Machine Learning Applications in Biomedical Engineering Professors and Supervisors in Canada

Marzyeh Ghassemiمشاهده پروفایل

استادیار

University of TorontoCanada

Dr. Marzyeh Ghassemi serves as an Assistant Professor at the University of Toronto with cross-appointments in Computer Science and Medicine. She holds a Canadian CIFAR AI Chair and is a faculty member at the Vector Institute, focusing on bridging artificial intelligence with clinical healthcare applications through rigorous academic research and community leadership. Her educational background includes dual B.S. degrees in Computer Science and Electrical Engineering from New Mexico State University as a Goldwater Scholar, an MSc in Biomedical Engineering from Oxford University as a Marshall Scholar, and doctoral research at MIT centered on machine learning for clinical risk prediction and patient stratification. Professor Ghassemi's research program pioneers machine learning solutions for critical healthcare challenges, including physiological state estimation in critical illness, clinical intervention modeling, and phonotraumatic voice disorder diagnosis using wearable sensors. Her methodological expertise spans unsupervised learning, supervised learning, and structured prediction, with significant contributions to translating AI innovations into real-world clinical settings. Her scientific recognition includes the prestigious Canadian CIFAR AI Chair, Marshall Scholarship, and Goldwater Scholarship, reflecting her exceptional trajectory from undergraduate studies through doctoral research and into independent scholarship. Professor Ghassemi actively shapes her field through service as NeurIPS 2019 Workshop Co-Chair, Board Member of the Machine Learning for Health Unconference, and organizer of the NIPS Workshop on Machine Learning for Health (2016-2018). She regularly reviews for top venues including NIPS, ICML, KDD, and JMLR while mentoring through formal academic channels. Her research extends through clinical collaborations with Beth Israel Deaconess Medical Center and Massachusetts General Hospital, fostering interdisciplinary partnerships that connect computational innovation with frontline healthcare delivery and patient outcomes.

پروفایل رسمی دانشگاه

Ejaife Agbaniمشاهده پروفایل

استادیار

University of CalgaryCanada

Dr. Ejaife Agbani is an Assistant Professor of Thrombosis and Haemostasis Cell Biology at the Cumming School of Medicine, Department of Physiology and Pharmacology, University of Calgary. He is also a Member of the Libin Cardiovascular Institute and the McCaig Institute for Bone and Joint Health, and a Child Health & Wellness Researcher at the Alberta Children's Hospital Research Institute. Dr. Agbani's educational background includes: Bachelor of Pharmacy (with Distinction) from Obafemi Awolowo University, Nigeria Master's in Clinical Pharmacy (with Distinction) from University College London, England PhD in peroxynitrite chemistry and cellular actions in pulmonary hypertension from Strathclyde University, Glasgow, Scotland (2010) Post-doctoral research at University of Edinburgh and University of Bristol Dr. Agbani's research focuses on platelet biology, specifically on membrane dynamics in thrombosis and hemostasis. His lab pioneers approaches to target procoagulant membrane dynamics to control platelet-driven thrombosis without blocking essential pro-hemostatic platelet secretions. This work opens pathways for developing new antithrombotics devoid of bleeding side effects. His research spans thrombo-haemorrhagic complications of pregnancy, drug-induced thrombosis, and sickle cell disease, coupling machine learning with systematic quantification of platelet procoagulant membrane dynamics. Analysis of Dr. Agbani's recent publications reveals a strong focus on platelet procoagulant membrane dynamics across multiple disease contexts. His work consistently explores the distinction between thrombosis and hemostasis mechanisms, with particular emphasis on pregnancy complications like preeclampsia, cancer-associated thrombosis, and viral infections including COVID-19. The research integrates advanced imaging, proteomics, and machine learning approaches to identify novel therapeutic targets and diagnostic biomarkers. Dr. Agbani's notable recognition includes: Member of CIHR Advisory Board for Institute of Circulatory and Respiratory Health (2024) Dr. Agbani's research program, the "AgbaniLab," is supported by multiple prestigious funding sources including the McCaig, Libin, ACHRI, and Snyder Institutes at the University of Calgary, the Cal Wenzel Family Foundation, and a Canada NSERC Discovery Grant. His work bridges basic science with clinical applications through collaborations with clinicians across multiple specialties. The Agbani Lab is actively engaged in several university strategic initiatives including Child Health and Wellness (2020-2025), Engineering Solutions for Health (2015-2021), and Infections, Inflammations and Chronic Diseases (2015-2021), reflecting the transdisciplinary nature of his research in platelet biology and thrombosis.

