Ziyi Huang

Ziyi Huang is a machine learning researcher at Bell Labs and an Adjunct Professor in the Biomedical Engineering department at Stevens Institute of Technology. They hold a doctoral degree and completed postdoctoral training at Columbia University under Professor Christine Hendon. Their research focuses on developing trustworthy AI systems for healthcare, machine learning theory, and decision-making under data imperfections.

Education: Ph.D. and postdoctoral studies in Electrical Engineering at Columbia University, advised by Prof. Christine Hendon.

Research Interests: Huang’s work emphasizes robust, reliable AI for healthcare applications, including proactive medical dialogue systems, medical image analysis, and uncertainty quantification in deep learning. They also explore methods to handle noisy or incomplete data in real-world scenarios.

Grant Contributions: Served as Site-PI for NIH R21 and R01 grant submissions, securing over $283K in doctoral fellowships/grants. Awards include the Machine Learning and Systems Rising Star fellowship.

Collaboration Opportunities: Actively seeks research partnerships to advance AI-driven healthcare solutions.