2026 Oklahoma Conference for Statistics, Biostatistics and Data Science

The 2026 Oklahoma Conference for Statistics, Biostatistics and Data Science is coming soon!

Location: Hudson College of Public Health Building, Room 150 (801 NE 13th Street, Oklahoma City, OK 73104)

Conference Date: October 26-27, 2026

Contact Person(s): Chao Xu chao-xu@ouhsc.edu

Registration Deadline: October 20, 2026

Registration Cost:

Abstracts

We are accepting abstracts in advance of this year's conference!

Abstract poster submission deadline is Friday, October 16, 2026.

Two student poster winners will receive a prize of $200 each!

Abstract Submission Link: https://qualtrics.ou.edu/jfe/form/SV_06yiu57JLMK5jme

Day 1 (Oct 26)

Time	Session	Speaker
Morning: Scientific Talks
8:30-9:00	Registration, Coffee & Networking
9:00-9:15	Welcome & Opening Remarks	Dr. Sixia Chen – University of Oklahoma Health Campus
9:15-10:00	Understanding the Benefits of AI-Generated Data in Semi-Supervised Learning	Dr. Jiwei Zhao — University of Wisconsin-Madison
10:00-10:45	Toward Efficient Machine Learning: Statistical Theory and Randomized Algorithms	Dr. Chao Lan — University of Oklahoma
10:45-11:00	Coffee Break
11:00-11:45	From Biological Priors to Interpretable Concepts: Knowledge-Guided Graph Neural Networks for Brain Disorder Prediction	Dr. Aiying Zhang — University of Virginia
11:45-12:00	Discussion/Transition
12:00-1:15	Lunch

Afternoon: Scientific Talks + Posters
1:15-2:00	Bregman Projection for Calibration Estimation and Data Integration	Dr. Jae Kwang Kim — Iowa State University
2:00-2:45	On the Adaptivity and Scalability of Kernel Methods for Testing and Prediction	Dr. Pingshou Zhong — University of Illinois at Chicago
2:45-3:00	Coffee Break
3:00-3:45	Bayesian Methods to Improve the Design and Analysis of Feasibility Studies	Dr. Robert Montgomery — University of Kansas Medical Center
3:00-4:30	Poster Presentation Session
End of Day 1

Day 2 (Oct 27)

Time	Session	Speakers
Morning: Scientific Talks
8:30-9:00	Coffee & Networking
9:00-9:45	Design-Assisted Regression	Dr. Ye Liang — Oklahoma State University
9:45–10:30	Regression Analysis of Bivariate Survival Data Using Pseudo-Observations	Dr. Steven Chiou — Southern Methodist University
10:30–10:45	Coffee Break
10:45–11:30	Beyond FRAX: Evaluating Genomics and Machine Learning for Trustworthy Fracture Risk Prediction	Dr. Qing Wu — Ohio State University
11:30–12:00	Closing Remarks / Discussion / Transition
12:00–1:15	Lunch

Afternoon: Career + Posters
1:15-2:15	Career Panel / Forum	Dr. Lance Ford - Senior Consultant at The Lewin Group (Optum / UHG); Dr. Justin Dvorak; Zachary Barrett, MS - Co-Founder; Prokopton Technologies; Dr. Gledius Kola - Data scientist at University Hospitals
2:15-2:30	Coffee Break
2:30-4:00	Poster Presentation Session
End of Day 2