François Leduc-Primeau
B.Eng., M.Eng., Ph.D.
Associate Professor
Department of Electrical Engineering
Department of Electrical Engineering
Areas of expertise
Integrated circuits Communications systems Microelectronics Wireless communication systems Computer hardware Computer systems organization VLSI systems
Integrated circuits Communications systems Microelectronics Wireless communication systems Computer hardware Computer systems organization VLSI systems
Primary sphere of excellence in research
New Frontiers in Information and Communication Technologies
New Frontiers in Information and Communication Technologies
Secondary sphere(s) of excellence in research
Modeling and Artificial Intelligence
Modeling and Artificial Intelligence
Research interests and affiliations
Research interests
Telecommunications, signal processing, error-correction codes, deep neural networks, digital system design, embedded systems
Affiliation(s)
Expertise type(s) (NSERC subjects)
- 2504 Integrated circuits
- 2507 Communications systems
- 2519 Microelectronics
- 2525 Wireless communication systems
- 2701 Computer hardware
- 2702 Computer systems organization
- 2722 VLSI systems
Publications
Recent publications
Conference paper
Conference paper
Conference paper
Conference paper
Emery, J., Hasanzadeh Karkan, A., Frigon, J.-F., & Leduc-Primeau, F. (2025, September). A Foundation Model for Massive MIMO Precoding with an Adaptive Per-User Rate-Power Tradeoff [Paper]. 36th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2025), Istanbul, Turkiye (6 pages).
Hasanzadeh Karkan, A., Ibrahim, A., Frigon, J.-F., & Leduc-Primeau, F. (2025, May). A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites [Paper]. International Conference on Machine Learning for Communication and Networking (ICMLCN 2025), Barcelona, Spain.
Dupraz, E., & Leduc-Primeau, F. (2025, August). Channel Coding for Binary Neural Networks Implemented with Noisy Memristor Crossbars [Paper]. 13th International Symposium on Topics in Coding (ISTC 2025), Los Angeles, CA, USA.
Kasalaee, G., Hasanzadeh Karkan, A., Frigon, J.-F., & Leduc-Primeau, F. (2025, May). Compression of Site-Specific Deep Neural Networks for Massive MIMO Precoding [Paper]. International Conference on Machine Learning for Communication and Networking (ICMLCN 2025), Barcelona, Spain.
See all publications (69)
Biography
François Leduc-Primeau received the B.Eng. degree in 2007, the M.Eng. degree in 2010, and a Ph.D. degree in 2016, all in the department of Electrical and Computer Engineering of McGill University (Montreal, Canada). From 2016 to 2018, he was a postdoctoral researcher at IMT Atlantique in Brest, France, and then at École de technologie supérieure in Montreal. He has been a professor at Polytechnique Montreal since 2019.
His research interests span digital system design, telecommunications, and machine learning, with applications in next-generation wireless communication systems, energy-efficient artificial intelligence, and low-energy digital communication.
Education
- B.Eng. (McGill University)
- M.Eng. (McGill University)
- Ph.D. (McGill University)
Supervision at Polytechnique
COMPLETED
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Ph.D. Thesis (6)
- El-Sayegh, B. (2024). A Portable Platform for Women Pelvic Floor Muscles Function Monitoring and Assessment [Ph.D. thesis, Polytechnique Montréal].
- Henwood, S. (2024). Optimisation de réseaux de neurones profonds pour déploiement sur matériel incertain à faible consommation d'énergie [Ph.D. thesis, Polytechnique Montréal].
- Zhang, Y. (2024). Efficient Deep Learning Algorithms for Robust Prediction of Epileptic Seizures [Ph.D. thesis, Polytechnique Montréal].
- Hojatian, H. (2023). Beamforming Design for Massive MIMO Systems with Deep Neural Networks [Ph.D. thesis, Polytechnique Montréal].
- Kern, J. (2023). Improving the Energy Efficiency for Signal Processing and Machine Learning Algorithms Using Unreliable Memories [Ph.D. thesis, Polytechnique Montréal].
- El Zarif, N. (2021). A Platform for Enhancing the Vision of Patients Suffering from Age-Related Macular Degeneration Disease [Ph.D. thesis, Polytechnique Montréal].
- El-Sayegh, B. (2024). A Portable Platform for Women Pelvic Floor Muscles Function Monitoring and Assessment [Ph.D. thesis, Polytechnique Montréal].
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Master's Thesis (8)
- Kasalaee, G. (2025). Compression of Site-Specific Deep Neural Networks for Massive MIMO Precoding [Master's thesis, Polytechnique Montréal].
- Fournier, Y. (2024). Conception physique d'un processeur vectoriel RISC-V multicoeur avec une technologie avancée [Master's thesis, Polytechnique Montréal].
- Humblet, E. (2024). Verification and Characterization of Multicore Vector Processors Enhanced for Low-precision Convolutional Layers Through FPGA Emulation [Master's thesis, Polytechnique Montréal].
- Rohman, S. T. (2024). Optimisation énergétique efficace des mémoires ECC intégrées sur puce [Master's thesis, Polytechnique Montréal].
- Brown, S. (2023). Activity Reduction and Energy Modeling of Gallager-B LDPC Decoders [Master's thesis, Polytechnique Montréal].
- Chitsaz Zade Allaf, K. (2023). Robust Quantization for Enhanced Energy Efficiency and Bit Error Tolerance in DNNs [Master's thesis, Polytechnique Montréal].
- Ang Houle, L.-N. (2022). Validation et caractérisation d'un décodeur LDPC matériel en sous-alimentation [Master's thesis, Polytechnique Montréal].
- Dermont, D. B. (2022). Single-Min LDPC Offset Optimization Methods [Master's thesis, Polytechnique Montréal].
- Kasalaee, G. (2025). Compression of Site-Specific Deep Neural Networks for Massive MIMO Precoding [Master's thesis, Polytechnique Montréal].
News about François Leduc-Primeau
Press review about François Leduc-Primeau
February 22, 2024,
Québec Science,
Solutions pour une intelligence artificielle moins énergivore
François Leduc-Primeau, professeur au Département de génie électrique, explique que le développement de nouvelles puces électroniques plus efficaces rend la consommation d’énergie des grands modèles d’IA plus modérée.
