جست‌وجوی استاد و پژوهشگر

Paul McNicholasمشاهده پروفایل

استاد

• Computational Statistics
• Mixture Model-Based Clustering
• Classification
• +۶ مورد دیگر

Paul McNicholas is a Professor in the Department of Mathematics and Statistics at McMaster University, where he holds a Tier 1 Canada Research Chair in Computational Statistics. He serves as Editor-in-Chief of the Journal of Classification and has directed the MacData Institute (2017-2022). His academic leadership extends to his role as Associate Chair of Statistics (2021-2023) and his extensive supervision of graduate students across multiple cohorts. Dr. McNicholas earned his academic credentials from Trinity College Dublin, including a Sc.D. in Statistics, Ph.D. in Statistics, M.Sc. in High Performance Computing, and B.A./M.A. in Mathematics. His educational background reflects the interdisciplinary nature of modern computational statistics, combining deep mathematical knowledge with advanced computational skills essential for contemporary data science. His research focuses on computational statistics, particularly mixture model-based clustering and classification. Current research includes work on non-Gaussian mixtures, matrix variate distributions, and real problems in big data analytics. McNicholas has made significant contributions to developing statistical methods for higher-order data, mixed-type data, and multivariate longitudinal data, with special applications in autism and aging research. His methodological innovations have enabled more sophisticated analysis of complex datasets across various domains, particularly in health sciences. Analysis of his recent publications reveals a strong focus on advancing mixture model methodology for increasingly complex data structures. His work spans theoretical developments in distribution theory, computational algorithms for model fitting, and practical applications in health sciences. A notable trend is the extension of traditional statistical methods to handle high-dimensional, non-Gaussian, and structured data while maintaining computational efficiency, with increasing attention to applications in autism spectrum disorder and aging research. Dr. McNicholas has received numerous prestigious awards recognizing his contributions to statistics: Dorothy Killam Fellowship (2023) John L. Synge Award, Royal Society of Canada (2021) Steacie Prize for the Natural Sciences (2020) E.W.R Steacie Memorial Fellowship (2019) College Member, Royal Society of Canada (2017) University Scholar (2017) Tier 1 Canada Research Chair (2015) Dr. McNicholas actively mentors the next generation of statisticians, currently supervising eight Ph.D. students, a Master's student, and an undergraduate researcher. His research group has secured significant funding through various grants and fellowships, enabling cutting-edge research in computational statistics. He has also contributed to the field through software development, with R packages like 'mixture', 'pgmm', 'CDGHMM', 'longclust', and 'vscc' that implement his methodological innovations and make advanced statistical techniques accessible to practitioners. His research group operates within the broader context of the MacData Institute at McMaster University, which he directed from 2017-2022. The group fosters interdisciplinary collaboration, particularly in applications related to health sciences, including autism spectrum disorder research and aging studies. McNicholas has built a vibrant research community that bridges theoretical statistics with practical applications through regular seminars, workshops, and collaborative projects with researchers across multiple disciplines, with particular emphasis on methodological innovations that address real-world challenges in health analytics.

• Volcanology
• Igneous Petrology
• Glaciovolcanism
• +۳ مورد دیگر

Kelly Russell is a Professor in the Department of Earth, Ocean and Atmospheric Sciences at the University of British Columbia (Vancouver Campus), affiliated with the Faculty of Science. Their research focuses on volcanology, igneous petrology, and glaciovolcanism, with an emphasis on magma transport, mantle dynamics, and paleoenvironmental reconstructions through volcanic systems. Russell leads the Volcanology & Petrology Laboratory at EOS-South 253. Education: Ph.D. in Earth Sciences, University of Calgary, 1984 M.Sc. in Earth Sciences, University of Calgary, 1980 B.Sc. (Honours) in Earth Science, University of Manitoba, 1976 Research Interests: Russell’s work spans three core themes: (1) glaciovolcanism as a paleoenvironmental proxy, (2) melt viscosity modeling for planetary and magmatic systems, and (3) mantle xenolith transport dynamics. Their studies integrate field observations, experimental petrology, and computational models to understand volcanic processes and Earth’s interior. Publication Trends: Recent work explores particle dynamics in magma systems, carbonated mantle lithosphere interactions, and glaciovolcanic reconstruction. Key contributions include the GRD viscosity model and studies on kimberlite volcanism. Awards/Honors: 2023 Alexander von Humboldt Research Award 2022 Elected Member, Academia Europaea 2016 Fellow, Mineralogical Society of America Advising: Russell mentors graduate and undergraduate students on volcanology projects, including glaciovolcanic field studies and magma dynamics modeling. Their team includes postdoctoral fellows and students exploring volcanic hazards and mantle processes. Lab & Collaborations: The Volcanology & Petrology Lab collaborates internationally on projects like glaciovolcanic mapping in the Garibaldi Belt and kimberlite ascent mechanisms. Russell also contributes to the GeoSentinel Program and UBC’s Climate Crisis initiatives.

