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Oliver SchulteView profile

Professor

• Machine Learning
• Statistical Learning for Relational Databases
• Computational Game Theory
• +4 more

Oliver Schulte is a Professor and School Director at the School of Computing Science, Simon Fraser University. His research focuses on Machine Learning, particularly in relational databases and computational game theory. He holds a Ph.D. from Carnegie Mellon University (1997) and has held academic roles since 1997, including Adjunct Professorships at the University of Alberta. His work includes foundational contributions to learning theory, generative graph models, and sports analytics. Awards include the NSERC Discovery Award and Best Paper Awards in AI conferences. He leads the Structured Machine Learning Lab and collaborates with institutions like SportLogiq. His teaching spans database systems, AI, and societal impacts of technology. Education: Ph.D. (Logic & Computation, CMU, 1997), M.Sc. (CMU, 1993), B.Sc. (Computing Science, U Toronto, 1992). Research Interests: Machine learning for relational data, Bayesian networks, reinforcement learning in sports, computational game theory, and formal epistemology. Recent work includes subgraph prediction, rule-enhanced graph learning, and privacy-aware graph generation. Awards & Grants: Over $500K NSERC Strategic Project Award (2020s), Best Paper Awards, and leadership in grants with industry partners like SportLogiq. His research bridges theory and applications, including hockey analytics and predictive analytics labs.

Edgar JohnView profile

Senior Lecturer

• Computer Science Education
• Algorithms
• Game Design
• +1 more

Edgar John is a Senior Lecturer and Undergrad Program Committee Chair at the School of Computing Science, Simon Fraser University. He holds an M.Sc. in Computing Sciences from Simon Fraser University (1999), a B.Sc. in Psychology from University College London (1984), and is a qualified member of the Institute of Chartered Accountants of England and Wales (1988). His teaching focuses on introductory computing science, programming fundamentals, data structures, algorithms, and database systems. Research interests include algorithm animations and game design. In 2025, he teaches courses such as CMPT 130 (Introduction to Computer Programming I) and CMPT 225 (Data Structures and Programming). Edgar actively contributes to undergraduate education, overseeing program development through his role in the Undergrad Program Committee. He is affiliated with the School's research ecosystem, which includes labs like the Tangent Lab. No specific grants or awards are highlighted in his profile.

Mehdi KargarView profile

Professor

• Computer Science
• Data Management
• Database Systems
• +3 more

Mehdi Kargar is a Professor in the Department of Computer Science at the University of Windsor's Faculty of Engineering. His research focuses on simplifying search through massive datasets, leveraging advancements in data management and structured data analysis. He received a $20,000 NSERC grant in 2017 to support this work. Affiliation: University of Windsor Role: Professor of Computer Science Dr. Kargar's research interests include optimizing search algorithms for large-scale datasets, with applications in database systems and information retrieval. His NSERC-funded project aims to develop methodologies that enhance efficiency and accessibility in handling big data challenges. Grants: NSERC Grant ($20,000, 2017) Advising & Grants: While specific advising details are not provided, his grant-funded research indicates ongoing contributions to computational data science.

Nigel HusseyView profile

Professor

• Marine Biology
• Conservation Physiology
• Aquatic Ecosystems
• +4 more

Professor Nigel Hussey is a Biology faculty member at the University of Windsor's Great Lakes Institute for Environmental Research (GLIER). His research focuses on marine megafauna ecology, animal tracking technology, and Arctic ecosystem conservation. Key areas include Greenland shark behavior, beluga whale migration patterns, and the impacts of climate change on Arctic species. Hussey has pioneered the use of acoustic telemetry and satellite tracking to study species such as narwhals, manta rays, and Greenland halibut. He collaborates with Inuit communities in northern Canada to develop sustainable fisheries practices and advises doctoral students like Eric Ste-Marie and Danielle Orrell. His work emphasizes global data-sharing initiatives to enhance conservation efforts, particularly in understudied regions like the Red Sea and Sudan's coastal waters. Education and professional background: While specific educational details are not provided in the texts, his professorial role implies advanced degrees in marine biology or ecology. His research spans over a decade, with notable contributions to understanding elasmobranch behavior, Arctic food webs, and the effects of anthropogenic pressures on marine life. He has contributed to UNESCO World Heritage Site nominations and published in high-impact journals like Nature . Research labs/teams: Active in GLIER, leading interdisciplinary projects involving acoustic tagging and habitat modeling. Collaborates with institutions worldwide on conservation physiology and marine megafauna tracking. His fieldwork includes Arctic expeditions and deep-sea exploration using submersibles.

