Find Academic Supervisors

• Graph Representation Learning
• Deep Learning
• Reinforcement Learning
• +7 more

Jian Tang is an Assistant Professor at HEC Montreal and the Montreal Institute for Learning Algorithms (MILA), as well as an Associate Professor at the Department of Computer Science and Operations Research (DIRO) at Université de Montréal. He is also affiliated with IVADO (Institut de valorisation des données) as a member. His research spans multiple institutions including collaborations with leading biology labs worldwide and access to extensive computational resources through industry partners. Ph.D. in Computer Science, Peking University (2009-2014) Visiting Ph.D. student, University of Michigan (2011.10-2013.8) B.S. in Mathematics, Beijing Normal University (2005-2009) Professor Tang's research focuses on the intersection of deep learning and graph theory, with particular emphasis on geometric deep learning, knowledge graph reasoning, and applications in drug discovery. His work bridges symbolic and neural approaches to create robust reasoning systems that can handle complex structured data. He has pioneered techniques in graph representation learning that have significantly advanced the field of molecular property prediction and protein design. His publication record shows a clear trajectory toward applying geometric deep learning to biological problems, with a growing emphasis on protein design, molecular conformation generation, and multi-omics analysis. Recent work demonstrates sophisticated integration of 3D geometry with deep learning architectures to model complex biomolecular interactions. Canada CIFAR Artificial Intelligence Chairs (CCAI Chair) Tencent AI Lab Rhino-Bird Gift Fund Amazon Faculty Research Award Microsoft-Mila collaboration grant National Research Council Canada (NRC) Collaborative Research and Development Grant Professor Tang actively mentors doctoral and master's students, with six recent graduates working on cutting-edge topics including graph neural networks for reasoning, protein design, and molecular representation learning. His research is supported by substantial funding from industry partners including Microsoft, Amazon, and Tencent, as well as government agencies like NRC. He collaborates extensively with biology labs worldwide, applying AI to solve real-world biomedical challenges. He leads a research group focused on geometric deep learning for drug discovery, with active projects in protein design using geometric-aware models and large language models for multi-omics analysis. The group has access to thousands of GPUs through industry collaborations, enabling large-scale experiments in molecular simulation and generative modeling.

• Neuromuscular Function
• Muscle Physiology
• Aging and Exercise
• +3 more

Dr. Charles L. Rice is a Professor in the School of Kinesiology at Western University, with a joint appointment in the Faculty of Health Sciences. He holds roles as an Associate Investigator at The Lawson Health Research Institute and Research Director of the Canadian Centre for Activity & Aging. His research focuses on neuromuscular function, particularly neural control of muscle contractions during aging, fatigue, and exercise training. He earned his Ph.D. from the University of Western Ontario, M.Sc. from the University of Saskatchewan, and B.Sc. from Acadia University. Education: Ph.D., University of Western Ontario M.Sc., University of Saskatchewan B.Sc., Acadia University Research emphasizes understanding muscle-neural interactions using MRI and spectroscopy. Key themes include age-related neuromuscular decline, exercise adaptations, and disease impacts like diabetic neuropathy. Recent articles explore motor unit stability in aging athletes, fatigability mechanisms, and MRI-assessed muscle pathology. Awards include Fellow of the American College of Sports Medicine (2009). His work bridges clinical and basic science through collaborations in aging, rehabilitation, and sports medicine. The Neuromuscular Lab, supported by Schulich Medicine & Dentistry, focuses on translating findings into practical applications for human movement quality.

