Meet the Team

We are an Duke-based statistics lab focused on research, outreach, and the effectiveness of caffeine as a creative fuel

Dr. Eric B. Laber

Principal Investigator
James B. Duke Distinguished Professor
Statistical Science and Biostatistics and Bioinformatics
Duke University 2021 – Present

Current Students

Peter Norwood

PhD Student

He/Him

Research interests:
Adaptive Clinical trials, Non-regular Inference for Adaptively-collected Data
Current projects:
Adaptive Randomization in SMARTs, Non-Dominated Adaptive Randomization, Working on the ISPY Breast Cancer Trial

Alex Cloud

Post-Doc

He/Him

Research interests:
Reinforcement learning, statistics
Current projects:
Secret corporate projects

Yen-Chun Liu

PhD Student

Research interests:
Sequential design, Bayesian optimization, and causal inference
Current projects:
Optimal experimental designs for the average treatment effect under incentives

Yinyihong Liu

Master Student

Research interests:
Bandit algorithms
Current projects:
Bandit algorithms under partially ordered surrogates

Caitrin Murphy

PhD Student

Research interests:
Functional data analysis and dynamic treatment regimes
Current projects:
Functional regression problems for physiological data

Shuo Wang

PhD Student

Research interests:
Not specific
Current projects:
Sample Splitting

Piotr Suder

PhD Student

He/Him

Research interests:
Scalable reinforcement learning and optimization in high dimensions, deep neural networks, transfer learning
Current projects:
Nonparametric information methods for reinforcement learning algorithms, Bayesian transfer learning

Derek Dongkyu Cho

PhD Student

He/Him

Research interests:
Reinforcement Learning, Machine Learning, Distribution Robust Optimization
Current projects:
Spatial Reinforcement Learning

Jackson Chen

Master Student

He/Him

Research interests:
Q Learning, Experiment design, Dynamic Treatment Regime
Current projects:
Experimental Design for Q Learning

Hunyong Cho

Post-Doc

He/Him

Research interests:
Reinforcement learning methods and theory
Current projects:
Asymptotics of Bayesian MDPs, Asymptotics of Outcome Weighted Learning, Combinatorial bandits in industrial settings

Young Jun

Undergrad Student

He/Him

Research interests:
Machine learning and functional data analysis
Current projects:
Functional Data Analysis in Healthcare

Devin Johnson

PhD Student

He/Him

Research interests:
Reinforcement Learning
Current projects:
Reinforcement Learning

Andrei Staicu

Undergrad Student

Research interests:
Theoretical computer science and machine learning
Current projects:
Computer vision applications in kitchens

Siyeon Kim

Post-Doc

She/Her

Research interests:
Precision medicine, reinforcement learning
Current projects:
Identifying preferences of patients through treatment assignments by experts

Designers

Danny Schmidt

Art + Design

He/Him

Current projects:
Zombies on Treadmills, Statistics Boardwalk: Vincent Price Presents..., Flying Squirrel

Sasha Chirova

Art + Design

She/Her

Current projects:
Zombies on Treadmills, Flying Squirrel, 2 Minute Stats

Alumni

— Eric Rose, PhD, 2019. “Sample Size and Power Calculations for Estimation of Optimal Treatment Regimes” Post-doctoral researcher, McGill University.
— Lin Dong, PhD, 2019. “Semiparametric Methods for Decision Making and Causal Effect Generalization” Quantitative Associate, Wells Fargo.
— Isaac J. Michaud, PhD, 2019. “Adaptive Experimental Design with Application to Nonproliferation,” Scientist, Statistical Sciences Group, Los Alamos National Lab.
— Wenhao Hu, PhD, 2018. “Noise Addition Methods for Variable Selection.” SAS Institute.
— Brad Ferguson, PhD, 2018. “Semi-supervised Bootstrap with Auxiliary Variables.” Domo.
— Tao Hu, PhD, 2017. “Parametric Thompson Sampling.” Bank of America.
— Nick Meyer, PhD, 2017. “Spatio-temporal Decision Making.” Argo.
— Marshall Wang, PhD, 2017. “Sufficient Markov Processes.” Amazon.
— Shuping Ruan, PhD, 2017. “Constrained Treatment Regimes.” Cisco.
— Yichi Zhang, PhD, 2016. "List-based Treatment Regimes." Post-doctoral fellow, Harvard University.
— Fan Wu, PhD, 2015. “Adaptive Projection Intervals for Non-smooth Functionals.” Seattle Genetics
— Kristin A. Linn, PhD, 2014. “Interactive Methods for Estimation of Optimal Dynamic Treatment Regimes,” (Co-advisor: Len Stefanski). Post-doctoral fellow, University of Pennsylvania.
— Kasturi Talapatra, PhD, 2014. “Computer Aided Simulation Design," (Coadvisor: Len Stefanski). Consultant, SAS Institute.
— Na Zhang, PhD, 2014. “Variable Selection for Personalized Medicine,” (Coadvisor: Howard Bondell). Biostatistician, Bristol-Meyers-Squibb.
— Todd Reigh, MS. 2013. (Co-advisor: Marie Davidian). Biostatistician, Boston Childrens Hospital.