Trustworthy AI Lab

Research Area

Publications

AI conference submission checklist

Our current Machine Learning research mainly focuses on fundamental problems in adversarial/OOD generalizability, fairness, explainability, security and privacy of the predictive models.

Introduction

Trustworthy AI Lab

We conduct original research in developing trustworthy machine learning models, algorithms and systems to leverage the emerging big data in medical imaging, natural language processing, cybersecurity, healthcare, multi-modal sensor, GIS, and social media to realize AI's full potential to benefit humanity and society.

Our current use-inspired research include smart and connected health, mobile and tiny machine learning, recommender system, medical imaging, spatiotemporal modeling, and stylometry based user-authentication.

NIH Grant Funded!

Aug 2025: VisionWay: Accessibility-aware Path Selection for Wayfinding has been funded by the National Institutes of Health (NIH). This project advances accessibility-aware AI for path selection and wayfinding.

NSF Grant Funded!

Aug 2025: Advancing Large Language Model Unlearning: Foundations and Applications has been funded by the National Science Foundation (NSF). This foundational AI research explores new methods for LLM unlearning and applications.

ECAI-25 Papers Accepted!

Congratulations to students Rafi Ibn Sultan and Saleh Zare Zade on having two papers accepted at the European Conference on Artificial Intelligence (ECAI-25).

Large Federal Grant Awarded!

$5M HRSA Geriatrics Workforce Enhancement Program project (Sept 2024).

JMIR AI Paper Accepted!

Congratulations to Mohammad Amin Roshani for his first-authored paper “Generative LLM–Powered Conversational AI App for Personalized Risk Assessment: Case Study in COVID-19” accepted by JMIR AI.

WACV Papers Accepted!

Two papers accepted by WACV 2025, first authored by Chengyin Li.

WSU CS 2023 Awards!

We proudly congratulate Yao Qiang on receiving the 2023 Michael E. Conard Award and Chengyin Li for securing the Best Graduate Research Assistant of 2023 title, highlighting their exceptional contributions to their fields.

Images

MICCAI-23 paper acceptance!

Congratulations to Chengyin Li: 'FocalUNETR: A Focal Transformer for Boundary-aware Prostate Segmentation using CT Images' Accepted by the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI-23)