جست‌وجوی استاد و پژوهشگر

Jay Werberمشاهده پروفایل

استادیار

• Membrane Separations
• Water Treatment and Desalination
• Sustainable Resource Management
• +۳ مورد دیگر

Jay Werber serves as Assistant Professor in the Department of Chemical Engineering & Applied Chemistry at the University of Toronto's Faculty of Applied Science and Engineering. His research group develops advanced membrane materials and separation processes targeting sustainability challenges in water scarcity, CO2 management, and metal recycling, with active projects including Enhanced Reverse Osmosis for High-Salinity Brines and Ion-Selective Electrodialysis for Battery Recycling. Education: B.Sc. from Washington University in St. Louis M.Sc. and Ph.D. from Yale University Postdoctoral training at the University of Minnesota Research Focus: Dr. Werber's work integrates polymer synthesis , transport phenomena , and process design to create breakthrough membranes. His group specializes in fundamental studies of polymeric desalination membranes, next-generation synthesis techniques, and lab-scale demonstrations for applications ranging from water treatment to critical mineral recovery. Key innovations include self-driving labs for membrane fabrication and biomimetic approaches inspired by natural water channels. Publication Trends: Recent work (2018-2023) shows increasing emphasis on data-driven membrane characterization , block polymer engineering , and ion-selective separations . Publications reveal a strategic shift toward computational methods (e.g., Monte Carlo simulations) and industrial scalability, with growing applications in battery recycling and high-salinity wastewater treatment. Scientific Recognition: Young Membrane Scientist Award (North American Membrane Society, 2021) Abel Wolman Fellowship (AWWA, 2017) Ellen Gonter Award (ACS Environmental Chemistry, 2017) NSF Graduate Research Fellowship (2013) Academic Leadership: Dr. Werber mentors PhD and MASc students in the Advanced Membranes Lab, emphasizing collaborative culture and real-world impact. His group maintains active industry partnerships through the Institute for Water Innovation and participates in the Acceleration Consortium for self-driving lab development. Current recruitment focuses on candidates with leadership experience and passion for sustainability challenges. Research Infrastructure: The Advanced Membranes (AM) Lab operates as a core unit within U of T's Institute for Water Innovation, housing specialized equipment for membrane synthesis, transport characterization, and process optimization. Current initiatives include two self-driving labs for automated membrane fabrication (porous membranes and interfacial polymerization) developed in collaboration with Prof. Jason Hattrick-Simpers' materials science group.

• Neuroimaging
• Neurodegenerative Diseases
• Alzheimer's Disease Research
• +۵ مورد دیگر

D. Louis Collins is a Professor at the Montreal Neurological Institute, McGill University, specializing in advanced neuroimaging techniques for neurodegenerative diseases. His research spans Alzheimer's disease, Parkinson's disease, frontotemporal dementia, and autism spectrum disorders, with emphasis on quantitative MRI analysis, biomarker development, and computational modeling of disease progression. His research focuses on: Development of automated tools for hippocampal-ventricle ratio analysis and brain age prediction Mechanistic studies of tau and amyloid pathology in Alzheimer's disease progression Neuroanatomical mapping of genetic frontotemporal lobar degeneration Early biomarker discovery in pediatric neurodevelopmental disorders Methodological innovations in MRI-ultrasound co-registration and template construction Analysis of his 15 most recent publications reveals dominant themes in Alzheimer's disease biomarker validation (40%), Parkinson's disease neurodegeneration (20%), neurodevelopmental disorder imaging (15%), and methodological advances in neuroimaging (25%). His work frequently appears in high-impact neurology journals with strong clinical translation focus. Professor Collins actively contributes to national imaging guidelines through the CCNA Imaging Workgroup and has developed significant neuroimaging resources including the FinnBrain neonatal atlas and MRI-ultrasound co-registration databases. His research bridges computational neuroscience with clinical neurology, emphasizing practical applications for disease diagnosis and monitoring. Current projects include optimizing clinical trial designs for Alzheimer's therapeutics using simulation-based power analysis, repurposing clinical MRI archives for multiple sclerosis research, and developing sex-specific biomarkers for neurodegenerative diseases. His lab maintains strong collaborations with national and international consortia focused on neurodegenerative and neurodevelopmental disorders.