پروفایل رسمی دانشگاه

Eli Kinney-Langمشاهده پروفایل

استاد

University of CalgaryCanada

Eli Kinney-Lang serves as an Azrieli Accelerator Professor within the Department of Biomedical Engineering at the Schulich School of Engineering, University of Calgary. They also hold appointments as Engineering Core Director and Child Health and Wellness Researcher at the Alberta Children's Hospital Research Institute, Owerko Centre. Their primary research focus is developing inclusive brain-computer interface systems for pediatric applications. Educational background: PhD in Digital Signal Processing (Brain-computer Interfaces), University of Edinburgh, UK BSc in Mathematics, University of Wyoming, USA Kinney-Lang's research specializes in Pediatric Brain-Computer Interfaces, addressing the critical gap in BCI technology for children with complex needs. They investigate adaptations across the entire BCI pipeline - from signal acquisition and processing to machine learning classification and feedback - ensuring inclusivity for diverse pediatric populations. This work bridges biomedical engineering, child health, and assistive technology development. They participate in multiple university strategic initiatives including Brain and Mental Health (2015-2021), Child Health and Wellness (2020-2025), Engineering Solutions for Health (2015-2021), and Human Dynamics in a Changing World (2015-2021). Award: Azrieli Accelerator Professorship in Inclusive Engineering Technologies for Neurodevelopment Kinney-Lang directs the BCI4Kids initiative, which develops brain-computer interface technologies specifically for children. Their work integrates engineering solutions with child health research to create accessible neurotechnology, supported by their dual affiliations with the university's engineering school and children's hospital research institute.

پروفایل رسمی دانشگاه

Matthew Ethan MacDonaldمشاهده پروفایل

دانشیار

University of CalgaryCanada

Ethan MacDonald is an Associate Professor in the Department of Biomedical Engineering and Department of Electrical and Software Engineering at the Schulich School of Engineering, University of Calgary. He also holds an Adjunct Associate Professor position in the Department of Radiology at the Cumming School of Medicine and is a Full Member of both the Hotchkiss Brain Institute and the Alberta Children's Hospital Research Institute. His research program focuses on three core themes: software and hardware for MRI image acquisition and reconstruction, big data science for biomedical applications, and modeling brain circuits to inspire next-generation intelligent algorithms. Dr. MacDonald completed his technical diplomas in electronics engineering at Nova Scotia Community College, followed by a BEng in Electrical Engineering at Lakehead University where he received the Dean Brawn Medal for highest ranking graduating student and the Professional Engineers of Ontario Medal. He then pursued graduate studies at the University of Calgary, earning his MSc (2010) and PhD (2014) in Biomedical Engineering, followed by a Postdoctoral Fellowship in Radiology (2020). He was appointed as an Assistant Professor in 2020 and became a founding member of the Department of Biomedical Engineering in 2021. His research encompasses diverse applications of Magnetic Resonance Imaging, including endovascular catheter tracking, quantitative cerebrovascular imaging, and imaging of brain development and aging physiology. He specializes in acquisition and reconstruction of MRI data, pulse sequence programming, and brain imaging methods such as vascular imaging, functional MRI, and diffusion tensor imaging. His work integrates big data analytics, machine learning, and computational modeling for applications in neuroinformatics, brain morphology, aging physiology, and genetics. Dr. MacDonald's publications demonstrate significant contributions to age prediction models using cerebral blood flow and cortical thickness measurements, cerebrovascular reactivity analysis, machine learning applications in neuroimaging, and novel MRI techniques for vascular and brain imaging. His research shows a consistent trajectory toward integrating advanced computational methods with sophisticated MRI techniques to address fundamental questions in neuroscience and clinical applications. Dean Brawn Medal for highest ranking graduating student Professional Engineers of Ontario Medal for Academic Achievement Dr. MacDonald actively supervises graduate students in Electrical and Computer Engineering and Biomedical Engineering programs. His lab emphasizes skill development in programming, writing, and presentation skills, while promoting a culture of healthy work-life balance, equity, diversity, and inclusion. He serves on university strategic initiatives including Brain and Mental Health (2015-2021), Child Health and Wellness (2020-2025), Engineering Solutions for Health (2015-2021), and One Health (2020-2025). His teaching includes courses on sensor systems, biomedical imaging, and advanced data analytics.

