Graduate probability

• MATH 275A, 275B, 275C -- our main graduate probability sequence. Typically, part A is devoted to the axiomatic formulation of probability theory, independence, convergence of random variables, laws of large numbers, central limit theorem. In part B, important classes of discrete time stochastic processes are introduced: Markov chains, random walks, stationary sequences and martingales. Finally, part C deals with Brownian motion and continuous time Markov processes.
• MATH 275D -- graduate course on Stochastic Calculus (offered occasionally).
• MATH 275E -- a topical graduate course on Stochastic Particle Systems or Percolation (offered occasionally).
• MATH 285K -- a topical course devoted to various subjects of interest. Previous topics taught:
  • The Random Conductance Model (Winter 2011)
  • Stochastic Processes in Evolution and Genetics (Spring 2010)
  • Introduction to Mathematical Finance (Fall 2008)
  • Mean-Field Models of Spin Glasses (Spring 2006)
  • Statistical Mechanics of the Ising Model (Winter 2005)
  • Random Walk in Random Environment
• MATH 290K -- current-literature seminar. Students give two-hour presentations on recent papers under the supervision of the faculty. In the past, we've had 290's on
  • Path Properties of Brownian Motion
  • Domino Tilings

Undergraduate probability

• Math 3C -- a basic probability course for life sciences students. Covers elementary probability, probability distributions, random variables, and limit theorems.
• MATH 170A, 170B -- undergraduate probability. Covers basic concepts of discrete and continuous probability culminating with (simplified) versions of the basic limit laws.
• MATH 171 -- undergraduate course on (discrete-time) stochastic processes building upon the 170A course.