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Our current Machine Learning research mainly focuses on fundamental problems in adversarial/OOD generalizability, fairness, explainability, security and privacy of the predictive models.
Introduction
Introduction
Trustworthy AI Lab
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.
WSU CS 2023 Awards!
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.
MICCAI-23 paper acceptance!
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)
NIH R33 Grant Funded!
NIH R33 Grant Funded!
Congratulations to Dongxiao Zhu to leverage AI for predict MIS-C severity (R33HD105610) funded by NIH!
IJCAI-23 paper acceptance!
IJCAI-23 paper acceptance!
Congratulations Xin Li for paper accepted by IJCAI-23.
NIH R61 Grant Funded!
NIH R61 Grant Funded!
Congratulations to Dongxiao Zhu to leverage AI for predict MIS-C severity (R61HD105610) funded by NIH!
AAAI-21 paper acceptance!
AAAI-21 paper acceptance!
Congratulations to Xin Li for paper accepted by AAAI-21.
Will artificial intelligence be your next ER doctor?
Will artificial intelligence be your next ER doctor?
On Feb, 2019, Prof. Zhu comments on Scientific American on AI assisted diagnosis. (more...)
MIDL-20 paper acceptance!
MIDL-20 paper acceptance!
Congratulations to Xin Li for paper accepted by Medical Imaging with Deep Learning (MIDL-20).
Contact
Contact
Address：5057 Woodward Ave. Suite 14101.3, Detroit, MI 48202
Phone: (313) 577-3104
E-mail: ct4442@wayne.edu
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