• Concurrent Systems
• Performance Analysis
• Parallel Algorithms
• +۳ مورد دیگر

Naama Ben-David serves as an Assistant Professor at the Technion - Israel Institute of Technology, specializing in theoretical foundations for concurrent computing systems. Her work bridges theoretical rigor with practical performance optimization in parallel programming environments. Her academic journey includes: Undergraduate studies at the University of Toronto PhD in Computer Science from Carnegie Mellon University (advised by Guy Blelloch) Three-year postdoctoral research position at VMware Research Research focuses on identifying performance bottlenecks in concurrent programs through mathematical modeling and algorithmic analysis. She develops frameworks for quantifying synchronization costs while exploring novel concurrent data structures and distributed algorithm design. Her methodology emphasizes formal verification of performance guarantees in real-world systems. Major recognitions include: 2022 PODC Doctoral Dissertation Award CMU School of Computer Science Dissertation Award Honorable Mention NSERC PGSD scholarship during doctoral studies Microsoft Research PhD Fellowship Her doctoral research at Carnegie Mellon was fully funded through competitive fellowships, with dissertation work receiving dual institutional recognition. Current research continues this focus on performance modeling while expanding into practical implementations of theoretically sound concurrent systems.

Jean-Marc Frayretمشاهده پروفایل

استاد

• Logistics
• Production management
• Operational research
• +۷ مورد دیگر

Jean-Marc Frayret is a Full Professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal, where he has established himself as a leading researcher in supply chain management, logistics, and industrial ecology. His academic credentials include an Ing. from ESB (France), an M.Sc. from Laval University, and a Ph.D. from Laval University. He maintains active research affiliations with multiple centers including CIRRELT (interuniversity research center on enterprise networks, logistics and transportation), CIRODD (interdisciplinary research center on sustainable development operationalization), GMT (research group on technology management and globalization), and IVADO (data valorization institute). Professor Frayret's research focuses on decision support systems for operations management and value chain networks, with particular emphasis on agent-based information systems, electronic business processes, and collaborative decision-making in production networks. His work spans both theoretical and applied domains, with significant applications in the forest products industry, circular economy, and sustainable resource management. His research interests include Logistics, Production Management, Operational Research, Industry 4.0, Industrial Ecology, and Agent-Based Simulation. His publication record demonstrates consistent scholarly output with numerous articles in top journals across operations research, supply chain management, and industrial ecology. His research trajectory shows increasing focus on sustainability applications, with recent work exploring industrial symbiosis, waste management, and circular economy models. His publications often combine methodological advances in optimization and simulation with practical industrial applications. 2013 NSERC Brockhouse Award for interdisciplinary research (with the FORAC research team) Teaching Scholarship of the Québec Ministry of Education (2009-2014) Second Best Student Paper Award (2008) Second Best Student Paper Award (2007) Méritas Best Teacher Award from École Polytechnique de Montréal (2006-2007) Professor Frayret has supervised numerous graduate students through completion of their theses, including 8 doctoral students and 23 master's students. His research has been supported by various funding agencies including NSERC, MITACS, and FQRNT, as well as industry partnerships with organizations like FPInnovations, Bombardier, and Air Canada. His current research projects span industrial ecology applications, healthcare operations, sustainable freight transportation, and supply chain collaborative planning in the aerospace industry.

• Corporate Governance
• Mergers and Acquisitions
• Corporate Culture
• +۳ مورد دیگر

Kai Li is a Professor at the Finance Division of the Sauder School of Business, University of British Columbia. Holding prestigious titles such as Fellow of the Royal Society of Canada, Canada Research Chair in Corporate Governance, and W. Maurice Young Endowed Chair in Finance, Dr. Li contributes extensively to research in corporate governance, mergers and acquisitions, corporate culture, and innovation. Education: BSc (Jiaotong University), MA (Concordia), PhD (Toronto) Dr. Li's research explores the intersection of corporate governance mechanisms with finance, emphasizing gender dynamics, machine learning applications, and environmental sustainability. Her work includes studies on gender diversity in corporate settings and the integration of AI in analyzing corporate culture and climate risk. Recent publications highlight trends in gender and finance, corporate culture measurement using machine learning, and climate-related financial innovations. Dr. Li's influence extends to editorial roles in journals like the Journal of Financial and Quantitative Analysis and recognition through awards such as the UBC Killam Research Award and Sauder Research Excellence Award. Scientific Awards: UBC Killam Research Award Sauder Research Excellence Award (junior and senior) Barclays Global Investors Canada Research Award Senior Fellow, Asian Bureau of Finance and Economic Research Research Member, European Corporate Governance Institute Research Fellow, FinTech at Cornell Initiative Dr. Li's contributions to finance include groundbreaking work on corporate culture analysis, gender effects in financial performance, and sustainable finance instruments. As Managing Editor of the Journal of Financial and Quantitative Analysis , she plays a pivotal role in advancing financial research.

