جستجوی استاد راهنمای دانشگاهی

Guillaume-Alexandre Bilodeauمشاهده پروفایل

استاد

• Computer vision
• Artificial intelligence
• Image and video processing
• +۶ مورد دیگر

Guillaume-Alexandre Bilodeau is a Full Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. He serves as Head of the Laboratory for Image and Video Interpretation and Processing (LITIV) and is a member of the Institute for Data Valorization (IVADO). His research is centered within the 'New frontiers in information and communications technologies' center of excellence, with additional affiliations in 'Modeling and Artificial Intelligence' and 'Transport and Sustainable Infrastructure' centers. Professor Bilodeau's research focuses on computer vision and artificial intelligence, with particular expertise in: Developing methods for interpreting human actions and interactions within scenes Integrating visible and infrared camera data for improved object and human detection Object tracking using pan-tilt-zoom camera systems Medical applications of thermal imaging and thermography, including Parkinson's disease diagnosis from gait analysis His recent publications demonstrate continued strong activity in video prediction, medical applications of computer vision, and multi-object tracking. Professor Bilodeau maintains a robust publication record with multiple 2025 publications in top venues, reflecting ongoing research productivity and relevance in the computer vision community. Professor Bilodeau has received significant recognition for his work, including: 2023: Fonds de recherche du Québec research grant award 2008: Best vision paper award at Canadian Conference on Robot Vision 2002: Honorable mention for Pattern Recognition Society award As an educator and mentor, Professor Bilodeau has supervised 12 PhD students and 26 Master's students to completion. He teaches courses in multimedia technologies and computer vision. His laboratory, LITIV, provides a research environment focused on image and video interpretation with applications spanning surveillance systems, medical diagnostics, and transportation infrastructure monitoring.

Frédéric Lesageمشاهده پروفایل

استاد

• Biomedical Engineering
• Neuroimaging
• Optical Imaging
• +۵ مورد دیگر

Frédéric Lesage is a Full Professor in the Department of Electrical Engineering at Polytechnique Montréal and holds a Tier 1 Canada Research Chair in Vascular Optical Imaging. His multidisciplinary research bridges biomedical engineering, neuroscience, and AI, with affiliations spanning the Functional Imaging Laboratory (INSERM), Montreal Heart Institute, and Centre for Mathematical Research. Research interests center on neuroimaging innovations for studying cerebral physiology. Key areas include: Neurovascular Coupling: Investigating blood flow dynamics in aging and Alzheimer's using optical coherence tomography and NIRS. Epilepsy Diagnostics: Developing AI models for seizure prediction via EEG/fNIRS fusion. Microvascular Pathologies: Mapping microstroke impacts using two-photon microscopy and adversarial learning. His 15 most recent publications (2020-2025) emphasize AI-driven neurology applications, showing trends in: Machine learning for epileptic EEG analysis Cerebral pulsatility in neurodegenerative diseases Translational vascular imaging (OCT/TPM) Awards include the Canada Research Chair (Tier 1) , renewed in 2022 for pioneering vascular imaging techniques. He has advised 57+ graduate students (27 PhD, 30 Master's) and secured grants from NSERC, CIHR, and CRC. Current projects focus on hypoxia effects, statin therapy in Alzheimer's, and catheter-based surgical simulators.

