Research Scientist in Dept of Neuroscience, Yale School of Medicine
Lecturer in Dept of Computer Science, Yale SEAS
My long-term career goal is to leverage artificial intelligence to advance neuroscience research. I have a solid background in ML/AI and over 10 years of experience across both academia and industry. In my doctoral research, I spearheaded a multi-lab project analyzing brain-wide activity in larval zebrafish (Chen et al., 2018). As Data Science lead at a biotech startup, I developed automated pipelines for precision cell manufacturing. At Amazon Alexa AI, I enhanced device and cloud-based deep learning models for Alexa Guard, implemented across Echo devices and Astro robots. I collaborated with engineering teams to refine science infrastructure and automation workflows, and led science initiatives for production features with cross-functional team coordination. I have also performed Machine Learning research in acoustic event detection and filed US patents on my work at Amazon.
Meanwhile, I embraced the opportunity to share my knowledge and experiences through teaching. I have taught graduate-level classes on AI and data vizualization at Northeastern University as a part-time lecturer. With my recent transition to Yale, I teach courses on AI applications with the Computer Science Department both at the graduate and undergraduate level, and perform computational genomics research in the Neuroscience Department.
Spring 2024 | CPSC 776: Topics in Industrial AI Applications | Graduate Seminar | link
Fall 2024 | CPSC 171: Introduction to AI Applications | New Course, coming soon!
Ph.D. in Biology (systems and computational neuroscience), Harvard University
B.Sc. in Biochemistry, Hong Kong University of Science & Technology