Faraz Hachمشاهده پروفایل

دانشیار

• Computational Genomics
• Cancer Research
• Biomolecular Sequence Analysis
• +۳ مورد دیگر

Dr. Faraz Hach is an Associate Professor in the Faculty of Medicine at the University of British Columbia, with a primary appointment in the Department of Urologic Sciences. He is also a Senior Research Scientist at the Vancouver Prostate Centre located at Vancouver General Hospital. His research bridges computational algorithm design with biological problems in precision medicine, with a special focus on cancer genomics. Dr. Hach received his B.Sc. in Computer Engineering from Sharif University of Technology in Iran, followed by M.Sc. and Ph.D. degrees in Computing Science from Simon Fraser University, Canada. His doctoral work was recognized with the Governor General's Gold Medal for the best doctoral thesis at Simon Fraser University in 2014. Dr. Hach's research focuses on computational genomics and biomolecular sequence analysis, particularly in the context of cancer. His lab develops novel high-performance algorithms for analyzing large, high-dimensional omics data produced by next-generation sequencing technologies. Current research directions include: Designing combinatorial algorithms for analyzing genomic structural variations and segmental duplications Developing computational methods for detecting aberrations in tissue and liquid biopsies to understand clonal evolution in cancer genomes Creating data structures and algorithms for compressing large quantities of sequencing data Working on standardization of genomic data formats through involvement with the MPEG-ISO sub-committee Dr. Hach's publications demonstrate a strong trend toward developing computational tools that address specific challenges in cancer genomics and precision medicine. His work spans from fundamental algorithm development to clinical applications, with a particular emphasis on creating tools that improve sensitivity and accuracy while maintaining computational efficiency. Many of his recent publications focus on single-cell analysis, transcriptomic long-read sequencing, and structural variant detection in cancer genomes. Dr. Hach has received several prestigious awards for his work, including: The Ian Lawson Van Toch Memorial Award for an outstanding paper at the 20th Annual International Conference on Intelligent Systems for Molecular Biology The Governor General's Gold Medal for the best doctoral thesis award from Simon Fraser University in 2014 Dr. Hach is actively involved in several major research consortia including the International Cancer Genome Consortium (ICGC) and the ICGC-TCGA Pan Cancer Analysis of Whole Genomes (PCAWG). His earlier work on NGS mappings has been extensively used in the detection of copy number and structural variations in the 1000 Genome Project. He maintains an active research lab that develops numerous open-source software tools for genomic analysis, including Freddie, TKSM, scTagger, Genion, CircMiner, and HASLR. Dr. Hach is available for graduate student supervision, with opportunities for M.Sc., PhD, PostDoc, and intern positions in his lab. His research has significant interdisciplinary components, bridging computer science, genomics, and clinical medicine.

Pierre Dutilleulمشاهده پروفایل

استاد

• Environment
• Ecology
• Agriculture
• +۷ مورد دیگر

Pierre Dutilleul is a Professor at McGill University's Macdonald Campus, associated with the McGill School of Environment and the Department of Mathematics and Statistics. His research focuses on spatio-temporal heterogeneity, plant and soil imaging, and fractal analysis of natural structures. Current affiliations: Department of Plant Science, McGill School of Environment Specializations: CT scanning for root and wood imaging, multifractal analysis, soil aggregate dynamics Research interests span environmental sustainability , soil science , and plant production , with recent work on 3D root phenotyping, biochar characterization, and space-time modeling of agricultural and seismic events. Articles demonstrate expertise in applied statistics and computational methods for ecological and agricultural systems. Key methodological contributions include: Development of R packages for spatio-temporal analysis Innovative CT scanning applications in plant and soil research Statistical tests for separable variance-covariance structures

Heng-Yong Nieمشاهده پروفایل

استاد مدعو

• Analytical Chemistry
• Surface Chemistry
• Materials Science
• +۶ مورد دیگر

Dr. Heng-Yong Nie is a Senior Research Scientist and Adjunct Research Professor in the Department of Physics and Astronomy at Western University. His work bridges analytical chemistry, surface science, and materials engineering through advanced characterization techniques. Research Focus : Surface chemistry, soft materials, and hybrid organic-inorganic systems Key Techniques : ToF-SIMS, AFM, XPS, and laser-based diagnostics Applications : Organic electronics, biomedical devices, corrosion protection, and automotive coatings Recent publications reveal a strong emphasis on: Advanced characterization of surface interactions using mass spectrometry and microscopy Development of novel analytical approaches for nanomaterials and polymer systems Surface engineering for enhanced material stability and performance Applications in biomedical materials, energy systems, and industrial diagnostics Scientific contributions include: Over 20 publications in high-impact journals since 2005 Innovative methods for surface modification and analysis Interdisciplinary work spanning chemistry, physics, and engineering

