Curriculum Vitae

Education

MS/PhD, University of Massachusetts, Amherst, February 2010.

Computer Science (Reinforcement Learning), Advisor Andrew G. Barto

Combined BS/BA, Brown University, 1997.

Computer Science/Russian Language and Literature

National Physical Sciences Consortium Fellowship, 2000-2006. Sandia National Laboratories, Livermore, CA.

Industry

Fiksu, Researcher, Dec 2010-July 2012.

Non-linear regression for data analysis of noisy data with varying formula complexity. Experimental work to determine optimal formula forms for regression. Simple web applications providing access to the results of regression analysis in the form of predictions. Implemented multiple time step planner combining multiple regression models. Automatic data cleaning (application specific heuristics). Some experience with Hive/Hadoop.

Microsoft Corp. Software Design Engineer, Site Server Search Team (1997-1999)

Debugged complex multi-threading issues, maintenance of a SQL data exposure interface.

Teaching and Research

University of Vermont, Lecturer, Fall 2015-present

Courses taught: Reinforcement Learning, Java Programming, Discrete Structures, Complexity and Computability.

Smith College, Visiting Lecturer, 2012-2015

Courses taught: Artificial Intelligence, Theoretical Foundations of Computer Science, Server Scripting for the Web, Interactive Web Documents, How Computers Work, How the Internet Works, Interactive Web Documents

Williams College, Visiting Assistant Professor, Spring 2010.

Instructor for Artificial Intelligence.

UMass Amherst, TA Positions, 2002-2009

Research Methods. Mentored student research projects in a wide variety of topics from Systems to AI, oversaw student design and analysis of experimental projects.

Discrete Math. Filled in for lecturer when away, full lecturing responsibilities for final month of class.

Data Structures, Programming Languages, Discrete Math. Weekly discussion section, office hours, grading.

Database Systems. Grading and student project supervision.

UMass Amherst, RA Positions, 2002-2009

Autonomous Learning Lab, (Summer 2002, 2003 and 2007) Developed algorithms for finding abstract models (models that ignore irrelevant data and construct compact representations) for active, goal oriented agents, using novel applications of spectral graph partitioning, decision trees.

ROLE Educational Software Project, (Summer 2005) Prediction and optimization for educational software.

Knowledge Discovery Lab, (Summer 2004) Research on social networks where individuals may have multiple roles (parent, physician, soccer player). Applied Gibbs sampling to show that discovering labels with a multiple label model in this case is more efficient and more informative than learning using single label models.

Sandia National Laboratories, CA Research Intern, (Summer 2000 & 2001)

Distributed computing.