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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