Chris Hopkinsonمشاهده پروفایل

استاد

• Remote Sensing
• Lidar Technology
• Environmental Monitoring
• +۴ مورد دیگر

Chris Hopkinson holds the Campus Alberta Innovates Program (CAIP) Research Chair in Terrestrial Ecosystems Remote Sensing, a position he has maintained since 2013 following a visiting scientist role at Australia's CSIRO and leadership of lidar research at Nova Scotia's Applied Geomatics Research Group. His work bridges engineering and geography to advance environmental monitoring through cutting-edge remote sensing technologies. His research spans mountain hydrology, water resources, and lidar applications across geosciences, with recent emphasis on integrating in situ and remote sensing data to study glacial dynamics, permafrost thaw, and carbon cycling in forest ecosystems. He provides critical guidance on lidar best practices for government agencies and serves on executive committees in Canada and the US, focusing on appropriate technology deployment for environmental assessment. Analysis of his 15 most recent publications (2024-2025) reveals dominant themes in boreal ecosystem monitoring, particularly wildfire impacts on carbon stocks, wetland hydrology under climate change, and multi-sensor data fusion techniques. His work increasingly leverages deep learning for lidar processing while maintaining field validation as a cornerstone of methodology. Awards: Campus Alberta Innovates Program (CAIP) Research Chair Dr. Hopkinson actively mentors graduate students (evidenced by recruitment announcements) and secures research funding through competitive grants, including his CAIP chair which supports collaborative projects across Canada and internationally. His team develops novel workflows for lidar-based carbon assessment and ecosystem monitoring, with strong emphasis on practical applications for natural resource management. Previously leading the Canadian Consortium for Lidar Environmental Applications Research (C-CLEAR), he now maintains a global network of collaborators advancing terrestrial remote sensing through field campaigns, algorithm development, and policy-relevant science addressing climate change impacts on critical ecosystems.

Clark Verbruggeمشاهده پروفایل

دانشیار

• Computer Science
• Artificial Intelligence
• Algorithms and Data Structures
• +۳ مورد دیگر

Clark Verbrugge serves as an associate professor within the School of Computer Science at McGill University, focusing on computational research and academic instruction. His research spans core computer science domains including Artificial Intelligence, Algorithms and Data Structures, Programming Languages, Software Engineering, and Data Science, emphasizing theoretical and applied computational methodologies. No scientific awards or publications are detailed in the provided text excerpt. Advising activities, grants, laboratory affiliations, or collaborative teams are not referenced in the available information.

Matt Davisonمشاهده پروفایل

استاد

• Financial Mathematics
• Commodity Finance
• Financial Wellness
• +۹ مورد دیگر

Matthew Davison is a distinguished academic serving as Dean of Science at the University of Western Ontario. Holding a PhD from the same institution, his career spans multiple disciplines including financial mathematics, stochastic control, and renewable energy systems. As a Professor in the Department of Statistical and Actuarial Sciences, he leads research initiatives at the intersection of mathematics and finance. Key research areas include commodity finance, stochastic optimal control, and financial wellness Supervises graduate students in mathematical finance and data science Active in cross-departmental collaborations with Engineering and Energy Systems His scholarly work examines: Energy production optimization with production constraints Renewable energy project valuation with real options Robust portfolio construction in stochastic environments Mathematical properties of mean-reverting processes Applications of Hidden Markov Models in financial contexts Recent publications demonstrate a strong focus on energy systems, risk management, and financial optimization. He has contributed to advancements in: Commodity pricing under uncertainty Energy storage arbitrage strategies Stochastic process inference with change points Financial applications of Laplace transforms Smart meter data analysis with privacy preservation As Dean of Science, he oversees one of Western University's largest faculties while maintaining an active research program.

Jiandong Renمشاهده پروفایل

استاد

• Actuarial Science
• Risk Management
• Insurance

Jiandong Ren is a Professor and Acting Department Chair in the Department of Statistical and Actuarial Sciences at Western University. He holds a Ph.D. from Temple University (2003) and leads research in actuarial science, risk management, and insurance mathematics. His core research explores: Credibility theory and fuzzy logic applications in insurance Multivariate risk modeling and dependence structures Compound distributions and simulation methods Pareto-optimal reinsurance contract design Tail risk evaluation for extreme events Recent publications (2020-2024) demonstrate a strong focus on advanced statistical methods for insurance applications, including generalized Poisson models, risk constraint optimization, and catastrophe risk quantification. His work consistently appears in top actuarial journals like ASTIN Bulletin and Insurance: Mathematics and Economics . He actively supervises graduate students including Shiva Mehdipour Ghobadlou and Safoora Zarei.

