Meet the Team

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

Dr. Eric B. Laber

Principal Investigator
Professor of Statistics
Faculty Scholar
NC State 2011 – Present

Current Students

Matthew Zabka

Post-Doc

Research interests:
Topological data analysis and random topological spaces
Current projects:
Counting Morse functions up to persistence and investigating cohomology operations on random spaces

Eric Rose

PhD

Research interests:
Dynamic treatment regimes, causal inference, and reinforcement learning
Current projects:
Q-learning for time-to-event data

Jesse Clifton

PhD Student

Research interests:
Reinforcement learning and artificial intelligence
Current projects:
Spatio-temporal decision problems and model-based exploration tuning

Yeng Saanchi

PhD Student

Research interests:
Predictive modeling and variable selection
Current projects:
Exploring similarities between stochastic gradient descent methods and classical regularization methods

Alex Cloud

PhD Student

Research interests:
Reinforcement learning and interpretable models
Current projects:
Adversarial decision making in games with imperfect information

Lili Wu

PhD Student

Research interests:
Reinforcement learning, interpretable policy, and off policy evaluation
Current projects:
Inference of decision list and parameterized exploration

Khuzaima Hameed

PhD Student

Research interests:
Optimal treatment regimes on networks, automation, and mobile health
Current projects:
Detecting influence on social media, AWS DeepRacer, and network model estimation

Kyle Duke

PhD Student

Research interests:
Dynamic treatment regimes, experimental design, and reinforcement learning
Current projects:
Dynamic treatment regimes with multi-component treatments and optimal exploration and patient horizon

Conor Artman

PhD Student

Research interests:
Reinforcement learning, statistical learning, and agent-based modeling
Current projects:
Efficient policy estimation of multi-agent reinforcement learning

Yunshu Zhang

PhD Student

Research interests:
Causal inference and reinforcement learning
Current projects:
High-dimensional precision medicine from patient-derived xenografts

Nick Kapur

PhD Student

Research interests:
Sports analytics and reinforcement learning
Current projects:
Madden decision making and working for the LA Dodgers

Ben Hu

PhD Student

Research interests:
Reinforcement learning and deep learning
Current projects:
AWS DeepRacer

Robert Pehlman

PhD Student

Research interests:
Computational statistics and machine learning
Current projects:
Functional Q-learning

Zekun (Jack) Xu

PhD Student

Research interests:
Hidden Markov models and partially-observable Markov decision process
Current projects:
Partially-observable Markov decision process for dynamic treatment regimes

Zhen Li

PhD Student

Research interests:
Posterior sampling in reinforcement learning and multi-agent reinforcement learning
Current projects:
Convergence rates of posterior distribution in Markov decision process and Thompson sampling for pursuit-evasion problems

Cole Manschot

PhD Student

Research interests:
Sports analytics, randomization in clinical trial design, and computer vision
Current projects:
Reinforcement learning in personalized trials, small object detection in sports, and constrained optimizations

Kade Young

PhD Student

Research interests:
Sports analytics, computer vision, and reinforcement learning
Current projects:
Reinforcement learning in personalized medicine/education and object detection in sports

Peter Norwood

PhD Student

Research interests:
Causal inference, dynamic treatment regimes, and statistical learning
Current projects:
Adaptive randomization in dynamic treatment regimes

James Gilman

PhD Student

Research interests:
Reinforcement learning and game theory
Current projects:
Reinforcement learning for video games and card games

Saran Ahluwalia

Post-Bacc Student

Research interests:
Reinforcement learning, language modeling, deep learning, and statistical learning applied to urban policy and public health
Current projects:
Curiosity driven learning for first player games and spatio-temporal decision problems

Jess Phillips

Undergrad Student

Research interests:
Traffic modeling/analysis and reinforcement learning
Current projects:
Times series forecasting through reinforcement learning

Liam Dao

Undergrad Student

Research interests:
Sports analytics
Current projects:
Object detection in sports

Jonathan Moore

Undergrad Student

Research interests:
Machine learning and programming for AI
Current projects:
TBD

Designers

Lisa Wong

Project Manager
Graphic Design

Current projects:
UI/UX for Hedra app, statistician playing cards, and Shapes in Capes

Danny Schmidt

Art + Design

Current projects:
2-Min Stats and Statistics Boardwalk: Vincent Price Presents...

Sasha Chirova

Art + Design

Current projects:
Mount Boredoom

Téa Blumer

Art + Design

Current projects:
2-Min Stats and Statistics Boardwalk: Vincent Price Presents...

Louis Bailey

Industrial Design

Current projects:
Giant quincunx and Statistics Boardwalk: Vincent Price Presents...

Kamaria Fyffe

Music + Sound

Current projects:
Music and sound for 2-Min Stats

Alumni

— Lin Dong, PhD, 2019. “” Wells Fargo.
— Isaac J. Michaud, PhD, 2019. “” 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.