پروفایل رسمی دانشگاه

Junho Parkمشاهده پروفایل

استادیار

University of CalgaryCanada

Junho Park is an Assistant Professor at the University of Calgary, holding cross-appointment across three academic units: Schulich School of Engineering (Biomedical Engineering), Cumming School of Medicine (Community Health Sciences), and Faculty of Arts (Psychology). He also serves as Faculty Researcher at W21C Research and Innovation Centre, Member at O'Brien Institute for Public Health, and Child Health and Wellness Researcher at Alberta Children's Hospital Research Institute. PhD in Industrial and Systems Engineering (Texas A&M University) MSc in Industrial Engineering (Seoul National University) BSc in Computer and Industrial Engineering with Psychology minor (Yonsei University) His research focuses on Human-AI Interaction, Human Factors Engineering, and Ergonomics, with specific applications in biosignal processing for prosthetics, workload assessment in assistive technologies, and cognitive support systems for aging populations. Current projects include augmented reality biofeedback systems and autonomous vehicle interfaces for individuals with cognitive impairments. Recent publications demonstrate expertise in applying machine learning to biomedical engineering challenges and human factors assessments. The HERO Lab actively seeks postdoctoral researchers and graduate students in areas spanning human-AI interaction, ergonomics, and computational modeling. Scientific Awards Student Member with Honours, Human Factors and Ergonomics Society (2023) IEEE International Conference on Human-Machine Systems Travel Grant (2022) Institute for Applied Creativity Student Fellowship, TAMU (2022) Korean-American Scholarship Foundation (2021) HFES Best Student Paper Award (2021)

پروفایل رسمی دانشگاه

Naimul Khanمشاهده پروفایل

دانشیار

Toronto Metropolitan UniversityCanada

Naimul Khan is an Associate Professor and Associate Chair in Graduate Studies at Toronto Metropolitan University's Department of Electrical, Computer, and Biomedical Engineering. His research focuses on practical applications of machine learning, medical imaging, computer vision, and augmented/virtual reality technologies to solve real-world healthcare and multimedia challenges. PhD (Toronto Metropolitan University, 2014) MSc (University of Windsor, 2010) BSc (Bangladesh University of Engineering and Technology, 2008) His research interests span medical imaging automation, virtual reality systems for healthcare applications, and machine learning techniques for biomedical signal processing. He has developed innovative algorithms for ultrasound analysis, emotion recognition systems using EEG data, and segmentation approaches for diabetic foot ulcers. Publications demonstrate consistent focus on practical implementations across computer vision, medical diagnostics, and extended reality (XR) technologies. Scientific contributions include a Best Paper Award at the IEEE International Symposium on Multimedia (2017) and prestigious postdoctoral and graduate scholarships. He actively collaborates with industry partners through the TMU Multimedia Research Laboratory, teaching graduate courses like ELE 725 (Basics of Multimedia Systems) and COE 318 (Software Systems). Best Paper Award, IEEE International Symposium on Multimedia (2017) OCE TalentEdge Postdoctoral Fellowship (2014-2016) Ontario Graduate Scholarship (2013-2014) Queen Elizabeth II Scholarship in Science & Technology (2012-2013) As co-director of the TMU Multimedia Research Laboratory, Khan bridges academic research with industry applications through practical implementations of machine learning and extended reality technologies in healthcare domains.

