Publications

Books

Papers

  • 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. Gilbert, 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
  • 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]
  • 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]
  • 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
  • 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. Marsh
    CogSci, 2021
    [pdf]
  • 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. 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]
  • 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]
  • Automated Identification of Causal Moderators in Time-Series Data
    M. Zheng, J. Claassen, and S. Kleinberg
    ACM SIGKDD Causal Discovery Workshop, 2018
    [pdf]
  • 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]
  • 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]
  • 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]
  • 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]
  • 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]
  • Nonconvulsive seizures after subarachnoid hemorrhage: multimodality detection and outcomes
    J. Claassen, A. Perotte, D. Albers, S. Kleinberg, J. M. Schmidt, B. Tu, N. Badjatia, H. Lantigua, L. J. Hirsch, S. A. Mayer, E. S. Connoly, and G. Hripcsak
    Annals of Neurology, 2013
    [pdf]
  • A review of causal inference for biomedical informatics
    S. Kleinberg and G. Hripcsak
    Journal of Biomedical Informatics (JBI) (6):1102-1112, 2011
    [pdf] [ScienceDirect]
  • A Logic for Causal Inference in Time Series with Discrete and Continuous Variables
    S. Kleinberg
    International Joint Conference on Artificial Intelligence (IJCAI), 2011
    [pdf]
  • Multiple Testing of Causal Hypotheses
    S. Kleinberg and B. Mishra
    Causality in the Sciences, Oxford University Press 2011
    (P. M. Illari, F. Russo & J. Williamson eds.)
  • The Temporal Logic of Token Causes
    S. Kleinberg and B. Mishra
    Principles of Knowledge Representation and Reasoning (KR), 2010
    Extended version: CIMS Technical Report TR2010-926
    [extended pdf]
  • Predicting malaria interactome classifications from time-course transcriptomic data along the intraerythrocytic developmental cycle
    A. Mitrofanova, S. Kleinberg, J. Carlton, S. Kasif, and B. Mishra
    Artificial Intelligence in Medicine 49(3):167-176, 2010
    [ScienceDirect] [bibtex]
  • Metamorphosis: The Coming Transformation of Translational Systems Biology
    S. Kleinberg and B. Mishra
    ACM Queue, 2009
    [pdf] [bibtex]
  • The Temporal Logic of Causal Structures
    S. Kleinberg and B. Mishra
    Uncertainty in Artificial Intelligence (UAI), 2009
    [pdf] [bibtex] [Supplementary material]
  • Systems Biology via Redescription and Ontologies (III): Protein Classification using Malaria Parasite's Temporal Transcriptomic Profiles
    A. Mitrofanova, S. Kleinberg, J. Carlton, S. Kasif, and B. Mishra
    IEEE BIBM 2008
    [bibtex]
  • Systems Biology via Redescription and Ontologies (II): A Tool for Discovery in Complex Systems
    S. Kleinberg, M. Antoniotti, S. Tadepalli, N. Ramakrishnan and B. Mishra
    Unifying Themes in Complex Systems, Volume VI: Proceedings of the Sixth International Conference on Complex Systems, 2008
    [pdf]
  • Systems Biology via Redescription and Ontologies (I): finding phase changes with applications to malaria temporal data
    S. Kleinberg, K. Casey, and B. Mishra
    Systems and Synthetic Biology (SSB) 1(4):197-205, December 2007
    [pdf] [Springer] [bibtex]
  • Modal Logic, Temporal Models and Neural Circuits: What Connects Them
    S. Kleinberg, M. Antoniotti, N. Ramakrishnan, and B. Mishra
    CIMS Technical Report TR2007-907
    [pdf]
  • Systems Biology via Redescription and Ontologies: Untangling the Malaria Parasite Life Cycle
    S. Kleinberg, K. Casey, and B. Mishra
    LSMS 07, Shanghai, China, September 14-17, 2007
  • Remembrance of Experiments Past: A Redescription Based Tool for Discovery in Complex System
    S. Kleinberg, M. Antoniotti, S. Tadepalli, N. Ramakrishnan and B. Mishra
    Interational Conference on Complex Systems, Quincy, MA, June 2006

Abstracts and Posters

(see CV)