Jacob M. Chen

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• Bounding the Causal Impact of ML-assisted Decision-Making via Counterfactual Correctness
  42nd Conference on Uncertainty in Artificial Intelligence (UAI 2026)
  Jonathan Zhang, Erik Skalnes, Jacob M. Chen, Michael Oberst
  [arXiv]

• From Efficient Counterfactual Mean Estimation to Estimating Marginal Structural Models
  Poster at American Causal Inference Conference (ACIC) 2026
  Jacob M. Chen, Ilya Shpitser
  [poster]

• Acute Kidney Injury During X-Clamp in Cardiopulmonary Bypass Surgery: A Novel Causal Machine Learning Framework for Analyzing Causes, Mechanisms, and Prevention
  Poster at Society of Thoracic Surgeons (STS) Annual Meeting 2026
  Jacob M. Chen, Shivalika Khanduja, Zachary Darby, Joseph DiNatale, Marc Sussman, Diane Alejo, Steven Menez, Lee Goeddel, Ilya Shpitser, Glenn Whitman
  [poster]

• The TRaditional versus Early Aggressive Therapy for Multiple Sclerosis (TREAT-MS) trial: design and baseline characteristics of participants
  Contemporary Clinical Trials, 2025
  Ellen M. Mowry, Peiqing Qian, William Meador, Sharon Lynch, Ram Narayan, Aimee Borazanci, Derrick Robertson, Sara Qureshi, Jennifer Graves, Jason Silversteen, Megan Esch, Leticia Tornes, Claire Riley, Marwa Kaisey, Nancy Sicotte, Siddharama Pawate, Tirisham Gyang, Torge Rempe, Ahmed Z. Obeidat, Geeta Ganesh, Lana Zhovtis Ryerson, Tyler Smith, John Rose, Aaron Carass, Ornusa Chalayon, Mason Kruse-Hoyer, Monilola Salami, Amy Liu, Blake Dewey, Jacob M. Chen, Elizabeth Ogburn, Carolyn Koch, Jerry Prince, Sandra D. Cassard, Scott D. Newsome
  [Contemporary Clinical Trials]

• Just Trial Once: Ongoing Causal Validation of Machine Learning Models
  41st Conference on Uncertainty in Artificial Intelligence (UAI 2025)
  Jacob M. Chen, Michael Oberst
  [arXiv] [PMLR] [slides]

• On the consistency of supervised learning with missing values
  Statistical Papers, 2024
  Julie Joss, Jacob M. Chen, Nicolas Prost, Gaël Varoquaux, Erwan Scornet
  [springer] [arXiv]

• Proximal Causal Inference With Text Data
  Advances in Neural Information Processing Systems 38 (NeurIPS 2024)
  Jacob M. Chen, Rohit Bhattacharya, Katherine A. Keith
  [paper] [NeurIPS Proceedings] [arXiv]

• Causal Inference With Outcome-Dependent Missingness And Self-Censoring
  39th Conference on Uncertainty in Artificial Intelligence (UAI 2023)
  Jacob M. Chen, Daniel Malinsky, Rohit Bhattacharya
  [arXiv] [OpenReview] [PMLR]