Xiao Shou

Assistant Professor
Department of Computer Science
School of Engineering and Computer Science
Baylor University
One Bear Place #97141, Waco, Texas 76798, United States

Email: xiao_shou [at] baylor [dot] edu

News []

[08/2026] Zhengshi joined my team!
[07/2026] Received NSF STTR Phase I award with Photopica for cool AI + Photonics project!
[02/2026] Received Baylor Data Science Hub - Data Hub Affiliate Program Award for cool TPP + Cybersecurity research!
[01/2026] Received Baylor ONE-URC award with Dr. Jonathan Hu for cool AI + Photonics research!
[01/2026] Rofiq joined my team!
[08/2025] Paper Accepted at EMNLP 25.
[08/2025] Xinyi joined my team!
[05/2025] Josh joined my team!
[02/2025] Paper Accepted DASFAA 2025.
[01/2025] I volunteered as a Judge at First Tech Challenge Robotics Competition in Waco TX!
[12/2024] I will serve as a reviewer for ICML 2025.
[12/2024] Paper Accepted AAAI 2025.
[11/2024] Paper Accepted at NeurIPS Workshop 2024.
[09/2024] I will serve as a reviewer for AISTATS 2025.
[08/2024] I will serve as a reviewer for ICLR 2025.
[08/2024] I will serve as a PC member for AAAI 2025.

Biography

I am an Assistant Professor in the Department of Computer Science at Baylor University. Prior to joining Baylor, I was a visiting scholar hosted by Jianxi Gao in the CS department at RPI. I obtained a PhD in Applied Math from Department of Mathematical Sciences, Rensselaer Polytechnic Institute in August 2023, working under the supervision of Kristin Bennett. I have published many paper in top ML conferences, including NeurIPS, AAAI, ICML, CLeaR etc. I have served as a PC member for several international conferences, such as NeurIPS, AAAI, ICML, ICLR, AISTATS etc.

Education

Ph.D. (Applied Mathematics), RPI, 2023.
M.S. (Computer Science), RPI, 2023.
M.S. (Chemistry), Ohio State University, 2014.
B.A. (Chemistry), (minor in applied math, east asian studies and Japanese), Wittenberg University, 2012.

Research

I am generally interested in machine/deep learning, and trustworthy (dynamics of) AI, with a primary focus on

(Neural) Marked Temporal Point Process & Sequential Data;
Causal Inference & Learning;
(Deep) Generative Models;
Neural Network Training and Dynamics;
Applications in Engineering, Cyber and Health: 1. AI for Photonics 2. Malware Classification and Unpacking 3. Dementia Early Detection and Intervention Via Speech Data.

Awards & Honors

IBM Research Accomplishment Award 2023 for Graphical Event Models, IBM, 2023.
RPI-IBM AIRC Fellowship, RPI and IBM, 2020-2023
Schmidt Science Fellowship Nomination, RPI
Best Student Paper Award, ACM BCB, 2021