• Natural Language Processing
• Machine Learning
• Autobiographical Memory
• +2 more

Claudia Morales Valiente is a Researcher at the University of Alberta working in the Memory for Events Lab, where she applies computational methodologies to investigate autobiographical memory systems through linguistic analysis of personal narratives. Her academic foundation includes: Bachelor of Science in Psychology from the University of Havana, Cuba Master of Science in Psychology from the University of Western Ontario, Canada Doctor of Philosophy in Psychology from the University of Western Ontario, Canada under Dr. Ken McRae Dr. Morales Valiente's research integrates natural language processing with cognitive psychology to decode narrative structures in autobiographical accounts. She specializes in supervised machine learning algorithms, mixed-effects modeling, and hierarchical statistical frameworks to quantify memory representation patterns. Her methodological innovations bridge computational linguistics and experimental psychology, particularly in extracting semantic features from life-story narratives to understand memory organization and retrieval mechanisms. Active in the Memory for Events Lab, she develops open-source analytical tools including lexical property extractors and NLP pipelines for narrative scoring, as evidenced by her GitHub repositories which implement R and Python frameworks for text analysis. Her technical contributions focus on adapting sentiment analysis and word norm databases to psychological research contexts.

Lai-Tze FanView profile

Associate Professor

• Science and Technology Studies
• AI Ethics
• Critical Design
• +5 more

Lai-Tze Fan is an Associate Professor of Technology & Social Change at the University of Waterloo, Canada, cross-appointed between the Department of Sociology & Legal Studies and the Department of English Language and Literature. She holds a Canada Research Chair in Technology and Social Change (Tier 2 SSHRC) and directs The U&AI Lab, which focuses on AI ethics and research-creation methods for equity, diversity, and inclusion (EDI). Additionally, she serves as a visiting Associate Professor II (part-time) at the University of Bergen, Norway, and holds editorial roles at electronic book review and the digital review . Her interdisciplinary work spans Media Studies, Science and Technology Studies, Critical Design, and Digital Humanities, with a focus on AI ethics, gendered design, and digital narratives. She has held academic positions at Lingnan University (Hong Kong), Concordia University (Montréal), and the University of Mainz (Germany). Her research includes projects like the Global Urban Wilds locative media app, exploring environmental storytelling and urban ecology, and the Decameron 2.0 Virtual Gallery , addressing pandemic-era community making. Fan’s awards include the N. Katherine Hayles Award for Criticism and SSHRC grants. Her recent publications address AI equity, gendered technology design, and digital environmental narratives. She actively mentors students in areas like AI ethics, critical design, and electronic literature.

Doug WelchView profile

Professor

• Light Echoes
• Supernovae
• Variable Stars
• +4 more

Doug Welch is a Professor in the Department of Physics and Astronomy at McMaster University and serves as Vice-Provost and Dean of Graduate Studies. He earned his PhD in Astronomy & Astrophysics from the University of Toronto in 1986, followed by postdoctoral work at the Dominion Astrophysical Observatory. His research focuses on light echoes from supernovae/transient events and pulsating variable stars (Cepheids, RR Lyrae, R CrB stars), with collaborations including Armin Rest (STScI), Geoff Clayton, and Patrick Tisserand. Welch's work leverages light echoes to study asymmetry in historical supernovae and stellar eruptions, advancing constraints for computational models. His articles emphasize supernovae, Cepheid variables, and novel light echo methodologies, reflecting trends in time-domain astronomy and precision distance measurements. Awards: McNeil Medal of the Royal Society of Canada (2010) for science communication. He contributes to major observatories as a Board Member of the Canada-France-Hawaii Telescope Corporation and previously served on the Thirty Meter Telescope Board of Governors. Welch co-leads teams in transient surveys and mentors through institutional roles, though specific grants/students are not detailed.

