May Tajima is an Assistant Professor in the Department of Management & Organizational Studies at Western University. She holds a Ph.D. in Management Sciences from the University of Waterloo (1998). Her research focuses on RFID technology applications in supply chains, operations management, and supply chain agility. She teaches courses including Operations Management (as course coordinator) and Statistics at Western's DAN Management program. Teaching Experience: Previously taught at University of Waterloo and Wilfrid Laurier University in areas like Production Management, Operations Research, and Engineering Economics. Industry background includes supply chain analysis at Chesapeake Decision Sciences. Key Research Themes: RFID adoption challenges across industries, technology standardization in pharmaceutical contexts, and strategic supply chain adaptability. Authored five major publications between 2005-2012 and contributed to an engineering economics textbook (2005). Awards: Recognized on University Student Council Teaching Honour Roll (2016) Office: SSC 4415 | Phone: 519-661-2111 x87619
Ming Li is a Professor at the University of Waterloo , holding the Canada Research Chair in Bioinformatics . Affiliated with the David R. Cheriton School of Computer Science , his research spans Bioinformatics , Kolmogorov Complexity , Deep Learning , Natural Language Processing , and Computational Biology . His contact details include office Davis Center 3355 and email mli@uwaterloo.ca . Research Interests include Bioinformatics (protein/antibody sequencing, structure analysis), Deep Learning , Natural Language Processing , Kolmogorov Complexity and Applications , and Algorithms & Complexity (average-case analysis, information distance). Editorial Roles : Co-Managing Editor of the Journal of Bioinformatics and Computational Biology , Associate Editor-in-Chief for Journal of Computer Science and Technology , Editorial board member of multiple journals including SIAM Journal on Computing and Information and Computation . Professional Activities : Served on scientific advisory committees for Genome Prairie and Tsinghua University, and numerous international conference program committees (e.g., KDD 2007, CPM 2007, FOCS'99). Awards & Honors : Killam Prize (2010) IEEE Granular Computing Outstanding Contribution Award (2010) Premier's Discovery Award (2009) Fellow of Royal Society of Canada, ACM, and IEEE (2006) Killam Fellowship (2001) E.W.R. Steacie Memorial Fellowship (1996) Multiple Best Paper Awards Students & Postdocs : Mentored over 30 graduate students and postdocs, including current advisees Guangyu Feng, Anqi Cui, and alumni like Babak Alipanahi, Xin Chen, and Brona Brejova.
Dr. Mohsen Yoosefzadeh Najafabadi is an Assistant Professor in the Department of Plant Agriculture at the University of Guelph, Ontario Agricultural College. He holds a PhD in Plant Breeding from the University of Guelph (2022), following M.Sc. and B.Sc. degrees from the University of Tehran. His research focuses on dry bean breeding, computational biology, and integrating omics technologies to enhance crop resilience and productivity. Key areas include developing stress-tolerant dry bean varieties, leveraging remote sensing for trait prediction, and optimizing genomic selection methods. He leads the Dry Bean Breeding & Computational Biology Program and has contributed to over 30 peer-reviewed publications since 2017. Education : PhD, Plant Breeding, University of Guelph (2022) M.Sc., University of Tehran B.Sc., University of Tehran Research interests emphasize computational tools development (e.g., AllInOne preprocessing framework), omics-based selection strategies, and non-Mendelian heredity mechanisms. His lab combines machine learning with field phenotyping to address agricultural challenges such as disease resistance and climate adaptation. Collaborative projects include soybean cold stress analysis and cannabinoid profile prediction in cannabis. Publications span genomic approaches to crop improvement, remote sensing applications, and transcriptomic studies. He teaches courses in plant breeding methodologies and actively engages in technology transfer initiatives. Lab activities include developing high-yielding dry bean cultivars resistant to biotic/abiotic stresses and advancing data-driven pipelines for crop breeding. Future work aims to synergize AI with multi-omics data to enhance crop resilience in diverse environments.