Wei ShiView profile

Professor

• Distributed computing
• Cloud computing
• Data center networks
• +6 more

Professor Wei Shi is a faculty member at the School of Computer Science, Carleton University. His research focuses on distributed computing, cloud networks, algorithm design for sensor/actuator systems, big data analytics, and data privacy. Notable projects include federated learning optimizations, blockchain-enabled edge intelligence for IoT/vehicle networks, and AI-driven cybersecurity solutions. His work addresses challenges in dynamic resource allocation, anomaly detection, and privacy-preserving techniques. Research Interests: Distributed Computing: Optimizing federated learning and client selection algorithms for wireless networks. Blockchain & Edge Intelligence: Developing decentralized systems for IoT and vehicular networks using AI large models. Security & Privacy: Innovating methods to detect AI-generated content, combat cyber-physical attacks, and protect user data privacy. Publications: Recent works emphasize federated learning applications, blockchain integration with edge computing, and cybersecurity for vehicular/IoT ecosystems. Key themes include energy-efficient algorithms, dynamic resource allocation, and intrusion detection in constrained environments. Email: wei.shi@carleton.ca

• Accounting Theory
• Agency Theory
• Performance Measurement
• +3 more

Florin Sabac is a Professor at the University of Alberta's Alberta School of Business, Department of Accounting and Business Analytics. He holds PhDs in Accounting and Mathematics, alongside MSc and BSc degrees in Mathematics. His research focuses on how institutional settings impact the value of accounting performance information, with contributions to agency theory, contract design, and performance measurement systems. Sabac teaches courses in managerial accounting, emphasizing decision contexts and the strategic use of accounting methods. Education: PhD in Accounting, University of Alberta PhD in Mathematics MSc in Mathematics BSc in Mathematics Research Interests: Sabac explores the intersection of accounting information systems and agency theory, particularly how performance measures function in multi-task and dynamic contractual environments. His work addresses contract renegotiation, soft information effects, and the stewardship value of managerial reports. Recent studies include analyses of employee representation in governance and cross-country comparisons of labor rights. Teaching: Sabac teaches ACCTG 324 (Intermediate Management Accounting), focusing on cost systems, pricing strategies, and performance evaluation. He emphasizes contextual decision-making and integrates academic research with practitioner insights to broaden student perspectives. Affiliations: Professor, Alberta School of Business Canada Research Chair in Accounting Theory

Liz NilsenView profile

Professor

• Developmental Psychology
• Child Communication
• Educational Technology
• +4 more

Liz Nilsen is a Professor and Clinical Research Area Head at the University of Waterloo. She specializes in developmental psychology, with a focus on child communication, social robotics, and the intersection of executive functioning with social and cognitive development. Her work explores how contextual factors, technology, and interpersonal dynamics influence children’s communicative behaviors, perspective-taking abilities, and social interactions. She is affiliated with the university’s clinical research initiatives and has collaborated on projects involving robot-assisted interventions and AI-driven educational tools. Dr. Nilsen’s research interests extend to understanding how temperamental traits like shyness, ADHD symptoms, and parental factors shape communication patterns in children and adolescents. Her studies often employ experimental designs to examine real-world scenarios, such as the impact of pandemic disruptions on adolescent mental health and the role of prosody in speaker competence judgments. She has also contributed to the design of educational platforms, such as the Curiosity Notebook, aimed at enhancing learning through teaching and critical reflection. Her publications highlight a commitment to translational research, bridging theoretical insights with practical applications in education and clinical settings. Though no specific awards are listed, her extensive body of work reflects recognition in developmental psychology and technology-mediated learning. She is based at the University of Waterloo and can be reached at enilsen@uwaterloo.ca.

John ZettelView profile

Associate Professor

• Biomechanics
• Motor Control
• Postural Control
• +3 more

Dr. John Zettel is an Associate Professor at the University of Guelph, specializing in biomechanics and motor control of human movement. His research focuses on postural control, balance recovery, and the integration of voluntary movements with rapid compensatory stepping reactions, particularly in aging populations and clinical groups such as stroke survivors. Education : B.Sc. in Kinesiology from the University of Waterloo; M.Sc. and Ph.D. from the University of Toronto. His work examines how attention, visual feedback, and vestibular input modulate balance recovery strategies, with applications to fall prevention and mobility enhancement in older adults. Recent studies include vibrotactile feedback systems for sensory substitution and dual-task paradigms for assessing age-related declines in dynamic stability. Dr. Zettel's research is funded through grants focused on clinical rehabilitation and aging populations. He supervises graduate students, including MSc candidates like Cassidy, and teaches courses in biomechanics and biophysics at the Guelph-Humber campus.

