Bio

Jason Xiaotian Dou is a postdoc research fellow at Harvard University working on artificial intelligence and medicine.  He did his Ph.D. in Computer Engineering at the University of Pittsburgh/University of Pittsburgh Medical Center (UPMC). His Ph.D. dissertation is titled “Learning Effective Representation Efficiently: Models, Applications, and Metrics.” Previously He did B.S. in Computer Science from Peking University with an undergraduate thesis at Carnegie Mellon University on “A Markov Chain Approach to the Gerrymandering Problem.” He also did master study in Information Science at Cornell University. His research is in machine learning, specifically representation learning with various applications in computer vision, natural language processing, single-cell biology, mobile sensing, and healthcare. His works have appeared in AI and machine learning conferences such as AAAI, Neurips, ICML, ML4H, and ICIBM and journals like Clinical Cancer Research. His work on Internet Finance Index has been featured in news media such as Tencent, Sina, and Caixin. For more about his works please go to his website jasondou.org.

Research Interests

• Machine Learning
• Representation Learning
• Artificial Intelligence