I am advised by the following unordered pair: {Geoff Gordon, André Platzer}. Currents interests are:

  • complementarity problems
  • convex optimization and analysis
  • planning and MDPs
  • learning theory and machine learning
  • probabilistic inference
I am currently working on methods for incorporating function approximation into solution methods for a broad class of linear complementarity problems. These complementarity problems are strongly connected to the Karush-Kuhn-Tucker conditions for linear and quadratic programs, but are more general. Applications include approximating Markov decision processes and approximating support vector machines. Approximate solution methods include projected-gradient descent, proximal methods, and interior point methods.

I am a member of the Logical Systems Lab and the SELECT Lab. I have also been helping a CMU/JHU APL team out with verifying the FAA's new Airborne Collision Avoidance System (ACAS X), which is based on an MDP.


  • Ph.D. in Computer Science from Carnegie Mellon University (2008 - )
  • M.Sc. in Computer Science from the University of British Columbia; advised by Kevin Leyton-Brown (2007 - 2008)
  • EPIC Intern, IBM Toronto (2004 - 2005)
  • B.Sc. Honours in Computer Science from the University of British Columbia (2001 - 2006)


  • "Nonparametric Scoring Rules." Erik Zawadzki, Sébastien Lahaie. AAAI, 2015. (Paper)
  • "A Formally Verified Hybrid System for the Next-Generation Airborne Collision Avoidance System." Jean-Baptiste Jeannin, Khalil Ghorbal, Yanni Kouskoulas, Ryan Gardner, Aurora Schmidt, Erik Zawadzki, and André Platzer. TACAS, 2015. (Paper)
  • "Hybrid theorem proving of aerospace systems: Applications and challenges." Khalil Ghorbal, Jean-Baptiste Jeannin, Erik Zawadzki, André Platzer, Geoffrey Gordon, and Peter Capell. Journal of Aerospace Information Systems, 2014. (Paper)
  • "A Projection Algorithm for Strictly Monotone Linear Complementarity Problems." Erik Zawadzki, Geoffrey Gordon, André Platzer. NIPS OPT, December 2013. (Paper)
  • "A Generalization of SAT and #SAT for Robust Policy Evaluation." Erik Zawadzki, André Platzer, Geoffrey Gordon. IJCAI, August 2013. (Paper)
  • "Memory-Efficient GroupBy-Aggregate with Compressed Buffer Trees." Hrishikesh Amur, Wolf Richter, David Andersen, Michael Kaminksy, Karsten Schwan, Athula Balachandran, Erik Zawadzki. ACM Symposium on Cloud Computing, October 2013 (Paper)
  • "An Instantiation-Based Theorem Prover for First-Order Programming." Erik Zawadzki, Geoffrey Gordon, André Platzer. AISTATS, April 2011. (Paper)
  • "Search Tree Restructuring." Erik Zawadzki, Tuomas Sandholm. Technical Report, May 2010. (Paper)
  • "Empirically Evaluating Multiagent Learning Algorithms." Erik Zawadzki, Ascher Lipson, Kevin Leyton-Brown. Working Paper, November 2014. (arXiv)
  • "Empirically testing decision making in TAC SCM.", Erik Zawadzki, Kevin Leyton-Brown. AAAI-07 Workshop on Trading Agent Design and Analysis (TADA-07), Vancouver, 2007. (Paper)
  • "Multiagent learning and empirical methods." Erik Zawadzki. Master's Thesis, 2008. (Thesis)



Graduate coursework



  • NSERC PGS M (2007-2008)
  • UBC Undergraduate Scholarship Program (2001-2006)