Teaching

Year Title and Information
2022 Spring

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

2020 Fall

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

2019 Fall

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

2019 Spring

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.)

2018 Fall

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

2018 Spring

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

2017 Fall

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)

2016 Fall

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

2015 Fall

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

2015 Spring

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.)

2014 Fall

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

2014 Spring

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)

2013 Fall

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)

2006 fall

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

2004 fall

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

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"Success is not final, failure is not fatal: it is the courage to continue that counts." --- Winston Churchill