# Career

From Lafortune Wiki

Career

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:::'''Prerequisistes:''' MATH 115 | :::'''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. | :::'''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 | + | :::'''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 19:35, 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****Prerequisites:**Senior or Graduate standing**Course Description:**This course was offered in Fall 2007 and Winter 2010.

**EECS 566: Discrete Event Systems****Prerequisites:**Graduate standing or permission of instructor**Course Description:**Modeling, analysis, and control of discrete event systems; untimed (logical) and timed models considered. Defining characteristics of discrete event systems. Logical models: languages, automata, and Petri nets. Analysis: safety, nonblocking, state estimation, and event diagnosis. Supervisory control: controllability, nonblocking and nonconflicting languages, observability, and coobservability. Control of Petri nets using place invariants. Timed models: timed automata and timed Petri nets; timed automata with guards. Brief introduction to stochastic models.