Eric Granger

Eric Granger is a Professor in the Department of Systems Engineering at École de technologie supérieure (ETS) in Montreal, Quebec, Canada. He holds a B.Sc.A. from UQAM, and M.Sc.A. and Ph.D. from Polytechnique Montréal. Dr. Granger leads research at the LIVIA – Imaging, Vision and Artificial Intelligence Laboratory and holds the Distech Controls Research Chair on Embedded Neural Networks in a Controller for Connected Buildings.

His research spans intelligent and autonomous systems with applications in health technologies. Dr. Granger's expertise includes machine learning, computer vision, pattern recognition, deep models, multimodal information fusion, domain adaptation, weakly supervised learning, and adaptive intelligent systems. His specific applications focus on face analysis and recognition, biometrics, medical imaging, affective computing, computer security, and video surveillance.

Analysis of his recent publications reveals a strong focus on person re-identification across different modalities (visible-infrared), weakly supervised object localization, depression detection from facial analysis, and medical image analysis. His work consistently addresses domain adaptation challenges and develops innovative neural network architectures for real-world applications in surveillance and healthcare.

Dr. Granger has supervised numerous doctoral students across various research topics including adaptive anomaly detection, signature verification, face recognition, medical image segmentation, and domain adaptation. His research is supported by multiple grants and collaborations with industry partners like Distech Controls.

He leads the LIVIA research laboratory which focuses on imaging, vision, and artificial intelligence applications. The lab works on projects involving embedded neural networks for connected buildings, video surveillance systems, medical imaging applications, and affective computing solutions.