Kaylena Ehgoetz MartensView profile

Associate Professor

• Motor Control
• Cognitive Neuroscience
• Neurodegenerative Diseases
• +4 more

Kaylena Ehgoetz Martens serves as an Associate Professor in the Department of Kinesiology and Health Sciences at the University of Waterloo, where she directs the Neurocognition and Mobility Lab. Her research program integrates movement kinematics, functional neuroimaging, psychophysiology, and cognitive neuroscience to investigate the neural basis of gait control and its disruption in neurodegenerative conditions, with particular emphasis on Parkinson's disease, dementia with Lewy bodies, and isolated REM sleep behavior disorder. She focuses on the complex interplay between cognition, emotion, and motor function to develop translational approaches for early diagnosis and intervention in mobility disorders. Dr. Martens' academic training includes a BSc in Kinesiology & Physical Education from Wilfrid Laurier University, an MA in Psychology from the University of Waterloo, a PhD in Cognitive Neuroscience from the University of Waterloo, and postdoctoral training at the Medicine, Brain and Mind Centre, University of Sydney, Australia. Her educational background established the foundation for her multidisciplinary approach to movement neuroscience. Her research program centers on three interconnected aims: (1) investigating cognitive-emotional interactions in gait and balance control; (2) leveraging gait complexity to identify subclinical predictors of neurodegeneration; and (3) developing technology-enhanced diagnostic and intervention tools using virtual reality and mobile recording devices. This work addresses critical gaps in understanding how anxiety, threat processing, and autonomic dysfunction contribute to movement impairments in aging and neurodegenerative diseases. Analysis of her recent publications (2023-2025) reveals a strong trajectory in subtype-specific characterization of freezing of gait, identification of sex-specific neurodegeneration patterns, and development of AI-driven detection methods. Her work increasingly incorporates machine learning for gait analysis while maintaining clinical relevance through biomarker discovery and therapeutic innovation, particularly in the prodromal phases of synucleinopathies. Scientific Awards: No specific awards were documented in the provided source material. Dr. Martens actively supervises graduate students across all levels including undergraduate theses, MSc, PhD, and postdoctoral fellows within her Neurocognition and Mobility Lab. She provides research opportunities for volunteers, coursework interns, and research coordinators, with a focus on translating laboratory findings to clinical applications. While specific grant details weren't provided, her extensive use of advanced neuroimaging, wearable sensors, and virtual reality technologies indicates substantial research funding supporting her program. The Neurocognition and Mobility Lab operates as a collaborative hub bridging basic neuroscience with clinical practice, working closely with healthcare providers to develop practical tools for early mobility impairment detection. Current projects emphasize translating gait complexity metrics into clinical biomarkers and developing anxiety-targeted interventions to prevent falls in neurodegenerative populations, with particular attention to preserving functional independence throughout the lifespan.