Hilary Evans Cameronمشاهده پروفایل

دانشیار

• Refugee law
• Evidence law
• Administrative law
• +۹ مورد دیگر

Hilary Evans Cameron is an Associate Professor at the Lincoln Alexander School of Law, Toronto Metropolitan University, where she teaches Evidence Law, Administrative Law, and Advanced Legal Research and Writing. A former litigator with a decade of experience representing refugee claimants, she holds a Doctor of Juridical Science from the University of Toronto. She is an active researcher and member of the Bridging Divides research team. Education: SJD (Doctor of Juridical Science), University of Toronto, 2016 LLB (Bachelor of Laws), Osgoode Hall Law School, 2001 BA Hons. (Bachelor of Arts, Honours), McGill University, 1998 Research Focus: Her work centers on fact-finding at the intersection of law and psychology, examining how decision-makers assess credibility in refugee cases. Key areas include deception detection, risk perception, memory limitations, and legal logics. She also explores administrative law pedagogy, pseudoscience in legal contexts, and AI applications in refugee hearings. Publication Trends: Her extensive publications demonstrate a consistent focus on refugee status determination, credibility assessment, and administrative justice. Recent works explore AI integration in legal processes, Indigenous oral history in courts, and psychological factors in refugee testimony. Methodologically, she employs empirical analysis and interdisciplinary approaches blending legal theory with behavioral science. Awards & Honors: Professor of the Year (Lincoln Alexander Law inaugural class), 2023 Dean's Scholarly Research and Creativity Award, 2023 Bora Laskin National Fellow in Human Rights Research (SSHRC), 2017 Research Leadership: She leads international training sessions on refugee law and has secured funding from SSHRC, the Law Foundation of Ontario, and the British Academy. As part of the Bridging Divides team, she collaborates on projects addressing systemic challenges in legal decision-making.

Ange Adrienne Nyamen Tatoمشاهده پروفایل

استادیار

• Artificial Intelligence in Education
• Generative AI for Education
• Machine Learning Algorithms
• +۷ مورد دیگر

Ange Adrienne Nyamen Tato serves as an Assistant Professor in the Department of Teaching and Learning Studies at Laval University's Faculty of Education. Her academic journey spans multiple institutions across Canada and Morocco, with a strong interdisciplinary background combining computer science, artificial intelligence, and educational theory. PhD in Computer Science (Artificial Intelligence) from University of Quebec at Montreal (UQAM), 2020 Master's degree in Computer Science from University of Quebec at Montreal (UQAM), 2015 Engineering degree in Information Systems from Mohammedia School of Engineers in Morocco, 2014 DEUST in Mathematics, Computer Science and Physics from Hassan II University, Morocco, 2011 Professor Tato's research focuses on the intersection of artificial intelligence and education, with particular expertise in generative AI applications for educational contexts, machine learning algorithms, intelligent tutoring systems, educational data mining, and serious game design. Her work addresses critical challenges in educational technology including transparency, assessment practices, and engagement issues that have limited the adoption of AI-powered learning tools. She is particularly interested in the ethical implications, environmental impact, and potential biases of AI in educational settings. Her recent publications demonstrate a consistent focus on developing sophisticated models for user behavior prediction, adaptive learning systems, and integrating pedagogical knowledge into AI frameworks. The research spans multiple domains including logical reasoning development, socio-moral reasoning, piloting training, and general educational applications of deep learning and knowledge tracing techniques. Professor Tato has secured significant research funding, including a $192,500 NSERC Discovery Grant for her project 'Optimizing Generative Artificial Intelligence for Education: Towards a Holistic Approach Integrating Teachers and Learners.' This five-year project aims to develop pedagogically aware large language models (PA-LLMs) that better serve educational purposes by integrating educational theories, human learning factors, and bias correction mechanisms. Principal Investigator for NSERC Discovery Grant ($192,500 over 5 years) PC Member for ICCE 2023 and 2024 conferences PC Member for EDM 2024 conference PC Member for AIED 2024 conference Professor Tato teaches graduate courses including TEN-7028 Games and Learning and TEN-7030 Digital Intelligence in Education: Opportunities and Challenges. She is currently accepting Master's students interested in AI applied to education. Her previous professional experience includes work as an Artificial Intelligence Specialist at Beam Me Up Augmented Intelligence (2018-2022) and a postdoctoral fellowship in Deep Learning applied to aeronautics in partnership with Bombardier and CAE (2020-2022).