David Churchill is an Associate Professor in the Department of Computer Science at Memorial University of Newfoundland (MUN), specializing in Artificial Intelligence and Real-Time Strategy (RTS) Game AI. He holds a PhD from the University of Alberta and has been actively involved in AI research since 2009. His work focuses on AI for RTS games like StarCraft, emphasizing heuristic search, combat simulation, and build order optimization. He organizes the annual AIIDE StarCraft AI Competition and maintains open-source projects like UAlbertaBot and SparCraft. Education: BSc in Pure Mathematics and Computer Science (MUN) MSc in Computer Science (MUN, 2009) PhD in Computing Science (University of Alberta, 2016) Research Interests: AI in video games, heuristic search algorithms, RTS game strategies, multi-agent systems, and robotics. His work bridges theoretical AI with practical applications in competitive gaming and robotics. Publications & Awards: Notable contributions include Search Ordering for StarCraft Build Order Optimization (2024) and Hierarchical Portfolio Search in Prismata (2017, Best Student Paper Award). His research has advanced combat simulation (SparCraft) and build-order planning (BOSS) in RTS games. Awards: Best Student Paper Award (2017) Best Paper Award (2013, 2022) Advising & Labs: Supervised over 20 graduate and undergraduate theses at MUN. Leads the StarCraft AI Competition and contributes to open-source projects like UAlbertaBot and STARTcraft. Currently not accepting new graduate students due to funding constraints.
Jonn Axsen is a Professor in the School of Resource & Environmental Management at Simon Fraser University (SFU), where he directs the Sustainable Transportation Research Team (START). With an academic career focused on mitigating transportation emissions, he bridges individual decision-making, social systems, technology, and public policy to advance sustainable mobility solutions. BBA, Business Administration (First Class Honours), Simon Fraser University MRM, Resource Management, Simon Fraser University PhD, Transportation Technology and Policy, University of California, Davis His research identifies solutions for decarbonizing road transportation, examining electric vehicles, alternative mobility systems, and policy frameworks. He emphasizes interdisciplinary approaches to understand consumer behavior, organizational transitions, and policy effectiveness in achieving zero-emissions vehicle adoption. Recent publications focus on policy mixes for ZEV adoption, automobility reduction, and consumer perceptions of emerging mobility technologies. Key trends include analyzing subsidy effectiveness, automaker responses to regulation, and cross-cultural differences in mobility preferences. His work appears in top venues like Nature Climate Change and Transportation Research Part D . Royal Society of Canada Fellow (2021) International Transport Forum Award (2012) Securing $2M+ in grants from SSHRC, Translink, Tesla, and PICS, Axsen collaborates with organizations including the UN, Transport Canada, and environmental NGOs. He serves as Senior Associate Editor for Energy Research & Social Science and sits on the US National Academies’ Transportation Research Board. The START team at SFU conducts applied research on sustainable transportation, integrating stakeholder insights with academic rigor. Axsen's lab focuses on bridging technical and social dimensions of mobility transitions through mixed-method studies.
David Eaton is a Professor and former NSERC/Chevron Industrial Research Chair in Microseismic System Dynamics at the University of Calgary's Department of Geoscience. He holds a PhD in Geophysics from the University of Calgary (1992) and has published the textbook 'Passive Seismic Monitoring of Induced Seismicity'. Educational Background: PhD Geophysics, University of Calgary, 1992 MSc Geophysics, University of Calgary, 1988 BSc Geology and Physics, Queen's University, 1984 His research focuses on induced seismicity characterization, microseismic monitoring technology development, distributed acoustic sensing applications, physics-informed machine learning approaches, and lithospheric structure analysis. Current projects investigate earthquake triggering mechanisms during hydraulic fracturing and geothermal energy development. Publications show consistent focus on induced seismicity source characterization, monitoring methodologies, and geophysical applications for energy resource development. Recent work integrates machine learning with seismic monitoring to understand geological controls on induced seismicity. Scientific Awards: NSERC Synergy Award for Innovation (2020) J. Tuzo Wilson Medal, Canadian Geophysical Union (2020) CSEG Distinguished Lecturer (2019) Schulich School of Engineering Distinguished Collaborator (2019) University of Calgary Great Supervisor Award (2016) He leads the CREATE-REDEVELOP program training future leaders in responsible resource development and directs the microseismic research laboratory.