• Biomechanics
• Biomedical Engineering
• Computational Modeling
• +6 more

Lindsey Westover, PhD, PEng, serves as an Associate Professor in the Department of Mechanical Engineering and Associate Dean in the Faculty of Engineering at the University of Alberta. Her research and teaching activities are centered in the Biomedical Engineering program, with her laboratory located in the Donadeo Innovation Centre for Engineering (13-224, 9211 116 St, Edmonton, AB T6G 2H5). She maintains an active research profile while contributing to academic leadership through her deanship. Her educational background includes: 2018: Postdoctoral Fellowship in Rehabilitation Medicine, University of Alberta 2016: Ph.D. in Mechanical Engineering, University of Alberta 2011: M.Sc. in Mechanical Engineering, University of Calgary 2007: B.Sc. in Mechanical Engineering, University of Calgary Dr. Westover's research program spans biomechanics and biomedical engineering with emphasis on noninvasive assessment of biological structures, vibration analysis for percutaneous implants, joint biomechanics (ligaments and cartilage), spinal deformity analysis through asymmetry metrics, mechanical testing of biological tissues, and computational modeling of biological systems. Her work integrates laboratory experiments, computational methods, and in vivo studies to develop innovative diagnostic and therapeutic approaches. Analysis of her 15 most recent publications (2018-2020) reveals consistent focus on bone mechanics, implant stability, and symmetry analysis across orthopedics, audiology, and dentistry. Key themes include osseointegration evaluation using ASIST technology, pelvic/spinal deformity quantification, and computational modeling of biological structures. Her work appears in high-impact journals spanning engineering and clinical disciplines, demonstrating strong interdisciplinary collaboration. Scientific recognition includes: Nomination for Ear and Hearing 2018 Editor's Award for bone conduction device research Dr. Westover mentors graduate students through co-authorship on numerous publications and teaches core mechanical engineering courses including MEC E 451 (Vibrations and Sound), MEC E 390 (Numerical Methods), and MEC E 200 (Introduction to Mechanical Engineering). Her research is supported by collaborative grants with clinical partners and engineering colleagues. She leads biomechanics research within the Department of Mechanical Engineering, collaborating extensively with the Faculty of Rehabilitation Medicine and surgical departments. Her laboratory develops advanced testing systems like ASIST for implant stability evaluation across hearing devices and dental applications, while her computational work informs clinical approaches to scoliosis management and fracture reconstruction.

Dongmei ZhaoView profile

Professor

• Wireless Networking
• Network Resource Management
• Mobile Edge Computing
• +4 more

Dr. Dongmei Zhao is a Professor in the Department of Electrical & Computer Engineering at McMaster University, part of the Faculty of Engineering. She specializes in wireless networking, network resource management, mobile edge computing, mobile computation offloading, and digital twins. Her research clusters focus on Digital & Smart Systems. Dr. Zhao holds a Ph.D. from the University of Waterloo. She teaches courses such as COMPENG 4DK4 (Computer Communication Networks), COMPENG 4DN4 (Advanced Internet Communications), and graduate-level courses like ECE 729 (Resource Management in Wireless Networks). Her research interests span cutting-edge topics including UAV-enabled edge computing, digital twin migration, vehicular networks, and reinforcement learning applications in resource allocation. She actively contributes to advancing 6G networks, security redundancy in autonomous systems, and decentralized manufacturing platforms. Dr. Zhao's recent publications emphasize optimization techniques for dynamic networks, platooning systems, and multi-agent learning frameworks. She has been recognized for her work in vehicular edge computing and digital twin integration, though explicit awards are not listed here. She advises on graduate studies in networking and edge computing, though no specific student names are provided in the text. Her work often intersects with practical challenges in smart infrastructure and autonomous vehicle systems.

Christophe GrovaView profile

Professor

• Biomedical Engineering
• Neuroscience
• Epilepsy Research
• +5 more

Christophe Grova , Professor in the Department of Physics at Concordia University and scientific lead of the PERFORM physiology platform , is a multidisciplinary researcher at the intersection of Biomedical Engineering , Neuroscience , and Medical Physics . He directs the Multimodal Functional Imaging Laboratory , focusing on advanced neuroimaging techniques like EEG/MEG , fMRI , and fNIRS to study brain mechanisms in epilepsy and sleep . His work emphasizes multimodal data fusion to uncover neurovascular coupling and functional connectivity patterns, with software developments such as MEM and NIRSTORM enhancing analysis precision. Key Research Areas : Epilepsy, Sleep Studies, Neuroimaging, Computational Neuroscience, Multimodal Data Fusion Affiliations : Full Professor at Concordia University (Physics), Adjunct Professor at McGill University (Biomedical Engineering, Neurology and Neurosurgery). Scientific Awards : Not explicitly listed in the provided text. Software Contributions : Developed MEM (EEG/MEG source localization) and NIRSTORM (fNIRS analysis) for open-source platforms like Brainstorm .

