Collaborative Machine Learning for Healthcare
My research focuses on collaborative machine learning in healthcare, aiming to develop privacy-preserving and equitable models that address critical healthcare challenges. I will introduce a series of innovative collaborative machine learning frameworks based on federated learning, with special emphasis on tackling local heterogeneity and constructing multimodal medical foundation models at the server level. These models are designed to protect patient privacy while delivering mutual benefits to all stakeholders. Moreover, the algorithms I develop have broad applicability across other fields, such as IoT, finance, and bioinformatics.
Jiaqi Wang is a final-year Ph.D. candidate in the College of Information Sciences and Technology at The Pennsylvania State University. His research focuses on collaborative machine learning, healthcare informatics, and multimodal foundation model distributed learning. He earned his B.E. from Zhejiang University and his M.S. from the University of Georgia.