Dominik Roeser is a Professor and Associate Dean of Research Forests & Community Outreach at the University of British Columbia's Faculty of Forestry, Department of Forest Resources Management. With over 21 years of experience in forest research and innovation, he has built a comprehensive forest operations research program since joining UBC in 2018, following his tenure as Senior Director at FPInnovations where he managed multidisciplinary teams focused on improving forest sector competitiveness and wildfire management solutions in Western Canada. Professor Roeser's research interests center on sustainable forest management and the bioeconomy, with specific expertise in forest bioproduction, supply chain design, steep slope harvesting, and biomass operations. His work through the Forest Action Lab applies diverse research methods including productivity studies, field trials, and modeling to address sustainability challenges across different operational environments. His research portfolio spans sustainable forest biomass utilization, harvesting in difficult terrain, innovative forest planning tools, operational productivity, carbon management, and community sustainability impacts from reforestation. His publication record shows a strong focus on practical applications of forest science, with recent work emphasizing wildfire management, remote sensing technologies for precision forestry, biomass energy systems, and the socio-ecological dimensions of forest management. His research increasingly integrates advanced technologies like LiDAR and drone-based systems with traditional forest operations to address contemporary challenges in sustainable forest management. Roeser has received the Recognition Award from the Canadian Forest Service (2017) for his contributions to forest science and innovation. His work demonstrates significant impact on both academic understanding and practical implementation of sustainable forest operations across North America and Europe. As an educator, Professor Roeser teaches several key courses including FOPR 264 Introduction to Forest Operations, FOPR 362 Harvesting systems and forest access, FOPR 464 Operational planning and management, and FRST 452 Coastal field school. He considers educating the next generation of forestry professionals one of his passions, bridging theoretical knowledge with practical industry applications. The Forest Action Lab, led by Professor Roeser, represents a multidisciplinary research hub applying diverse methodologies to address forestry stakeholders' needs across British Columbia, Canada, and globally. The lab's work connects academic research with industry implementation, focusing on practical solutions for sustainable forest utilization in varied operational environments.
Paul Wiegert is a Full Professor in the Department of Physics and Astronomy at the University of Western Ontario , where he has been since 1996 after positions at York University and Queen's University. He is a member of the Institute for Earth and Space Exploration (IESX) and the Centre for Planetary Science and Exploration (CPSX) . His research spans asteroid dynamics , exoplanet systems , and celestial mechanics , with notable work on Earth co-orbital asteroids like (3753) Cruithne and Earth's first Trojan asteroid 2010 TK7. Education : PhD in Astronomy (University of Toronto, 1996) Research Domains : Planetary Science, Astronomy, Big Data Analytics His recent publications focus on interstellar transport mechanisms , asteroid impact risks , and exomoon detection . Key findings include quantifying risks from asteroid 2024 YR4's potential lunar impact and demonstrating the feasibility of detecting alpha Centauri-origin material in our solar system. He actively supervises graduate students like Cole Gregg and participates in NSERC-funded summer research programs for undergraduates. For planetary defense, he has analyzed collision probabilities for Apophis and developed meteoroid hazard models for spacecraft. His work appears in Planetary Science Journal , Nature Astronomy , and Astrophysical Journal Letters , with media coverage in 60+ outlets and 126 X (Twitter) mentions .
Eldan Cohen serves as an Assistant Professor of Industrial Engineering within the Department of Mechanical & Industrial Engineering at the University of Toronto's Faculty of Applied Science and Engineering. His academic journey includes a PhD from the same department followed by a postdoctoral fellowship in Computer Science at the University of Toronto and the Vector Institute for Artificial Intelligence. His educational background is detailed as follows: PhD in Mechanical & Industrial Engineering, University of Toronto Postdoctoral Fellowship in Computer Science, University of Toronto and Vector Institute for Artificial Intelligence Dr. Cohen's research centers on machine learning, deep learning, heuristic search, and optimization with strong emphasis on interpretable and human-compatible AI systems. His work bridges theoretical advancements with practical applications in healthcare (e.g., patient-physician interaction analysis, surgical safety diagnostics), automated planning, natural language processing, and software engineering. Recent projects develop interpretable clustering methods for medical data and optimization techniques for constrained sequence generation. Analysis of his 2023-2025 publications reveals a concentrated focus on healthcare AI applications, particularly using large language models for clinical text analysis and diagnostic support systems. Significant work also addresses interpretable machine learning for medical imaging, diverse plan selection in optimization, and constrained sequence generation in domains like vehicle routing. No major scientific awards or fellowships are documented in the available information. As an academic advisor, Dr. Cohen mentors graduate students in mechanical and industrial engineering, guiding research in optimization and machine learning. His OptiMaL research group fosters collaboration between computer science and industrial engineering to solve real-world decision-making challenges through human-centered AI approaches. The Optimization and Machine Learning (OptiMaL) research group, led by Dr. Cohen, serves as the primary hub for developing scalable, interpretable AI solutions for complex healthcare, planning, and engineering problems, with active projects in medical diagnostics and automated planning systems.