Alain LerouxView profile

Associate Professor

• Stroke Rehabilitation
• Hemiparesis
• Community-Based Exercise
• +3 more

Dr. Alain Leroux serves as an Associate Professor in the Department of Health, Kinesiology and Applied Physiology at Concordia University, Montreal, and maintains an active research role at the Center for Interdisciplinary Research in Rehabilitation of Greater Montreal. Appointed Lecturer in 1999, he advanced to Assistant Professor in 2001 following completion of his PhD, and achieved Associate Professor rank in 2006. His doctoral training culminated in a PhD in Rehabilitation Science from McGill University, establishing the foundation for his specialized research trajectory. Dr. Leroux's research centers on stroke rehabilitation for hemiparetic patients, demonstrating that community-based exercise programs can restore physical functions years after conventional therapy ends. His work challenges traditional rehabilitation timelines by proving functional gains persist in chronic stroke phases. Future investigations will examine physical exertion's impact on postural stability in stroke survivors, addressing critical gaps in long-term recovery mechanisms. Analysis of his 2005-2006 publications reveals consistent focus on task-oriented interventions, balance training adaptations, and community exercise efficacy for stroke rehabilitation. His methodology bridges clinical observations with laboratory measurements to quantify mobility improvements, while exploring sensory input modifications during therapy. No scientific awards were documented in the source material. While graduate student mentorship isn't specified in available records, his research program operates through the Center for Interdisciplinary Research in Rehabilitation of Greater Montreal without explicit grant references. As an active investigator at the Center for Interdisciplinary Research in Rehabilitation of Greater Montreal, he collaborates across institutional boundaries to advance rehabilitation science in the Montreal metropolitan area.

Eunsik KimView profile

Professor

• Ergonomics
• Biomechanics
• Human Factors Engineering
• +5 more

Eunsik Kim is a Professor at the University of Windsor , holding a position in the Department of Mechanical, Automotive, and Materials Engineering within the Faculty of Engineering . His research focuses on ergonomics, occupational safety, and biomechanics, with applications in automotive design, workplace safety, and human-machine interaction. He leads the Occupational Safety and Ergonomics research lab , where students explore real-world solutions for challenges such as driver fatigue, musculoskeletal risks in manual labor, and automation in agriculture. Key research interests include: Ergonomics : Optimizing workstation designs, automotive seating, and anti-vibration tools Biomechanics : Analyzing human posture, musculoskeletal loading, and workplace ergonomics Machine Learning : Developing AI-driven systems for posture recognition, workload prediction, and task automation Autonomous Vehicles : Investigating human factors in driving automation and takeover scenarios Education Innovation : Gamification in engineering labs to enhance student motivation and learning Collaborations include projects with Ewha Womans University (South Korea) on autonomous vehicle comfort and a prototype robotic system for mushroom harvesting. His work often bridges theoretical research with practical applications, addressing both industry and academic challenges. Awards and Recognition: Students Ilfeoma Michael and Elnaz Akhavan Rezaee received accolades at the Association of Canadian Ergonomists conference for their lab research Advising and Grants: Professor Kim mentors students in interdisciplinary projects, focusing on ergonomics, robotics, and AI. His research has led to innovations in workplace safety and automated systems, supported by institutional and collaborative funding. Labs/Teams: The Occupational Safety and Ergonomics Lab and partnerships with South Korean institutions drive cutting-edge studies in automotive safety, robotics, and human factors engineering.

• Reinforcement Learning
• Robotics
• Deep Learning
• +3 more

Glen Berseth is an Associate Professor in the Department of Computer Science and Operations Research at the University of Montreal and a Senior Academic Fellow at Mila – Quebec Institute for Artificial Intelligence. He is also a Canada CIFAR Chair in AI and Co-Director of the Montreal Robotics and Integrative AI Laboratory (REAL). His work focuses on reinforcement learning, robotics, and deep learning applied to autonomous systems. He holds a postdoctoral background from Berkeley Artificial Intelligence Research (BAIR), working under Sergey Levine. His research emphasizes real-world applications, including human-robot collaboration, continual learning, and multi-agent systems. He teaches courses on robot learning at the University of Montreal and Mila, covering cutting-edge techniques for general-purpose robots. Key research interests include reinforcement learning for robotics, adaptive interfaces, and sim-to-real transfer. His recent work addresses challenges in autonomous learning systems, such as robust locomotion control and efficient exploration strategies. Notable awards include the Canada CIFAR AI Chair. He has supervised numerous students, including PhD candidates Ozgur Aslan and Siddarth Venkatraman, and Master’s students like Roger Creus-Castanyer and Léa Demeule, focusing on topics like reinforcement learning and robotic control. Berseth leads research projects funded by organizations like the CRSNG, FCI, and MITACS, addressing topics such as modular lifelong learning and generalization in robotics. His lab, REAL, explores embodied AI and robotics integration.

