معرفی
Lacra Pavel is a Professor in the Edward S. Rogers Sr. Department of Electrical and Computer Engineering at the University of Toronto, Faculty of Applied Science and Engineering. She joined the department in August 2002 after industry experience at Nortel Networks and Solinet Systems, and remains active in the System Control Group and Photonics Group.
Her educational background includes:
- Diploma of Engineering (with distinction) in Automatic Control, Technical University Gh. Asachi of Iasi, Romania (1989)
- PhD in Electrical and Computer Engineering, Queen's University at Kingston (1996)
Research focuses on integrating game theory, control theory, and optimization within networked systems. She pioneered applications in noncooperative/evolutionary game theory for network control, nonlinear/robust control frameworks, and energy-efficient optical/transportation networks. Current work develops mathematical foundations for learning in games via control-theoretic approaches to enable autonomous multi-agent network optimization.
Recent publications (2019-2013) reveal dominant trends: distributed Nash equilibrium seeking using passivity-based and operator-splitting methods, stability analysis for optical network power control with time-delays, and extensions to transportation systems like railway timetabling. Key subfields include graphical games, ADMM algorithms, and Lyapunov-based boundary control for distributed parameter systems.
Scientific recognition includes:
- Fellow of the IEEE (2025) for contributions to game theory, control, and optimization for network systems
- Connaught New Staff Award, University of Toronto (2003)
- New Opportunities Infrastructure Award, CFI/OIT (2003)
- Award for Innovation, Solinet Systems (2001, 2002)
- Inventor Recognition Award, Nortel Networks (2000)
She has advised over 20 graduate students including current PhD candidates and former students now at MIT, Princeton, Amazon, and Ciena. Major grants include the CFI/OIT New Opportunities Infrastructure Award (2003). Her research bridges theoretical game control with practical implementations in optical and transportation networks.
As co-director of the System Control Group and member of the Photonics Group, she leads teams developing algorithms for autonomous network optimization. Current projects focus on stochastic approximation methods for multi-agent learning and energy-efficient network design.
