Summary
Kai Zhang is a postdoctoral researcher specializing in multi-modal and federated learning for biomedicine, currently advancing AI for medical image analysis at Stanford. With eight years of experience spanning internships at Oracle Health AI, NEC Labs, Amazon, Mayo Clinic, and Samsung Research, he bridges trustworthy medical AI research with practical system design for clinical deployment. His work emphasizes accelerating discovery-to-delivery pipelines—combining federated learning, foundation models, and efficient ML systems—to tackle privacy-sensitive healthcare problems. Notably, his Amazon internship produced an oral paper at AMLC on practical federated learning for fraud detection, reflecting a mix of rigorous research and production-minded experimentation. Based in Bethlehem, PA, he emerged from Lehigh’s PhD program with a focus on building dependable, multimodal agents and reinforcement-learning approaches tailored to healthcare contexts.
8 years of coding experience
PhD Student, Computer Science, PhD Student, Computer Science at Lehigh University
chinses, English