Tao Huan is an Associate Professor in the Department of Chemistry , University of British Columbia , and holds the Canada Research Chair in Metabolomics and Exposomics . His research focuses on advancing mass spectrometry (MS) for metabolomics , integrating bioinformatics to address challenges in cancer metabolism , disease biomarker discovery , and exposome characterization . Education: Ph.D. in Analytical Chemistry (University of Alberta, 2015), Postdoctoral Research Associate (The Scripps Research Institute, 2015-2018). Dr. Huan’s work emphasizes systems biology , combining metabolomics with genomics and proteomics to decode complex biological mechanisms. He has pioneered methods for chemical isotope labeling and multimodal data integration , enhancing metabolite identification and pathway analysis. His recent publications (2020-2019) highlight innovations in LC-MS/MS workflows , freeze-thaw sample stability , and applications in colorectal cancer and Alzheimer’s disease . Dr. Huan’s lab actively recruits students and postdocs in analytical chemistry, metabolomics, and bioinformatics. Awards: Fred Beamish Award (2025), President’s Award, Metabolomics Society (2025), UBC Killam Faculty Research Award (2024), Michael Smith Health Research BC Scholar Award (2023). He serves as a faculty member in UBC’s Graduate Program in Bioinformatics , Genome Science and Technology , and the Cluster for Microplastics, Health and Environment . Lab alumni include Ph.D. and M.Sc. students now in academia and industry.
Dr. Keivan Ahmadi is an Associate Professor in the Department of Mechanical Engineering at the University of Victoria (UVic), serving as Graduate Program Director. He holds a PhD from the University of Waterloo (2012), followed by postdoctoral positions at UBC and Pratt & Whitney Canada. His research focuses on dynamics and vibrations in machining processes, robotic manufacturing, and advanced manufacturing systems. Education: BSc (Tehran Polytechnic), MSc (IUST), PhD (Waterloo) Affiliations: Dynamics and Digital Manufacturing Lab (DDML), UVic Mechanical Engineering Research interests include vibration suppression in machining, chatter prediction, robotic milling dynamics, and high-speed manufacturing systems. His work combines experimental modal analysis, Bayesian modeling, and data-driven approaches to enhance manufacturing precision and sustainability. Key projects include vibration compensation in 3D printing, dynamic modeling of robotic arms for milling, and optimization of thin-walled structure machining. Over 20 peer-reviewed articles showcase his contributions to machining stability, FRF estimation, and additive manufacturing. Advised 19 graduate students (9 alumni, 10 current) Collaborations with industries like GM, Linamar, and CanEV Labs/Teams: Leads the Dynamics and Digital Manufacturing Lab (DDML), focused on sustainable manufacturing through dynamic systems innovation. Hosts a diverse team prioritizing underrepresented groups in engineering.
Aurélie Labbe is a Full Professor in the Department of Decision Sciences at HEC Montréal, holding the prestigious FRQ-IVADO Chair in Data Science. Appointed as Co-Scientific Director – Academic Partnerships at IVADO in October 2023, she plays a key leadership role in establishing connections between IVADO and partner universities. Her academic journey includes a PhD in Statistics from the University of Waterloo, a Master's degree in Statistics from the University of Montreal, and dual Bachelor's degrees in Applied Mathematics and Social Sciences from Paris-Dauphine University and Pure Mathematics from Versailles-St Quentin University. Her research spans multiple interdisciplinary domains with a focus on developing advanced statistical and machine learning methodologies for big data analysis. Labbe's work bridges theoretical statistics with practical applications across diverse fields including genomics, neuroscience, transportation systems, and health informatics. She has made significant contributions to kernel methods, matrix factorization techniques, random forest applications, and spatiotemporal data analysis, with publications appearing in top journals across multiple disciplines. Analyzing her recent publications reveals a clear trend toward methodological innovation applied to complex real-world problems. Her work demonstrates expertise in handling high-dimensional data from diverse sources including neuroimaging, transportation networks, and genomic studies. The interdisciplinary nature of her research connects statistical theory with applications in healthcare, transportation safety, and biological sciences, reflecting her ability to develop methods that address domain-specific challenges while advancing statistical methodology. Holder of the FRQ-IVADO Chair in Data Science Member of the Center for Mathematical Research Training Professor Labbe actively mentors the next generation of data scientists, supervising numerous doctoral and master's students. Her supervision portfolio includes 1 doctoral thesis (2023), 4 master's theses (2022-2024), and 32 supervised projects spanning 2019-2025. Her students' work covers diverse applications including transportation safety, healthcare analytics, financial modeling, and environmental analysis. Through her leadership of the FRQ-IVADO Chair in Data Science, she coordinates research activities that integrate mathematical, statistical, and computer science expertise with domain knowledge from various data-generating fields. As Co-Scientific Director at IVADO, Professor Labbe leads efforts to establish connections with faculties and departments across five partner universities, integrating them into IVADO's research and knowledge transfer activities. Her leadership role positions her at the forefront of advancing data science research and applications in Quebec's academic ecosystem.
