About Kun Yang
Dr. Kun Yang is a Research Associate Professor at the O’Donnell Data Science and Research Computing Institute (ODSRCI) at ÃÛÌÒ½´Methodist University (SMU). Prior to joining SMU, Dr. Yang was an Associate Research Scholar in the Department of Operations Research and Financial Engineering (ORFE) at Princeton University from 2021 to 2024, where he focused on federated learning and clustering. Before that, he was a Postdoctoral Research Scientist in the Department of Statistics at Columbia University from 2019 to 2021, concentrating on anomaly detection using machine learning in the Internet of Things.
Dr. Yang earned his Ph.D. in Computer Science from the University of Chinese Academy of Sciences (Chinese Academy of Sciences, Institute of Information Engineering) in Beijing, China. His doctoral research, conducted from 2012 to 2018, centered on cybersecurity with machine learning.
Dr. Yang's research interests primarily lie in machine learning and federated learning. He is dedicated to advancing efficient, robust, and safe machine learning frameworks to address complex real-world challenges, including cybersecurity, natural language processing (NLP), and healthcare.