Daniel Aloiseمشاهده پروفایل

استاد

• Operations Research
• Data Mining
• Machine Learning
• +۵ مورد دیگر

Daniel Aloise is a Full Professor at the Department of Computer Engineering and Software Engineering at Polytechnique Montréal since 2016. He also holds an Assistant Professor position at Universidade Federal do Rio Grande do Norte, Brazil, since 2009. Aloise earned his Ph.D. in Applied Mathematics from Polytechnique Montréal in 2009 under Pierre Hansen, focusing on exact methods for minimum sum-of-squares clustering (k-means). His research spans data mining, machine learning, optimization, and mathematical programming. Education : Ph.D. (Polytechnique Montréal), M.Sc. (Pontifical Catholic University of Rio de Janeiro), B.Eng. (Universidade Federal do Rio Grande do Norte). Affiliations : Canada Excellence Research Chair in Data Science for Real-Time Decision-Making; Member of GERAD (Group for Research in Decision Analysis). His research bridges optimization techniques with real-time data science challenges, producing impactful work in clustering algorithms, wireless signal prediction, and humanitarian logistics. Recent projects include HurricaneLog for disaster response data collection and novel methods for optimizing bike-sharing systems. Aloise's work frequently appears in leading journals like INFORMS Journal on Computing and IEEE Transactions . Scientific honors include: Canada Excellence Research Chair in Data Science for Real-Time Decision-Making GERAD membership Aloise has supervised 7 Ph.D. and 12 Master’s students at Polytechnique Montréal, focusing on topics like bug deduplication, 3D mapping optimization, and personnel scheduling. His methodological contributions include variable neighborhood search heuristics and Lagrangian-based constraint analysis.

Michel Desmaraisمشاهده پروفایل

استاد

• Artificial Intelligence
• Cognitive Modeling
• Human Factors Engineering
• +۵ مورد دیگر

Michel Desmarais is a Full Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montreal since 2002. He has established himself as a prominent researcher in the fields of Artificial Intelligence, Cognitive Modeling, and Educational Data Mining. His work bridges the gap between human factors engineering and advanced computational techniques, with a strong focus on practical applications in learning environments and software systems. Dr. Desmarais holds a Ph.D. in Psychology from the University of Montreal. Prior to joining Polytechnique Montreal, he spent ten years at the Montreal Computer Research Institute (CRIM) as scientific lead of a research team, followed by management and R&D positions in a private firm specializing in Web applications. His interdisciplinary background spanning psychology and computer science has informed his unique approach to human-centered AI systems. Professor Desmarais' research focuses on applying artificial intelligence techniques to educational contexts, with particular expertise in cognitive modeling, knowledge representation, and recommender systems. His work in educational data mining has significantly contributed to understanding how students learn through technology-mediated environments. He has developed innovative approaches for short answer grading using sentence similarity, knowledge tracing, and Q-matrix refinement. His research also extends to human factors engineering, where he examines how intelligent systems can be designed to better align with human cognitive processes. His recent publications demonstrate a clear trajectory toward leveraging advanced AI techniques, particularly large language models and deep learning, to solve complex problems in software engineering and education. The recurring themes across his work include expertise modeling, latent dimension analysis, and the development of adaptive learning environments that respond to individual learner needs. Professor Desmarais has been editor of the Journal of Educational Data Mining from 2013 to 2017 and remains highly involved in both the Educational Data Mining and User Modeling research communities. His leadership in these fields is reflected in his numerous collaborations and his role as a sought-after expert, as evidenced by media appearances such as his commentary on Google's inner workings in La Presse+ in 2018. He has supervised 11 Ph.D. students and 24 Master's students, mentoring the next generation of researchers in AI and educational technology. His students have pursued diverse research topics including technology-mediated peer instruction, latent dimension analysis, video interaction patterns in MOOCs, knowledge tracing, and recommender systems. Professor Desmarais is affiliated with the Institute for Data Valorization (IVADO) as a Member and with LAMA-WeST (Web, Semantics and Text) as a Collaborating member. These affiliations reflect his commitment to interdisciplinary research that bridges computer science, cognitive science, and practical applications in information systems.

• Computer Science
• Artificial Intelligence
• Data Structures
• +۳ مورد دیگر

Dr. Qixiang Pang serves as an Adjunct Professor in the Department of Computer Science at Lakehead University, Thunder Bay, Ontario. His research interests span foundational areas of computer science including algorithms, data structures, software engineering, and artificial intelligence. Contact: Email: qpang@lakeheadu.ca