Elena KuzminView profile

Assistant Professor

• Synthetic Biology
• Functional Genomics
• Cancer Genomics
• +5 more

Elena Kuzmin, PhD, is an Assistant Professor in the Department of Biology at Concordia University, Montreal, Canada, where she holds a Canada Research Chair Tier 2 in Synthetic and Functional Genomics. She supervises MSc and PhD students in Biology and teaches courses in Cancer Evolution, Computational Biology, and Genome Evolution. Research Interests Mapping complex genetic interaction networks Cancer genomics and rare genetic diseases Genome evolution and functional genomics Yeast genetics as model systems Systematic genetic screening techniques Single-cell RNA/DNA sequencing applications Recent Article Trends Focus on genotype-phenotype relationships in cancer Development of yeast-based synthetic biology tools Investigations into gene duplication retention mechanisms Exploration of mechanical stress in cellular systems Neurogenomic cross-species comparisons Large-scale genetic network rewiring studies Awards Canada Research Chair Tier 2 in Synthetic and Functional Genomics Labs & Collaborations Kuzmin Lab at Centre for Applied Synthetic Biology Collaborations in biochemistry, cancer research, and neuroscience

William LeslieView profile

Professor

• Osteoporosis
• Bone Densitometry
• Fracture Risk Assessment
• +3 more

Dr. William Leslie is a Professor of Medicine and Radiology at the University of Manitoba , affiliated with the Max Rady College of Medicine . He serves as Founding Director of the Manitoba Bone Mineral Density (BMD) Program and holds cross-appointments in Radiology (Nuclear Medicine) and the Manitoba Centre for Health Policy . His research spans osteoporosis , fracture risk assessment , and artificial intelligence in diagnostics . Doctor of Medicine (University of Manitoba) MSc in Computer Science (University of Manitoba) BSc (Double Honours in Mathematics and Computer Science, University of Manitoba) Residencies in General Internal Medicine and Nuclear Medicine Research Interests Dr. Leslie's work focuses on bone densitometry , nuclear diagnostic techniques , and machine learning applications for fracture risk prediction. He has pioneered the integration of administrative health data with clinical outcomes in the Manitoba BMD program. Scientific Awards International Society for Clinical Densitometry Researcher of the Year (2020) John P. Bilezikian ISCD Global Leadership Award (2017) ASBMR Most Outstanding Clinical Abstract Award (2011) Lindy Fraser Memorial Award (2008)

Pascal TyrrellView profile

Associate Professor

• Biostatistics
• Data Science
• Machine Learning
• +3 more

Pascal Tyrrell is an Associate Professor at the University of Toronto, cross-appointed to the Department of Medical Imaging within the Faculty of Medicine. As Director of Data Science, he focuses on integrating advanced statistical methodologies and machine learning with medical imaging to enhance diagnostic accuracy and healthcare outcomes. Biostatistics Data Science Machine Learning for Medical Images His research investigates guidelines for data quantity and quality in AI-driven medical imaging, emphasizing innovation in computational frameworks and database solutions. The lab he leads explores cutting-edge applications of artificial intelligence in diagnostics, global health equity, and medical device development, aiming to address disparities in healthcare access and improve personalized treatment strategies. Pascal’s work spans AI-powered diagnostics, global health innovation, and medical device development, with a narrative centered on advancing healthcare efficiency and accessibility through technological integration. Administrative roles include Director of Data Science in the Department of Medical Imaging, contributing to interdisciplinary collaboration and research leadership in healthcare technology.

• Computational Terminology
• Natural Language Processing
• Corpus Linguistics
• +4 more

