Hello/你好! I am an Assistant Professor in Statistics at Georgia State University. I am also a faculty member of Brains & Behavior in its Neuroscience Institute and affiliated with the Center for Cosmic Ray Studies.
I was a postdoctoral scholar at McGill University jointly with the University of Waterloo, kindly sponsored by the Canadian Statistical Sciences Institute (CANSSI). I am also affiliated with Mila - Quebec AI Institute and the Health Data Science Lab.
My office is: Room 1407, 25 Park Place.
I currently serve as an associate editor of Statistics and Computing.
My research interests include, but are not limited to:
- Functional data analysis.
- Statistical machine learning and high-dimensional statistical inference.
- Dependence modeling.
- Optimal design of experiments.
- Large language model (LLM) alignment.
- Retrieval-augmented generation (RAG) with uncertainty quantification.
Applications include 💊 drug discovery and development, 🧪 toxicology, 🧠 neuroscience, 🌌 cosmic ray studies, and 🏀 sports.
😸 Inquiries about supervision and collaboration are always welcome!
Interested in studying or doing research at GSU? Explore 🎓 Why GSU, 👩🏫 GSU faculty in statistics and related fields, and 📅 Academic events.
☢️ Reference letter
Please do not contact me unless (1) you get at least an A/95% or (2) I know you well personally. 📧 If so, please use the subject line “Reference Letter Request - Your Full Name” in your email.
Fun things
😈 North America Taiwanese Statistics Map
I created a Taiwanese @ NA researcher map to visualize the locations of Taiwanese researchers in statistics across North America.
😈 UWaterloo Researcher Map
I created a researcher map to visualize the locations of researchers from the Department of Statistics and Actuarial Science at the University of Waterloo.
* indicates students or postdocs.
Preprint
- Patients-like-me: a variational LM--GNN framework for explainable clinical prediction
- AURA: adaptive uncertainty-aware refinement for LLM-as-a-judge auditing
- Quantifying and auditing LLM evaluation via positive--unlabeled learning
- ragR: retrieval-augmented generation and RAG assessment in R
- Single and multi-objective optimal designs for group testing experiments with a focus on screening for an infectious disease
- FTSgof: white noise and goodness-of-fit tests for functional time series in R
- CVXSADes: a stochastic algorithm for constructing optimal exact regression designs with single or multiple objectives
2026
- Severity-controlled prediction sets for medication recommendation
2025
- Positive and unlabeled data: model, estimation, inference, and classification
- Variable selection in multivariate functional linear regression
2023
- Functional spherical autocorrelation: a robust estimate of the autocorrelation of a functional time series
2022
- Evaluating real-time probabilistic forecasts with application to National Basketball Association outcome prediction
2021
- Properties of optimal regression designs under the second-order least squares estimator
Thesis
- Methods in functional data analysis: forecast evaluation, robust serial dependence measures, and a spatial factor copula model —
- Optimal regression design under second-order least squares estimator: theory, algorithm and applications —
* indicates students or postdocs.
Optimal Design of Experiment
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A R package for computing optimal regression designs under the second-order least-squares estimator
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A R package for computing optimal regression designs for group testing experiments
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A R package for computing optimal regression designs with single or multiple objectives through convex optimization
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A MATLAB toolbox to compute optimal regression design
Functional Data Analysis
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A R package for white noise and goodness-of-fit tests for functional time series
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A R package to Evaluating the probabilistic forecasts between competitive forecasters
AI and Machine Learning
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A R package for Retrieval-Augmented Generation and RAG Assessment
Personal
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A R package for knitting some RMarkdown reports and other usages
2026 Fall
Upcoming
2027 Spring (Tentative)
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STAT 8310 Bayesian Data Analysis
PhD Student
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Wenpu is working on cost-effectiveness analysis related problems.
Master Student
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Kalen is working on optimal design problems
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Seoyoung is working on human annotation and retrieval-augmented generation (RAG) problems.
Past Member (3)
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Sierra worked on classification problem on GSU Pitchers in baseball games
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Yi Xing Hu (2026), MS.c. at McGill UniversityYi Xing worked on gene/cell regulation problems using Reinforcement Learning
⚠️ Disclaimer: The views and opinions expressed in these resources are my own and do not represent the official views or positions of any university, institution, or for-profit organization.
Computing
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GSU research computing: a practical guide 2026-09-25Getting started with ARCTIC: access, file storage, and R or Python jobs on GSU's research computing cluster.
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MFCF computing resource shortguide 2025-02-20Demonstrate how to use UW MFCF computing resources, including VPN, server connection, and running R scripts
Conference & Seminar
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Statistics, ML & AI events 2026-09-26Statistics, biostatistics, bioinformatics, ML, and AI conferences and seminars in Atlanta and nearby Georgia, with dates, venues, and official links.
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Past Conference 2026-09-26
Completed statistics, biostatistics, bioinformatics, ML, AI, and related health research events.
View past events →
Georgia State University
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GSU faculty in statistics and related fields 2026-09-26A cross-department directory of researchers in statistics, biostatistics, machine learning, econometrics, measurement, and quantitative neuroscience.
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Misc 2026-09-26A practical directory of GSU research, computing, funding, teaching, and faculty resources, plus career links.
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Why study at GSU? 2026-09-26Statistics at GSU: R1 research, recognized faculty, Atlanta's career and cultural opportunities, and an affordable MS path through teaching assistantships.
Personal
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Job Market reflection 2026-05-08For Tenure-Track Statistics Professorship in North America
Research
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Optimal regression design: an introduction 2026-09-26An illustrated introduction to optimal design for calibration, concentration-response experiments, group testing, and multiple objectives, with models, workflows, and reproducible R examples.
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An illustrated introduction to retrieval-augmented generation, with a practical document example, evaluation metrics, and uncertainty quantification in R.
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Drug discovery: statistics and AI agents 2026-09-25Statistical models, uncertainty, and AI agents for drug discovery, with equations and reproducible illustrations.