Teaching Experience
- Co-Instructor: Probabilistic Graphical Models (10-708), Spring 2012, Spring 2013.
Machine Learning Department, Carnegie Mellon University, Instructor: Eric P. Xing.
Spring 2012: [slides I] [slides II] [slides III] on variational inference
Spring 2013: [slides] on variational principle, [slides] on sparse nonparametric regression
- Teaching Assistant: Advanced Topics in Statistical Learning Theory (STAT 241B), Spring 09.
Department of Statistics, UC Berkeley, Instructor: Martin J. Wainwright.
- Guest Lecturer: Practical Machine Learning (CS 294), Fall 2006.
Department of EECS, UC Berkeley, Instructor: Michael I. Jordan.
[reading materials] and [slides] on clustering
- Teaching Assistant: Efficient Algorithms and Intractable Problems (CS 170), Spring 2006.
Department of EECS, UC Berkeley, Instructor: Alistair Sinclair.
- Teaching Assistant: Efficient Algorithms and Intractable Problems (CS 170), Fall 2005.
Department of EECS, UC Berkeley, Instructor: Michael I. Jordan.
- Teaching Assistant: The Elements of Statistical Learning II, Summer
2004.
Max-Planck-Institut für Informatik, Instructor: Jörg Rahnenführer.
Graduate Courses
- Graphical Models, Advanced Topics in Statistical Learning Theory, Theoretical Statistics
- Topology and Analysis, Probability Theory, Convex Optimization, Population Genetics
- Randomness and Computation, Markov Chain Monte Carlo, Advanced Computer Systems