Patrick Drouin is a Professor and Department Director at the Université de Montréal , based in the Faculté des arts et des sciences and the Departement de linguistique et de traduction . His research focuses on computational terminology, corpus linguistics, and the automatic acquisition of specialized lexicons. He leads major projects like the NÉONUM initiative for monitoring Quebec French neology and the Lexique entre humains et machines team exploring human-machine lexical interactions. Teaching: He teaches advanced terminology (TRA-3455), localization workshops (TRA-6301), and directs programs in Linguistics and Translation at both undergraduate and graduate levels. Over 10 PhD and Master's students have been supervised by Drouin since 2007, focusing on topics like semantic shifts, terminological evolution, and corpus-based lexicography. Research Projects: Co-leads interdisciplinary teams funded by FRQSC and SSHRC, including studies on morphophonological variation via Twitter data, transdisciplinary vocabulary for primary education, and the historical analysis of terminology in translation studies. Key contributions include the SyllabO+ corpus and the QC-FR-Diac-V1 semantic shifts dataset. Grants: Secured over CAD 2M in funding for projects like Twitter-MPhon (2021–2025) and Lexiques nucléaires (2019–2025), emphasizing computational methods in linguistic research. Labs/Teams: Active in the Equipe SE (Lexical Studies) and collaborates with institutions like IRIC for biology-informatics interfaces. His work bridges theoretical linguistics with applied technologies for terminology management and language education.

• Renal Genetics
• Molecular Biology
• Genetic Diagnosis
• +5 more

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.

• Rehabilitation Engineering
• Human-Computer Interaction
• Health Informatics
• +7 more

Aaron Tabor is an Assistant Professor at the University of New Brunswick . His research focuses on bridging Human-Computer Interaction (HCI) with Biomedical Engineering and Health Informatics to develop innovative rehabilitation technologies and wellness-oriented systems. Email: q4k8p@unb.ca Office: Room GE109A His work emphasizes inbodied interaction design , which integrates internal physiological processes into technology development. Key areas include breathing exercise systems for ADHD and chronic disease management, EMG feedback for spinal cord injury rehabilitation, and gamification in therapeutic interventions. Research Trends : The provided articles highlight his focus on three domains: (1) gait analysis using underfoot pressure sensors and deep learning, (2) respiratory therapy through biofeedback and idle games, and (3) inbodied interaction frameworks that leverage neuro-physiological pathways for self-tuning systems. These works often intersect machine learning , gamification , and non-invasive physiological monitoring .

• Astrophysics
• Cosmology
• Galaxy Evolution
• +3 more

Karim Tanveer is a Research Fellow at the University of Toronto's Dunlap Institute for Astronomy & Astrophysics and Department of Astronomy & Astrophysics. His work spans cosmology, galaxy evolution, and instrumentation for large-scale surveys like the Dark Energy Spectroscopic Instrument (DESI). Current research focuses on precision cosmology through emission-line galaxies, photometric redshift estimation, and the interstellar medium's dynamics, including Fermi bubbles and galactic nuclear outflows. Key Research Themes: Cosmological parameter estimation via DESI and CMB lensing Galactic nuclear wind and outflow gas mapping Target selection algorithms for spectroscopic instruments UV absorption studies of galactic structures Next-generation infrared surveys like NANCY Instrumentation & Data: He contributes to DESI's large-scale structure catalogs, target pipelines, and data validation processes. His work bridges observational techniques with cosmological constraints, emphasizing systematic error mitigation in parameter inference.

Youcef DerbalView profile

Associate Professor

• Complex Adaptive Systems
• Cancer Modeling
• Machine Learning in Oncology
• +4 more

Dr. Youcef Derbal is an Associate Professor in the Department of Information Technology Management at Toronto Metropolitan University's Ted Rogers School of Information Technology Management. With a Ph.D. in Electrical and Computer Engineering from Queen's University, he brings extensive industry experience from robotics, telecommunications, and software sectors to his academic work. His research focuses on Complex Adaptive Systems, particularly in modeling cancer dynamics through agent-based simulations, machine learning applications for oncology, and computational frameworks for biological processes. Key research areas include tumor dynamics, cell signaling pathways, and tumor-infiltrating lymphocyte recruitment. Dr. Derbal teaches undergraduate courses in business information systems, programming, system analysis, database design, and client-server applications, along with graduate-level advanced project management. His publication record shows consistent output in computational biology, cancer modeling, and grid computing since 2006. Professional affiliations include: Association for Computing Machinery (ACM) Institute of Electrical and Electronics Engineers (IEEE) International Society for Computational Biology (ISCB) Administrative contributions include service on University Senate, chairing multiple departmental committees, leading the Business Technology Management curriculum development (2009-2014), and serving as School Director during 2013/2014.