207, 2015 [pdf][code on github]
Unintrusive Eating Recognition using Google Glass
S. A. Rahman, C. Merck, Y. Huang and S. Kleinberg Pervasive Health, 2015 [pdf][data]
Fast and Accurate Causal Inference from Time Series Data
Y. Huang and S. Kleinberg FLAIRS, 2015 [pdf][proofs]
2014
Imputation of Missing Values in Time Series with Lagged Correlations
S. A. Rahman, Y. Huang, J. Claassen, and S. Kleinberg IEEE ICDM Workshop on Data Mining in Biomedical Informatics and Healthcare, 2014 [pdf]
2013
Lessons Learned in Replicating Data-Driven Experiments in Multiple Medical Systems and Patient Populations
S. Kleinberg and N. Elhadad AMIA Annual Symposium, 2013 [pdf]
Causal Inference with Rare Events in Large-Scale Time-Series Data
S. Kleinberg International Joint Conference on Artificial Intelligence (IJCAI), 2013 [pdf]