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Graduate-level Courses

Graduate-level Courses

Estimation Theory

Last Year's Syllabus

A core course on the problem of parameter estimation. Topics that are covered include minimum variance unbiased estimation, the Cramér–Rao bound and maximum likelihood estimation; linear models, linear regression, least squares; regularization, LASSO; Stein's paradox, James–Stein estimators, Hodges–Le Cam's estimators; sufficient statistics; isotonic regression; Bayesian estimation: MMSE and MAP estimation; conjugate and Jeffreys' priors.

Learning to Control

Syllabus

​An advanced course. After a short recap on modern linear control, state-of-the-art learning techniques are presented for the problem of system identification and adaptive control.

Information Theory 2

Syllabus

An advanced course that introduces advanced topics and techniques in information theory: multi-user information theory, large deviations and its applications to communications, lattice-based techniques, and more. 

Control Under Communication Constraints

Syllabus

An advanced course that considers the control problem in the presence of noisy communication links in the feedback loop. The course explains different aspects and techniques to tackling different control–communication scenario.

learning2control

Teaching

Undergraduate-level Courses

Random Signals & Noise

Syllabus

A basic course on stochastic processes that covers basic probability, random vectors, Gaussian vectors, estimation, basic stochastic processes, stationarity, ergodicity, power spectral density, (non-causal) Wiener filtering, Markov chains, Lévy processes, Poisson processes, Wiener processes, Kalman filtering (time permitting).

Introduction to Control Theory

Syllabus

A basic course in control theory that covers

  • Classical control techniques: steady-state error, PID & PR controllers, lead–lag compensators, Routh–Hurwitz criterion, root locus, Nyquist criterion, sensitivity, phase & gain margins.

  • State-space representation: State-space realizations, minimality of a system, controllability, stabilizability, observability, detectability, Kalman & PBH tests, observers & observer-based control.

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