Colin Jones

EPFL STI IGM LA3
ME C2 408 (Bâtiment ME)
Station 9
1015 Lausanne

Colin Jones is an associate professor in the field of optimal control, with a focus on optimization and model predictive control. He received his bachelor's and master's degrees in electrical engineering and mathematics from the University of British Columbia and later earned his Ph.D. from the University of Cambridge, where he conducted research on polyhedral computational methods for constrained control. Prof Jones has been an associate professor at the école Polytechnique Fédérale de Lausanne since 2017, and has previously held positions as an assistant professor at the EPFL and a senior researcher at the ETH Zürich. In addition to his research, Colin is the director of the Robotics control and intelligent systems doctoral program at the EPFL. He has published over 200 papers and has been recognized for his work on optimal control of building networks with an ERC starting grant. Colin's current research interests include high-speed predictive control and optimization, as well as the control of green energy generation, distribution, and management.

Publications


All publications are available on the EPFL infoscience portal here and on google scholar here.

Education

BASc

| Electrical engineering and mathematics

1994 – 2000 University of British Columbia

MASc

| Electrical engineering

2000 – 2002 University of British Columbia, Canada

PhD

| Control theory

2002 – 2005 Cambridge, UK
Directed by Jan Maciejowski

Research Interests

My research focuses on the development of the theory and practice of optimization-based, or model predictive control with a particular emphasis on problems arising from renewable energy challenges.
Details of ongoing research can be found at la.epfl.ch

Infoscience

Infoscience

Teaching & PhD

PhD Students

Tudor Andrei Oancea, Pietro Mello Rella, Wenbin Wang, Jicheng Shi, Johannes Waibel, Fenglong Song, Shaohui Yang, Andrea Gattiglio, Yan Zhang

Past EPFL PhD Students

Andrea Alessandretti, Ye Pu, Jean-Hubert Hours, Milan Korda, Tomasz Tadeusz Gorecki, Faran Ahmed Qureshi, Georgios Stathopoulos, Francisco Fernandes Castro Rego, Altug Bitlislioglu, Ivan Pejcic, Sanket Sanjay Diwale, Luca Fabietti, Harsh Ambarishkumar Shukla, Petr Listov, Yingzhao Lian, Emilio Maddalena, Loris Di Natale, Paul Scharnhorst, Manuel Pascal Koch, Wenjie Xu, Roland Schwan

Courses

Control systems + TP

ME-321

Provides the students with basic notions and tools for the analysis and control of dynamic systems. Shows them how to design controllers and analyze the performance of controlled systems.

Model predictive control

ME-425

Provide an introduction to the theory and practice of Model Predictive Control (MPC). Main benefits of MPC: flexible specification of time-domain objectives, performance optimization of highly complex multivariable systems and ability to explicitly enforce constraints on system behavior.