• NeuroAI
• Computational Neuroscience
• Artificial Intelligence
• +4 more

Shahab Bakhtiari is an Adjunct Professor in the Department of Psychology at the University of Montreal's Faculty of Arts and Sciences. His research focuses on NeuroAI, exploring the intersection of neuroscience and artificial intelligence, particularly in visual perception and learning mechanisms in biological systems and artificial neural networks. He holds a PhD in Neuroscience from McGill University and conducted postdoctoral research at Mila, Quebec AI Institute. Education: Bachelor's and Master's in Electrical Engineering, University of Tehran PhD in Neuroscience, McGill University His research interests include computational neuroscience, machine learning, visual system modeling, and energy-efficient predictive coding. He teaches courses on AI, cognitive neuroscience, and deep learning applications in psychology. Key grants include a CRSNG grant (2023–2029) for comparative visual system studies and the UNIQUE strategic initiative (2022–2029), co-led by 50+ researchers. He has supervised one Master's student, Hamza Abdelhedi, on AI-human face recognition comparisons. His work bridges AI and biological systems, leveraging neuroimaging and deep learning to model brain dynamics and improve AI's biological plausibility.

M. Natasha RajahView profile

Professor

• Cognitive Neuroscience
• Memory and Aging
• Alzheimer's Disease Prevention
• +7 more

Dr. M. Natasha Rajah is a Full Professor in the Department of Psychology at Toronto Metropolitan University (TMU) and holds a Tier 1 Canada Research Chair in Sex, Gender and Diversity in Brain Health, Memory and Aging. She is also an Adjunct Faculty at McGill University's Department of Psychiatry and an Adjunct Scientist at the Rotman Research Institute, Baycrest. Her interdisciplinary affiliations reflect her leadership in cognitive neuroscience and aging research. Her research focuses on the cognitive neuroscience of memory and aging, particularly how biological sex, sociocultural gender, menopause, and social determinants of health influence brain aging and Alzheimer's disease risk. Using multimodal methods—including fMRI, structural MRI, behavioral testing, endocrine assays, and genetics—she investigates normative memory maintenance and risk factors for cognitive decline. The recent publications highlight a consistent focus on neuroimaging, memory systems, sex differences, and aging. Her work spans high-impact topics such as hippocampal mediation in aging, functional connectivity differences by sex, and genetic risk factors like APOE4. The research integrates clinical neuroscience with population diversity, aiming to develop equitable biomarkers and interventions. Scientific honors include: Tier 1 Canada Research Chair in Sex, Gender and Diversity in Brain Health, Memory and Aging CIHR Sex and Gender Research Chair in Neuroscience, Mental Health and Addiction Dr. Rajah has held major administrative roles, including Director of the Douglas Brain Imaging Centre (2011–2021) and Assistant Dean (Academic Affairs) at McGill’s Faculty of Medicine. She advises through her BHEAM Lab and leads national initiatives such as Team 9 (Developing Novel Biomarkers) and the IDEAS Committees in the Canadian Consortium on Neurodegeneration in Aging (CCNA). She is Editor-in-Chief of Aging, Neuropsychology and Cognition and Associate Editor of Psychological Science . She leads the Brain Health Equity in Aging and Memory (BHEAM) Lab at TMU, which conducts cutting-edge research on dementia prevention and brain health equity. Her team integrates cognitive testing with advanced neuroimaging and biomarker analysis to study diverse populations across the adult lifespan.