# Career

Career
 Revision as of 19:08, October 18, 2014 (view source)Stephane (Talk | contribs) (→Professional Career)← Older edit Revision as of 19:33, September 4, 2015 (view source)Stephane (Talk | contribs) (→Professional Career)Newer edit → Line 42: Line 42: '''Courses Recently Taught''' '''Courses Recently Taught''' − ::'''EECS 216: Introduction to Signal and Systems''' + ::'''EECS 203: Discrete Mathematics''' − :::'''Prerequisistes:''' EECS 215; Preceded or accompanied by MATH 216 + :::'''Prerequisistes:''' MATH 115 + :::'''Course Description:''' Introduction to the mathematical foundations of computer science. Topics covered include: propositional and predicate logic, set theory, function and relations, growth of functions and asymptotic notation, introduction to algorithms, elementary combinatorics and graph theory and discrete probability theory. + :::'''EECS 216: Introduction to Signals and Systems''' + ::'''Prerequisistes:''' EECS 215; Preceded or accompanied by MATH 216 :::'''Course Description:''' Theory and practice of signals and systems engineering in continuous and discrete time. Continuous-time linear time-invariant systems, impulse response, convolution. Fourier series, Fourier transforms, spectrum, frequency response and filtering. Sampling leading to basic digital signal processing using the discrete-time Fourier and the discrete Fourier transform. Laplace transforms, transfer functions, poles and zeros, stability. Applications of Laplace transform theory to RLC circuit analysis. Introduction to communications, control, and signal processing. Weekly recitations and hardware/Matlab software laboratories. :::'''Course Description:''' Theory and practice of signals and systems engineering in continuous and discrete time. Continuous-time linear time-invariant systems, impulse response, convolution. Fourier series, Fourier transforms, spectrum, frequency response and filtering. Sampling leading to basic digital signal processing using the discrete-time Fourier and the discrete Fourier transform. Laplace transforms, transfer functions, poles and zeros, stability. Applications of Laplace transform theory to RLC circuit analysis. Introduction to communications, control, and signal processing. Weekly recitations and hardware/Matlab software laboratories. ::'''EECS 498: Special Topics: Introduction to Discrete-Event and Hybrid Systems''' ::'''EECS 498: Special Topics: Introduction to Discrete-Event and Hybrid Systems'''

## Revision as of 19:33, September 4, 2015

Stéphane Lafortune | Contact Information | Career | Research | Publications | Related Links

## Education

École Polytechnique de Montréal

B.S. Electrical Engineering 1980

McGill University

M.S. Electrical Engineering 1982

University of California at Berkeley

Ph.D. Electrical Engineering 1986

## Professional Career

University of Michigan, Ann Arbor

Professor in the Department of Electrical Engineering and Computer Science since 1986

Visiting Positions

Visiting Professor at Northwestern University (2010-2011), the University of Cagliari (2007 and 2011), the University of Bologna (2004), and École Polytechnique de Montréal (1993).

Elected Fellow of the IEEE (1999)

For "Contributions to the theory of discrete event systems"

Axelby Outstanding Paper Award from the IEEE Control Systems Society

1994 - Limited Lookahead Policies in Supervisory Control of Discrete Event Systems
Co-authors: Sheng-Luen Chung and Feng Lin
2001 - Decentralized Supervisor Control with Communicating Controllers
Co-author: George Barrett

Editor-in-Chief

Journal of Discrete Event Dynamic Systems: Theory and Applications (effective 1/1/2015)

Co-author to the textbook Introduction to Discrete Event Systems

Courses Recently Taught

EECS 203: Discrete Mathematics
Prerequisistes: MATH 115
Course Description: Introduction to the mathematical foundations of computer science. Topics covered include: propositional and predicate logic, set theory, function and relations, growth of functions and asymptotic notation, introduction to algorithms, elementary combinatorics and graph theory and discrete probability theory.
EECS 216: Introduction to Signals and Systems
Prerequisistes: EECS 215; Preceded or accompanied by MATH 216
Course Description: Theory and practice of signals and systems engineering in continuous and discrete time. Continuous-time linear time-invariant systems, impulse response, convolution. Fourier series, Fourier transforms, spectrum, frequency response and filtering. Sampling leading to basic digital signal processing using the discrete-time Fourier and the discrete Fourier transform. Laplace transforms, transfer functions, poles and zeros, stability. Applications of Laplace transform theory to RLC circuit analysis. Introduction to communications, control, and signal processing. Weekly recitations and hardware/Matlab software laboratories.
EECS 498: Special Topics: Introduction to Discrete-Event and Hybrid Systems