Dr. Eunice Eunhee Jang is a Professor in the Department of Applied Psychology and Human Development at the Ontario Institute for Studies in Education (OISE), University of Toronto. Her research focuses on synergistic learner modeling, dynamic assessment systems, and the intersection of language testing with educational measurement. PhD with specializations in language testing, educational measurement, and program evaluation Develops interactive digital assessment interfaces for struggling readers Author of "Focus on Assessment" (2014) and co-author of OECD Reviews on Evaluation and Assessment in Education Research Interests Dr. Jang's work explores prismatic assessment analytics to understand learner potential and predict learning pathways. She integrates natural language processing and machine learning to create diagnostic feedback systems that support cognitive, metacognitive, and affective growth in technology-rich classrooms. Scientific Awards Jacqueline Ross TOEFL Dissertation Award Caroline Clapham IELTS Master’s Award Tatsuoka Measurement Award Professional Contributions She has served on major advisory boards including EQAO provincial assessments and TOEFL Committees of Examiners. Currently, she is an elected board member for the International Language Testing Association and contributes to the Broader Measures of Success Advisory Committee for People for Education.
Azadeh Tabiban is an Assistant Professor in the Department of Computer Science at the University of Manitoba, leading the FOCUS research lab. She specializes in cybersecurity with a focus on cloud/edge security, network security, and applying machine learning to security challenges. Her work emphasizes practical solutions for real-world systems, including provenance analysis, forensics, and securing smart grids and 5G networks. Education: PhD from Concordia University (supervised by Prof. Lingyu Wang and Prof. Makan Pourzandi), followed by a postdoctoral fellowship at the University of Waterloo collaborating with Ericsson Montreal. Previously involved in the NSERC/Ericsson IRC in SDN/NFV Security Project. Research Interests: Building scalable security technologies for transparency and trustworthiness in computing systems. Key areas include provenance systems, cloud/NFV security, smart grid cybersecurity, and AI-driven security solutions. Recent projects include URGP-funded work on AI-based intrusion detection and NCC-supported 5G security collaborations with Ericsson and other universities. Awards and Grants: NSERC Discovery Grant (2024), University Research Grants Program (URGP) (2025), National Cybersecurity Consortium (NCC) Grant (2023), and Best Paper Candidate at CNS'20. Active in securing industrial partnerships and government-funded initiatives. Advising and Training: Supervises PhD and MSc students in system security and machine learning applications. Offers funded positions prioritizing underrepresented groups. Mentors undergraduate students interested in programming and practical cybersecurity solutions. Labs/Teams: Leads the FOCUS lab focused on foundational and operational cybersecurity research. Collaborates with industry partners like Ericsson and academic institutions including Waterloo and Concordia.
Dr. Darren Scott is a Professor in the School of Earth, Environment & Society at McMaster University, specializing in Geographic Information Science (GIScience) and teaching courses such as GIS Programming and Data Processing Using Python. He previously served as an Assistant Professor at the University of Louisville’s Department of Geography and Geosciences (1999–2002) and held a Visiting Research Professor position at the Swiss Federal Institute of Technology (Zurich) in 2008. His academic background includes a BA (Honors and Co-op) in Geography from Saint Mary’s University (1991), an MA from the University of Western Ontario (1994), and a PhD from McMaster University (2000). Dr. Scott’s research focuses on transportation systems, aging populations, GIScience innovations, and sustainable infrastructure. He has pioneered work in route choice modeling, transportation demand analysis, and the impact of demographic changes on mobility. In 2008, he established TransLAB, a research lab within his school, which explores advanced transportation topics using GPS and geospatial tools. His projects have been funded by major agencies like NSF, SSHRC, and NSERC, addressing issues ranging from electric vehicle adoption to flood resilience in emergency services. His teaching emphasizes Python programming and advanced GIS applications, reflecting his expertise in geospatial technologies. He has contributed to policy debates on urban sustainability, particularly regarding Canada’s Greenbelt legislation and telework trends during the pandemic. Despite no explicitly mentioned scientific awards, his extensive grant history and scholarly output highlight his impactful contributions to the field. Dr. Scott’s advising and grant activities center on interdisciplinary studies, including the McMaster Monitoring My Mobility Study (MacM3), which tracks mobility patterns of older adults. His work bridges transportation engineering, urban planning, and public health, often leveraging big data and GIS tools to analyze real-world scenarios in cities like Hamilton and Calgary.
