Photo of Gabriel Wainer

Gabriel Wainer

Professor, Limited Engineering Licensee

Degrees:Ph.D. (Buenos Aires)
Phone:613-520-2600 x 1957
Office:VSIM 3216

Biographical Notes:

  • 2022 McLeod Founder Award for distinguished service to the profession by the Society for Modeling and Simulation International (SCS). This award recognizes a group of technical contributions which have been made by the candidate over a significant period of time. They clearly reflect a commitment by the candidate to nurturing a robust evolution of the profession. The significant nature of the contributions will be supported by their wide dissemination in the technical literature and their discernible impact on the manner in which some aspect of the modeling and simulation activity is carried out.
  • 2021 Distinguished Speaker. Association for Computing Machinery (ACM).
  • 2020 Outstanding Professional Achievement Award by the Society for Modeling and Simulation International (SCS). The award recognizes outstanding service to the Society by a member.
  • 2019 IEEE Outstanding Engineering Award (Ottawa Section). “For innovative and outstanding contributions to the field of discrete-event modeling and simulation”
  • 2017 Nepean’s Canada 150th Anniversary Medal. The medal was given in the 150 anniversary of Canadian Confederation to recognize people who have made a difference in the community or excelled in their professional life in the riding of Nepean, ON, Canada.
  • 2016 Fellow, the Society for Modeling and Simulation International (SCS).

Research Interests:

– DEVS formalism
– Real-Time modelling
– Cellular models
– Modelling and simulation methodologies and tools
– Parallel/distributed/Web-based simulation
– Real-Time operating systems

One funded PhD position is available in the area of Modeling and Simulation. Masters positions are available for Domestic students


Check our collaboration projects with Ericsson Canada

Channel Reconstruction for LTE/NR Performance Verification for Research and Leadership in Wireless Networks
Spectrum Sharing with Machine Learning
M-MIMO Channel Estimation using Distributed Machine Learning and Edge Computing Technologies
Ericsson-Carleton Partnership