System Optimization & Analysis for Manufacturing
  1. MIT Sloan School of Management, MBA Leaders for Global Operations Core, Summer 2013

    Teaching Assistant for Professor Itai Ashlagi

    Introduction to mathematical modeling, optimization, and simulation, as applied to manufacturing. Specific methods include linear programming, network flow problems, integer and nonlinear programming, discrete-event simulation, heuristics and computer applications for manufacturing processes and systems.

  1. MIT Departments of Economics and EECS, Undergraduate Elective, Spring 2013

    Teaching Assistant for Professors Daron Acemoglu, Munther Dahleh, Asu Ozdaglar

    This course highlights common principles that permeate the functioning of diverse technological, economic and social networks. It both introduces conceptual tools from dynamical systems, random graph models, optimization and game theory, and covers a wide variety of applications including: learning and informational cascades; economic and financial networks; social influence networks; formation of social groups; communication networks and the Internet; consensus and gossiping; spread and control of epidemics; and control and use of energy networks.

Mathematics for Computer Science
  1. MIT Departments of EECS and Mathematics, Undergraduate Elective, Fall 2008

    Teaching Assistant for Professor Tom Leighton

    This course covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics are covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions.