Guillaume Lajoie

I am an applied mathematician interested in the interactions and commonalities of biological and artificial neural computations. My research group works at the intersection of AI and Neuroscience, or Neuro-AI, developing tools to better understand neural networks as well as algorithms for brain-machine interfaces for scientific and clinical use. My work is motivated by the remarkable ability of neural networks (biological and artificial) to learn and support complex, emergent computations. I use tools from dynamical systems, information theory, statistics, and machine learning to address a range of problems, in collaboration with experimental neuroscientists and machine intelligence researchers.

Guillaume Lajoie is an Associate Professor in the Department of Mathematics and Statistics at Université de Montréal and a Core Academic Member of Mila – Quebec Artificial Intelligence Institute. He holds a Canada CIFAR AI Research Chair, and a Canada Research Chair in Neural Computation and Interfacing. His research is positioned at the intersection of AI and Neuroscience where he develops tools to better understand mechanisms of intelligence common to both biological and artificial systems. His research group's contributions range from advances in multi-scale learning paradigms for large artificial systems, to applications in neurotechnology. Dr. Lajoie is actively involved in responsible AI development efforts, seeking to identify guidelines and best practices for use of AI in research and beyond.

affiliations

• Associate Professor, Mathematics and Statistics, Université de Montréal
• Core Member, Mila – Quebec AI Institute
• Visiting Researcher, Google Paradigms of Intelligence Team
• Canada CIFAR AI Chair
• Canada Research Chair in Neural Computation and Interfacing
• Research Center Affiliations: UNIQUE, CIRCA, CRM
• Departmental Accreditations (UdeM): Computer Science and Operations Research, Neuroscience