پروفایل رسمی دانشگاه

Robert Funnellمشاهده پروفایل

استاد

McGill UniversityCanada

Robert Funnell, PhD is an Investigator at the Research Institute of the McGill University Health Centre (RI-MUHC) and a Professor in the Department of Otolaryngology - Head and Neck Surgery at McGill University's Faculty of Medicine. His research is conducted within the Child Health and Human Development Program at RI-MUHC, where he applies engineering principles to understand auditory mechanics and improve diagnostic tools for hearing assessment. Dr. Funnell's research focuses on the mechanics and acoustics of hearing, with particular emphasis on developing novel measurement techniques in experimental animals and infants, and creating computational models of the ear. His work combines experimental measurements with sophisticated modeling approaches to better understand middle ear function. He has developed specialized software for creating 3D models of complex anatomical structures, including his notable Thrup'ny 3D viewer application. His research has significant clinical applications, particularly in improving newborn hearing screening protocols and developing better diagnostic tests for middle ear conditions. Analysis of Dr. Funnell's recent publications reveals a consistent trajectory in middle ear biomechanics research spanning several decades. His work demonstrates increasing sophistication in computational modeling techniques, with recent publications integrating optical coherence tomography, X-ray microCT data, and finite element analysis to create increasingly accurate representations of middle ear function. A significant portion of his recent work focuses on newborn hearing assessment, reflecting the clinical importance of early hearing detection. His research bridges engineering principles with clinical audiology, creating practical applications for hearing screening and diagnosis. Dr. Funnell has developed several notable software tools including Thrup'ny, a free open-source 3D viewer for VRML models designed for both anatomy teaching and finite-element pre- and post-processing. His website hosts various educational resources including interactive 3D models of the ear, finite-element simulation tools, and teaching materials on middle ear mechanics. These resources have been widely used for both research and educational purposes in the field of otolaryngology and biomedical engineering.

پروفایل رسمی دانشگاه

Ethan MacDonaldمشاهده پروفایل

دانشیار

University of CalgaryCanada

Dr. Ethan MacDonald is an Associate Professor with joint appointments in Biomedical Engineering and Electrical & Software Engineering at the University of Calgary's Schulich School of Engineering. He also serves as Adjunct Associate Professor in Radiology at the Cumming School of Medicine and holds full memberships at the Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute. Educational background includes: Postdoctoral Fellowship in Radiology (UCalgary, 2020) PhD in Biomedical Engineering (UCalgary, 2014) MSc in Biomedical Engineering (UCalgary, 2010) BEng in Electrical Engineering (Lakehead University, 2008) Diplomas in Electronics Engineering (Nova Scotia Community College, 2005-2006) His research program centers on three interconnected themes: MRI hardware/software development for image acquisition/reconstruction Big Data analytics and machine learning for biomedical applications Brain circuit modeling for next-generation intelligent algorithms This work intersects biomedical engineering, medical imaging, and artificial intelligence. Notable scientific awards include: Dean Brawn Medal for academic excellence Professional Engineers of Ontario Medal Dr. MacDonald leads the Brain Image Team and mentors students through skill development in programming, technical writing, and presentation. The lab prioritizes work-life balance while preparing trainees for leadership positions in academia and industry.

پروفایل رسمی دانشگاه

Abolfazl Mohebbiمشاهده پروفایل

دانشیار

Polytechnic School of MontrealCanada

Abolfazl Mohebbi is an Associate Professor in the Department of Mechanical Engineering at Polytechnique Montréal. He directs the Polytechnique Laboratory for Assistive and Rehabilitation Technologies (POLAR) and holds the TransMedTech Research Chair in Assistive and Rehabilitation Technologies. His academic appointments also include Adjunct Professor at McGill University's Department of Biomedical Engineering and membership in numerous research networks including REPAR, FRQNT INTER cluster, Pediatric Rehabilitation Technology Park, and several biomedical engineering institutes. Professor Mohebbi's research focuses on robotics, control systems, and applied artificial intelligence with applications in biomedical engineering. His laboratory develops innovative robotic and biomechatronic technologies to help humans relearn, restore, or enhance their neuromotor performance. Specific research areas include human balance control modeling, joint neuromechanics, deep learning for medical diagnosis, sensory restoration in prosthetic users, custom exoskeleton design, and robotic rehabilitation systems. His recent publications (2022-2025) show a strong focus on rehabilitation robotics, with significant contributions to exoskeleton control, prosthetic feedback systems, neuromuscular modeling, and AI applications in medical diagnostics. The research demonstrates interdisciplinary collaboration across engineering, neuroscience, and clinical rehabilitation. Professor Mohebbi has received research funding from various organizations including NSERC, as evidenced by multiple grants awarded to Polytechnique Montréal researchers. His work demonstrates strong connections between academic research and clinical applications in rehabilitation engineering. He teaches courses in dynamic systems analysis, mechatronics, and dynamic measurement at Polytechnique Montréal and has supervised five graduate students to completion (one PhD and four Master's students) with research topics directly aligned with his laboratory's focus areas.

