Shirshendu Chatterjee

Teaching at CIMS, NYU

Calculus 11, Fall 2011.

Calculus 11, Fall 2012.

Calculus 11, Fall 2013.

Teaching at Cornell University


ORIE 3510/5510: Summer 2009 and Summer 2010.

  • Course: Introduction to Stochastic processes
  • Instructor: Shirshendu Chatterjee
  • Verbal Description: This course introduces the concept of stochastic process to the undergraduate and M.Eng students, and gives an overview of the basic techniques used to analyze several standard models. I covered discrete time Markov chain, Poisson process, continuous time Markov chain, branching process, renewal theory including regenerative process, some queuing theory and a brief introduction to Brownian motion.

Teaching Assistantship

  1. ORIE 6320: Spring 2010

    • Course: Nonlinear programming
    • Instructor: Michael Todd
    • Verbal Description: This course is connected with the theory and algorithms for nonlinear programming, and it covers optimality criterions, convexity and duality, and algorithms for unconstrained, and linearly and nonlinearly constrained optimizations.
  2. ORIE 3500/5500: Fall 2008

    • Course: Engineering probability and statistics II
    • Instructor: Stefan Weber
    • Verbal Description: A rigorous formulation in theory combined with the methods for modeling analyzing and controlling randomness in engineering problems. Specific topics include random variables, probability distributions, density functions, expectation and variance, random vector, important distributions including normal, Poisson, exponential, hypothesis testing, confidence intervals, and point estimates using maximum likelihood and method of moments.
  3. ORIE 360/560: Fall 2007

    • Course: Engineering probability and statistics II
    • Instructor: Sam Ehrlichman
    • Verbal Description: Topics include probability space, combinatorial probability, random variables and distributions, random vectors and independence of random variables, expectation, variance, correlation and higher moments and moment generating functions, standard inequalities and limit theorems, transformation of random variables, conditional expectations, multivariate normal distribution, sampling statistics, point and interval estimates.
  4. ORIE 270: Summer 2007

    • Course: Basic engineering probability and statistics
    • Instructor: Nikolay Bliznyuk
    • Verbal Description: This course introduces Statistics and Probability to the engineering undergraduate students and gives an overview of the basic techniques used in statistical analysis. It starts with the notion of survey, data collection, descriptive statistics and then introduces the concept of probability models. In Probability the course covers discrete and continuous random variables, their distributions, mean and variance, central limit theorem and linear combination of random variables and Normal approximation to binomial and Poisson. In Statistics it covers Point and interval estimation, hypothesis testing, two-sample t-test, paired t-test, introduction to linear regression, inference in regression analysis, regression diagnostics, multiple regression and ANOVA.