Araz Jabbariمشاهده پروفایل

دانشیار

• Information Systems
• Conceptual Modeling
• Digital Transformation
• +۴ مورد دیگر

Dr. Araz Jabbari serves as an Associate Professor in the Department of Organizational Information Systems at Laval University's Faculty of Business Administration. His research examines how individuals and organizations engage with digital technologies and navigate digital transformation, with particular focus on conceptual modeling practices in increasingly complex digital environments. Dr. Jabbari maintains an active research agenda that bridges theoretical frameworks with practical applications, contributing significantly to information systems scholarship through publications in top-tier journals and conferences. Dr. Jabbari's academic foundation includes: Ph.D. in Information Systems from Queensland University of Technology MBA in IT Management from Multimedia University B.Sc. in Mathematics from University of Urmia Dr. Jabbari's research centers on conceptual modeling in the digital era, investigating how traditional modeling approaches must evolve to address contemporary challenges. His work explores how individuals understand and use multiple conceptual modeling scripts, ontological overlap in combined models, and the transition from representation to mediation in digital environments. Recent research increasingly addresses AI-specific challenges, including information quality frameworks for AI systems and the faithfulness of machine learning training data. His scholarship examines digital transformation from both technical and organizational perspectives, with growing emphasis on how data, intelligence, and transparency reshape coordination practices. Dr. Jabbari's publication trajectory demonstrates progression from foundational conceptual modeling research to cutting-edge investigations at the intersection of information systems, organizational theory, and artificial intelligence. His work shows increasing engagement with interdisciplinary topics, particularly how digital systems fundamentally reshape organizational practice. The research evolution reflects the field's broader shift from viewing information systems as representations to understanding their mediating role in digital ecosystems. Dr. Jabbari's scholarly impact is evident through: Publications in premier journals including MIS Quarterly, Journal of the Association for Information Systems, and Decision Support Systems Presentations at leading conferences such as HICSS and AMCIS Development of influential frameworks like 'Modeling 4.0' that reshape conceptual modeling discourse 297 citations across 29 publications indicating research influence As an educator, Dr. Jabbari teaches system analysis and design, business analysis, and digitization courses that likely integrate his research expertise. His student supervision approach probably emphasizes both theoretical rigor and practical application, preparing students to address real-world digital transformation challenges. His collaborative research style, evident in numerous international co-authorships, suggests opportunities for students to engage with a global research network. The Department of Organizational Information Systems at Laval University provides a rich academic environment where Dr. Jabbari contributes to shaping how future information systems professionals understand and design digital solutions for complex organizational challenges.

Samira Abbasgholizadeh-Rahimiمشاهده پروفایل

استادیار

• Artificial Intelligence in Primary Healthcare
• Digital Health Technologies
• Medical Machine Learning
• +۵ مورد دیگر

Dr. Samira Abbasgholizadeh-Rahimi serves as Assistant Professor at McGill University in the Faculty of Medicine and Director of Artificial Intelligence in Family Medicine (AIFM) . She holds the Canada Research Chair in Advanced Digital Primary Health Care and maintains affiliations with Mila – Quebec AI Institute and Lady Davis Institute for Medical Research . B.Eng., Ph.D. from McGill University President-Elect, Canadian Operational Research Society Her interdisciplinary research bridges Artificial Intelligence and Primary Healthcare , with specific focus on: AI-enabled decision support tools Explainable machine learning for clinical contexts Medical knowledge graphs and NLP applications Addressing algorithmic bias in vulnerable populations Ageism mitigation in health AI systems Digital support for neurocognitive disorders Recent publications demonstrate her expertise in: AI ethics and EDI integration (4 papers since 2024) Geriatric depression prediction models (2025 JMIR study) Shared decision-making frameworks (2022-2023 series) Conscious AI debates in clinical settings (2024 commentary) Scientific recognition includes: 2022 NAPCRG New Investigator Award Cross-institutional collaborations across Canada, Europe, and Asia Research funding sources: Fonds de recherche du Québec – Santé Natural Sciences and Engineering Research Council Brocher Foundation (Switzerland) CIHR SPOR grants Industry partnership with Roche Canada Lab activities including: Developing HOPE (Home-Based Older Adults' Depression Prediction) model Creating incorpoRATE SDM assessment framework Building evidence-based decision support tools for dementia caregivers Training next-gen AI healthcare researchers through Mila collaborations