Machine Learning and Deep Learning (Senior Under level)
(Instructor, Department of Computer Science, University of Virginia)

Generative AI - Overview (Master + Senior Under level - Seminar)
(Instructor, Department of Computer Science, University of Virginia)

Generative AI - Risks and Benefits (Graduate Advanced level - Seminar)
(Instructor, Department of Computer Science, University of Virginia)

Machine Learning Foundation, Deep Learning, and Good Uses (Undergraduate Advanced level)
(Instructor, Department of Computer Science, University of Virginia)

Machine Learning Foundation, Deep Learning, and Good Use on COVID19 (Undergraduate Advanced level)
(Instructor, Department of Computer Science, University of Virginia)

Machine Learning (Master level)
(Instructor, Department of Computer Science, University of Virginia)

Deep Learning Advances Graphs (PhD Student level)
(Instructor, Department of Computer Science, University of Virginia)
(Course materials will be added into my Notes2LearnDeepLearning to help students learn state-of-the-art topics in deep learning.)

Machine Learning (Undergraduate level)
(Instructor, Department of Computer Science, University of Virginia)

Machine Learning (Undergraduate level)
(Instructor, Department of Computer Science, University of Virginia)

Advanced Deep Learning (PhD Student level)
(Instructor, Department of Computer Science, University of Virginia)
(Now we expand the course materials into my Notes2LearnDeepLearning to help students learn state-of-the-art topics in deep learning.)
(This list was started from the ~90 papers I chose from NIPS16+ICLR17+ICML17)

Machine Learning (Master+ AdvancedSenior level)
(Instructor, Department of Computer Science, University of Virginia)

Machine Learning (Master level)
(Instructor, Department of Computer Science, University of Virginia)

Special Topic: Large-Scale Machine Learning (PhD Student level)
(Instructor, Department of Computer Science, University of Virginia)
(Later I converted the materials into my Notes2LearnLearning): a list of tutorials to help students learn advanced topics in machine learning.)

Introduction to Machine Learning and Data Mining (Undergraduate+Master level)
(Instructor, Department of Computer Science, University of Virginia)

Special Topic: Machine Learning and Data Mining in Practice for Biomedicine (PhD Student level)
(This course covers 6 different topics about connecting machine learning and "big data" in biomedicine".)
(Instructor, Department of Computer Science, University of Virginia)

Special Topic: Machine Learning (PhD Student level)
(This course covered the book: The Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani and Jerome Friedman).
(Instructor, Department of Computer Science, University of Virginia)

Machine Learning (Undergraduate+Master level)
(Teaching Assistant, School of Computer Science, Carnegie Mellon University)

Machine Learning (PhD Student level)
(Teaching Assistant, School of Computer Science, Carnegie Mellon University)

I am an associate professor of computer science without term (tenured in 2019) at the University of Virginia.

I am an Amazon Scholar at Bedrock Science, Amazon Web Services (AWS).

I was a Senior Manager (starting as Principal Applied Scientist first) at Bedrock Science, Amazon Web Services (AWS).

I was part of the Data and Technology Advancement (DATA) National Service Scholar Program: Data Scientists Advancing Biomedical Research in National Institute of Health, NIA.

I took a Sabbatical in University of California, Berkeley, Visiting Prof. Bin Yu's group.

I was an assistant professor at the Department of Computer Science , in University of Virginia. I have received the Young Investigator CAREER award from NSF (National Science Foundation, 2015-2020)!

I was a senior researcher @ Machine Learning Department, NEC Labs America.

I was a research staff member @ Machine Learning Department, NEC Labs America.
( I was very fortunate to have the chance to work closely with Jason Weston , Ronan Collobert , Leon Bottou, Vladimir Vapnik, Koray Kavukcuoglu and many great colleagues.)

I completed my PhD in May of 2008 at the School of Computer Science in Carnegie Mellon University working with Ziv Bar-Joseph and Judith Klein-Seetharaman.
(Dissertation Committee: Ziv Bar-Joseph, Judith Klein-Seetharaman, Christos Faloutsos, Jaime Carbonell, Baldo Oliva)

I received my M.S. in May of 2003 from the School of Computer Science in Carnegie Mellon University.

I received my B.S. with first-class high honors (3 out of 156 graduates) and M.E. (in the accelerated program) in June of 2001 from Computer Science Department, Tsinghua university, Beijing.

I was a member of Tsinghua Univ. Chorus team and a member of Tsinghua Univ. Skating Team between 1999-2001.