جستجوی استاد راهنمای دانشگاهی

• Machine Learning
• Surgical Research
• Biomedical Informatics
• +۴ مورد دیگر

Stephen Kelly is an Assistant Professor in the Department of Computing and Software at McMaster University. His interdisciplinary work spans surgical research methodology, biomedical informatics, and machine learning. Affiliation: McMaster University Roles: Faculty in Computing and Software, Surgical Research Collaborator Research Interests: Dr. Kelly’s work focuses on applying evolutionary computation and reinforcement learning to medical and educational challenges, such as detecting mind wandering via EEG and optimizing surgical training programs. His research bridges clinical practice and software innovation. Recent Publications: Trends include automated program synthesis, neural memory frameworks for RL, and evidence-based surgical education tools. Key areas: AI for healthcare, algorithmic design, and educational technology. Contact: Email: kellys32@mcmaster.ca

Michiel Smidمشاهده پروفایل

استاد

• Computational Geometry
• Geometric Networks
• Graph Algorithms
• +۳ مورد دیگر

Michiel Smid is a Professor in the School of Computer Science at Carleton University. He earned his Ph.D. from the University of Amsterdam and M.Sc. from Eindhoven University of Technology. His research focuses on Computational Geometry, Geometric Networks, Graph Algorithms, and Data Structures, with applications in manufacturing. He joined Carleton in 2001 as an Associate Professor and was promoted to Professor in 2004. Education: Ph.D. in Computer Science, University of Amsterdam (1989) M.Sc. in Mathematics and Computer Science, Eindhoven University of Technology (1986) Research Interests: Design and analysis of algorithms Spanner networks and geometric routing Graph theory and combinatorial optimization Applications of computational geometry in manufacturing Affiliations: Computational Geometry Lab at Carleton University Former positions include the Max-Planck-Institute for Computer Science (1990–1996) and the University of Magdeburg (1996–2001) Teaching: Winter 2025: COMP/MATH 3804 (Design and Analysis of Algorithms I) Focus on algorithmic theory and practical implementations Labs/Teams: Active in the Computational Geometry Lab, collaborating on geometric algorithms and spanner networks.

Swati Mishraمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Dr. Swati Mishra is an Assistant Professor at McMaster University's Faculty of Engineering, Department of Computing and Software, specializing in Human-Computer Interaction , Machine Learning , and Explainable AI . With 9 years of industry experience and a PhD in Information Science from Cornell University, she focuses on designing interactive AI systems for healthcare, computational journalism, and museum engagement. PhD: Cornell University (Bloomberg Data Science Fellowship) MSc: Computer Science (Cornell), Human-Computer Interaction (Indiana University) Her research explores Machine Teaching , Concept-Based Explanations , and Human-Centered AI , with publications in ACM SIGCHI, CSCW, UMAP, and IEEE VIS. Her lab develops tools to bridge human cognitive models with AI systems, emphasizing transparency and usability. Recent projects include: Risk Analysis Dashboard for FDA clinical trial documentation Gestural interaction systems for museums Interactive Transfer Learning tools She has received a Best Paper Award at ACM SIGCHI and held industry roles in AI product development. Contact: mishrs23@mcmaster.ca | Personal Website | Office: ABB C-531

• Spatiotemporal Data Management
• Spatial Crowdsourcing
• Routing Algorithms
• +۳ مورد دیگر

Mario Nascimento is a Professor at the University of Alberta 's Department of Computing Science within the Faculty of Science. He previously served as department Chair from 2014-2021 (with a 2019-2020 leave) and holds affiliations with institutions including the National University of Singapore , Aalborg University , and others. His current leave-of-absence status allows focusing on specific research initiatives.

