Scholars@Duke

• Background
• 

  Education, Training, & Certifications

  • Ph.D., University of Michigan, Ann Arbor 2011
  • M.A., University of Michigan, Ann Arbor 2007
• 

  Previous Appointments & Affiliations

  • Scholar In Residence of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2020
• Recognition
• 

  In the News

  • FEB 22, 2021

    Duke Research Blog

    Increasing Access to Care with the Help of Big Data

  • SEP 30, 2020

    Eric Laber: From Awe-Inspiring Magic to Problem-Solving Statistics
• Research
• 

  Selected Grants

  • A randomized controlled trial of a novel, evidence-based algorithm for managing lower respiratory tract infection in a resource-limited setting awarded by National Institutes of Health 2022 - 2027
  • Using a SMART Design to Optimize PTSD Symptom Management Strategies Among Cancer Survivors awarded by National Institutes of Health 2019 - 2024
  • FACT: Near Real-Time Spatiotemporal Resource Allocation to Improve Swine Health awarded by North Carolina State University 2021 - 2024
  • A randomized controlled trial of iACT, a novel mHealth intervention for eating disorders in type 1 diabetes awarded by Juvenile Diabetes Research Foundation 2022 - 2023
  • A Patient-centered Intervention Using Technology to Reduce Colorectal Cancer Disparities in Primary Care awarded by University of Florida 2021 - 2023
  • RAPID: Planning for the present and future management of COVID-19 awarded by  National Science Foundation 2021 - 2022
  • A Pragmatic Trial of an Adaptive eHealth HIV Prevention Program for Diverse Adolescent MSM awarded by Northwestern University 2021 - 2022
  • CAREER: Big Computation and the Management of Emerging Infectious Diseases awarded by  National Science Foundation 2021 - 2022
  • Building a reinforcement learning tool for individually tailoring just-in-time adaptive interventions: Extending the reach of mHealth technology for improved weight loss outcomes awarded by University of North Carolina - Chapel Hill 2021 - 2022
• 

  External Relationships

  • Amazon
  • Chapman Hall/CRC Press
• Publications & Artistic Works
• 

  Selected Publications

  • Academic Articles

    • Weltz, Justin, Alex Volfovsky, and Eric B. Laber. “Reinforcement Learning Methods in Public Health.” Clinical Therapeutics 44, no. 1 (January 2022): 139–54. https://doi.org/10.1016/j.clinthera.2021.11.002.
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    • Rose, Eric J., Eric B. Laber, Marie Davidian, Anastasios A. Tsiatis, Ying-Qi Zhao, and Michael R. Kosorok. “Sample Size Calculations for SMARTs,” June 16, 2019.
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    • Luckett, Daniel J., Eric B. Laber, Samer S. El-Kamary, Cheng Fan, Ravi Jhaveri, Charles M. Perou, Fatma M. Shebl, and Michael R. Kosorok. “Receiver Operating Characteristic Curves and Confidence Bands for Support Vector Machines,” July 17, 2018.
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    • Laber, Eric B., Fan Wu, Catherine Munera, Ilya Lipkovich, Salvatore Colucci, and Steve Ripa. “Identifying optimal dosage regimes under safety constraints: An application to long term opioid treatment of chronic pain.” Statistics in Medicine 37, no. 9 (April 2018): 1407–18. https://doi.org/10.1002/sim.7566.
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    • Kelleher, Sarah A., Caroline S. Dorfman, Jen C. Plumb Vilardaga, Catherine Majestic, Joseph Winger, Vicky Gandhi, Christine Nunez, et al. “Optimizing delivery of a behavioral pain intervention in cancer patients using a sequential multiple assignment randomized trial SMART.” Contemp Clin Trials 57 (June 2017): 51–57. https://doi.org/10.1016/j.cct.2017.04.001.
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    • Zhang, Yichi, Eric B. Laber, Anastasios Tsiatis, and Marie Davidian. “Using decision lists to construct interpretable and parsimonious treatment regimes.” Biometrics 71, no. 4 (December 2015): 895–904. https://doi.org/10.1111/biom.12354.
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    • Schulte, Phillip J., Anastasios A. Tsiatis, Eric B. Laber, and Marie Davidian. “Q- and A-learning Methods for Estimating Optimal Dynamic Treatment Regimes.” Stat Sci 29, no. 4 (November 2014): 640–61. https://doi.org/10.1214/13-STS450.
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    • Laber, Eric B., Anastasios A. Tsiatis, Marie Davidian, and Shannon T. Holloway. “Discussion of "Combining biomarkers to optimize patient treatment recommendation".” Biometrics 70, no. 3 (September 2014): 707–10. https://doi.org/10.1111/biom.12187.
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    • Chakraborty, Bibhas, Eric B. Laber, and Ying-Qi Zhao. “Inference about the expected performance of a data-driven dynamic treatment regime.” Clinical Trials (London, England) 11, no. 4 (August 2014): 408–17. https://doi.org/10.1177/1740774514537727.
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    • Vock, David M., Anastasios A. Tsiatis, Marie Davidian, Eric B. Laber, Wayne M. Tsuang, C Ashley Finlen Copeland, and Scott M. Palmer. “Assessing the causal effect of organ transplantation on the distribution of residual lifetime.” Biometrics 69, no. 4 (December 2013): 820–29. https://doi.org/10.1111/biom.12084.
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    • Zhang, Baqun, Anastasios A. Tsiatis, Eric B. Laber, and Marie Davidian. “Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions.” Biometrika 100, no. 3 (2013). https://doi.org/10.1093/biomet/ast014.
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    • Zhang, Baqun, Anastasios A. Tsiatis, Eric B. Laber, and Marie Davidian. “A robust method for estimating optimal treatment regimes.” Biometrics 68, no. 4 (December 2012): 1010–18. https://doi.org/10.1111/j.1541-0420.2012.01763.x.
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    • Zhang, Baqun, Anastasios A. Tsiatis, Marie Davidian, Min Zhang, and Eric Laber. “Estimating Optimal Treatment Regimes from a Classification Perspective.” Stat 1, no. 1 (January 1, 2012): 103–14. https://doi.org/10.1002/sta.411.
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• Teaching & Mentoring
• 

  Recent Courses

  • COMPSCI 571D: Probabilistic Machine Learning 2022
  • ECE 682D: Probabilistic Machine Learning 2022
  • STA 493: Research Independent Study 2022
  • STA 561D: Probabilistic Machine Learning 2022
  • STA 693: Research Independent Study 2022
  • STA 995: Internship 2022
  • COMPSCI 571D: Probabilistic Machine Learning 2021
  • ECE 682D: Probabilistic Machine Learning 2021
  • STA 493: Research Independent Study 2021
  • STA 561D: Probabilistic Machine Learning 2021
  • STA 693: Research Independent Study 2021
  • STA 790-1: Special Topics in Statistics 2021

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