پروفایل رسمی دانشگاه

Steven Dufourمشاهده پروفایل

استاد

Polytechnic School of MontrealCanada

Professor Steven Dufour is a Full Professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal. With a career spanning over two decades since completing his Ph.D. in 1999, he has established himself as an expert in numerical modeling, particularly in the areas of finite element methods and multiphase systems. His academic journey began with B.Sc. and M.Sc. degrees from the University of Montreal, followed by a Ph.D. from Polytechnique Montréal. Professor Dufour's research focuses on the numerical modeling of free surface flows in industrial processes, with expertise recognized by NSERC in modeling, simulation, and finite element methods (topic 2107) and polyphase systems (topic 2202). Professor Dufour's research interests span computational fluid dynamics, finite element analysis, and more recently, the integration of machine learning techniques with traditional numerical methods. His work has evolved from foundational research in adaptive finite element methods for multiphase flows to cutting-edge applications combining physics-informed neural networks with computational fluid dynamics, electromagnetic field analysis, and millimeter-wave sensing. His publication record demonstrates consistent research productivity, with 23 publications documented across computational mathematics and engineering applications. The most recent publications from 2024 show his adaptation to emerging methodologies in computational science, particularly the application of physics-informed neural networks to solve complex fluid dynamics problems. NSERC Expertise: Modeling, simulation and finite element methods (2107) NSERC Expertise: Polyphase Systems (2202) Supervised 7 doctoral students to completion Supervised 13 master's students to completion Professor Dufour has maintained active research funding and supervision throughout his career, mentoring students in both theoretical numerical methods and practical engineering applications. His collaborative work spans multiple engineering disciplines, connecting computational mathematics with real-world industrial and biomedical problems.

پروفایل رسمی دانشگاه

Guillaume-Alexandre Bilodeauمشاهده پروفایل

استاد

Polytechnic School of MontrealCanada

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.

پروفایل رسمی دانشگاه

Frédéric Lesageمشاهده پروفایل

استاد

Polytechnic School of MontrealCanada

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.

پروفایل رسمی دانشگاه

Sina Radمشاهده پروفایل

استادیار

University Canada WestCanada

Sina Rad serves as Assistant Professor in the Master of Management program at the University of Niagara Falls Canada, specializing in the intersection of emerging technologies and business management. His research bridges computational methods with organizational leadership, focusing on practical applications that transform business processes and public administration. His academic credentials include: PhD in Management, Gordon S. Lang School of Business and Economics, University of Guelph MSc in Computer Science BEng in Software Engineering Dr. Rad's research portfolio demonstrates exceptional interdisciplinary range , spanning machine learning applications in healthcare diagnostics (2013), digital accountability systems in public administration (2016-2022), and blockchain solutions for business contracts (2025). His work consistently examines how technological innovations reshape organizational behavior, human resource practices, and management frameworks through rigorous analytical methods. Publication trends reveal growing focus on business-technology integration , with recent work emphasizing blockchain's transformative potential in contractual systems and machine learning's role in business analytics. His research spans administrative sciences, information systems, and computational social science, reflecting the increasingly digital nature of modern management challenges. As an educator, Dr. Rad teaches graduate courses including Technology Trends and Applications, Data Analytics for Management, and Capstone Project development. His industry-relevant curriculum prepares students for technology-driven business environments through practical implementation frameworks and analytical case studies. Students benefit from his dual expertise in software engineering and management theory when exploring emerging technology applications.

پروفایل رسمی دانشگاه