Jason Snyderمشاهده پروفایل

دانشیار

• Behavioral Neuroscience
• Neuroscience
• Cognitive Neuroscience
• +۴ مورد دیگر

Dr. Jason Snyder is an Associate Professor in the Department of Psychology at the University of British Columbia (UBC) and a member of the Centre for Brain Health. He holds a PhD from the University of Toronto (2005). His research focuses on hippocampal neurogenesis and its role in memory, decision-making, and stress-related behaviors. Snyder uses transgenic animals, viral tools, immunohistochemistry, and electrophysiology to study how new neurons regulate behavior. He has published extensively on neurogenesis across the lifespan, including its effects on spatial learning, reward processing, and psychiatric disorders. Education: PhD in Psychology, University of Toronto, 2005. Research Interests: Behavioral Neuroscience, Adult Neurogenesis, Hippocampal Circuitry, Stress Biology, and Neuroplasticity. Snyder’s lab investigates how newly generated neurons influence cognition and mood, with recent work highlighting neurogenesis’s role in probabilistic reward learning and future-oriented decision-making. Awards: Michael Smith Foundation for Health Research Scholar Award (2014), Canadian Institutes of Health Research New Investigator Award (2013). Lab and Collaborations: Snyder leads the Snyder Lab at UBC, which develops tools like Pathfinder for spatial navigation analysis. Collaborations include work on transgenic rat models and stress hormone regulation in neurons. His lab actively supervises graduate students and postdocs, with openings starting Fall 2022.

Danny Dyerمشاهده پروفایل

استاد

• Graph Theory
• Combinatorial Designs
• Graph Searching
• +۳ مورد دیگر

Dr. Danny Dyer is a Professor of Mathematics at Memorial University of Newfoundland, where he has been since 2005. He holds a PhD from Simon Fraser University (2004) and a B.Sc. from Memorial University (1998). His research focuses on graph theory, including motion in graphs, cops and robbers games, graph searching, watchman walks, graph decomposition, and labelling problems. He also explores the Scholarship of Teaching and Learning in undergraduate mathematics education. He has received prestigious awards, including the President’s Award for Distinguished Teaching and the Atlantic Universities’ Distinguished Teaching Award. His work bridges theoretical mathematics with educational innovation. Research interests prominently feature graph theory subfields such as pursuit-evasion games, graph labeling strategies, and structural graph analysis. His recent publications explore constrained searching algorithms, extremal graph problems, and applications of combinatorial sequences. Teaching contributions emphasize undergraduate mathematics pedagogy. Key academic milestones include foundational work on zero-forcing sets, eternal domination in graphs, and graceful labeling techniques. His research has been published in over 40 peer-reviewed articles, spanning topics from theoretical graph problems to practical teaching methodologies.

James Ian Munroمشاهده پروفایل

استاد

• Algorithms
• Data Structures
• Theoretical Computer Science
• +۱ مورد دیگر

James Ian Munro is a Professor of Computer Science at the University of Waterloo. His research focuses on algorithms, data structures, and theoretical computer science. He has been recognized with prestigious awards including the ACM Fellow (2008) and Fellowship in the Royal Society of Canada. Education: Earned degrees from the University of British Columbia, University of Toronto, and University of New Brunswick. His doctoral advisor was Allan Borodin. Research Interests: Specializes in succinct data structures, graph algorithms, search trees, and efficient algorithm design. His work emphasizes space-efficient and optimal data representation. Awards: ACM Fellow (2008) for contributions to algorithms and data structures; Royal Society of Canada Fellow. Advising: Supervised numerous doctoral students including Erik Demaine and Venkatesh Raman. His academic lineage spans foundational contributions to theoretical computer science.

• Renal Genetics
• Molecular Biology
• Genetic Diagnosis
• +۵ مورد دیگر

Prof. Daniel Bichet is a Full Professor at the University of Montreal's Faculty of Medicine, affiliated with the Department of Medicine and Department of Pharmacology and Physiology. His research focuses on renal genetics, molecular biology, and genetic disorders of kidney diseases. He specializes in congenital nephrogenic diabetes insipidus, Fabry disease, and molecular mechanisms underlying renal pathologies. He has received the 2018 Émilie Gala's Coup de Coeur award for research excellence. Education: Medical degree from Université de Montréal. Research Interests: Genetic diagnosis of hereditary renal diseases, molecular biology of kidney disorders, and clinical management of Fabry disease. His recent articles emphasize long-term efficacy of migalastat in Fabry nephropathy, consensus guidelines for diabetes insipidus management, and vasopressin receptor pharmacology. He leads the Canadian Fabry Disease Initiative (CFDI) registry, analyzing treatment outcomes in enzyme replacement therapies and pharmacological chaperones. Grants & Awards: CIHR funding for genetic studies, Émilie Gala recognition, and leadership roles in global renal disease registries. Labs/Teams: Active in the Université de Montréal's nephrology research unit, collaborating with international networks like the FollowME Fabry Pathfinders registry.