Nicolas Moitessierمشاهده پروفایل

استاد

• Medicinal Chemistry
• Computer-Aided Drug Design
• Asymmetric Synthesis
• +۱ مورد دیگر

Nicolas Moitessier is a Professor in the Department of Chemistry at McGill University, specializing in computational and experimental approaches to drug discovery. He earned his Maîtrise (1994) and Ph.D. (1998) from the University of Nancy, France, followed by postdoctoral research at the University of Montreal (1998-2000) and a Research Senior position at CNRS Nancy (2001-2003). His research integrates computer-aided drug design with organic synthesis, focusing on developing predictive software platforms (FITTED, IMPACTS, FORECASTER) for drug binding, metabolism prediction, and asymmetric catalyst design. Current projects include covalent inhibitor development for viral proteases and RNA-targeted therapeutics. Professor Moitessier teaches CHEM 222 (Introductory Organic Chemistry 2) and CHEM 552 (Physical Organic Chemistry). His interdisciplinary work bridges chemical biology, catalysis, and computational chemistry to accelerate molecular discovery.

Marcin Sabokمشاهده پروفایل

دانشیار

• Descriptive Set Theory
• Ramsey Theory
• Forcing (Logic)
• +۳ مورد دیگر

Marcin Sabok is an Associate Professor in the Department of Mathematics and Statistics at McGill University, part of the Faculty of Science. His research focuses on descriptive set theory, Ramsey theory, forcing, and their applications in operator algebras and geometric group theory. He co-authored the book *Canonical Ramsey Theory on Polish Spaces* with Vladimir Kanovei and Jindrich Zapletal. Sabok's work bridges foundational mathematics with geometric and algebraic structures, addressing classification problems and structural properties of mathematical objects. His research has been supported by contributions to areas such as Borel combinatorics, ergodic theory, and hyperfiniteness in group actions. Affiliation: Department of Mathematics and Statistics, McGill University Key Research Themes: Set Theory, Geometric Group Theory, Logic, Operator Algebras His recent interests include exploring connections between Ramsey-theoretic methods and operator algebras, as well as studying hyperfinite actions of groups on boundaries in geometric contexts. Sabok has published extensively in top journals like *Inventiones Mathematicae* and *Advances in Mathematics*, contributing to foundational questions in set theory and its applications. While no specific awards are listed, his contributions to descriptive set theory and geometric group theory indicate significant recognition in his field. He collaborates widely, with co-authors including experts in logic, combinatorics, and functional analysis. His academic website provides further details on his research and teaching activities.

• Nuclear Physics
• Laser Spectroscopy
• Penning Trap Mass Spectrometry
• +۳ مورد دیگر

Fritz Buchinger is a Faculty Lecturer in the Department of Physics at McGill University. He holds a Ph.D. from Johannes-Gutenberg-Universität Mainz (1981) and specializes in experimental nuclear physics. His research focuses on fundamental nuclear properties, particularly nuclear masses and charge radii, using techniques including laser spectroscopy and Penning trap mass spectrometry. Dr. Buchinger leads experiments at major facilities including the Canadian Penning Trap at Argonne National Laboratory, TITAN Penning Trap at TRIUMF, and Collinear Laser Spectroscopy Experiment at TRIUMF. His work provides critical data on nuclei far from stability, contributing to our understanding of stellar nucleosynthesis processes and refinement of nuclear models. Research interests span nuclear structure physics, experimental techniques development, and applied physics applications. Current investigations include: Precision mass measurements of neutron-rich nuclides Nuclear charge radii determination via laser spectroscopy Development of advanced ion trap instrumentation Applications in nuclear astrophysics and fundamental symmetries Recent publications demonstrate a consistent focus on advancing mass spectrometry techniques (MR-ToF, PI-ICR) and their application to nuclear structure questions, particularly in the rare-earth region relevant to r-process nucleosynthesis. His work shows growing emphasis on precision measurements for fundamental physics tests.

Jiying Zhaoمشاهده پروفایل

استاد

• Image Processing
• Video Processing
• Multimedia Communications
• +۳ مورد دیگر

Jiying Zhao is a Professor at the School of Electrical Engineering and Computer Science (EECS) at the University of Ottawa. He holds a Ph.D. in Engineering from Keio University (Japan) and multiple engineering degrees from North China Electric Power University (China). His academic career includes roles as an instructor and associate professor at Thompson Rivers University (Canada) before joining the University of Ottawa in 2001, where he advanced to full professor in 2009. Dr. Zhao's research focuses on image/video processing , multimedia communications , and digital watermarking . Notable contributions include advancements in video super-resolution techniques, perceptual quality assessment of stereoscopic images, and robust watermarking algorithms resistant to geometric attacks and compression. His professional affiliations include IEEE, IEICE, and membership in Professional Engineers Ontario. While no specific awards or grants are listed, his extensive publication record demonstrates significant contributions to multimedia and signal processing fields. Advising and student mentorship details are not provided in the available text. Research interests are centered around 3D imaging , haptic communication , and content security , with applications in telepresence systems and video authentication. He maintains an active research website linked to the School of EECS.

Christopher Ferrallمشاهده پروفایل

استاد

• Labour Economics
• Computational Methods
• Econometrics
• +۴ مورد دیگر

Christopher Ferrall is a Professor in the Department of Economics at Queen's University, where he has been since 1990. He also serves as the Academic Director of the Queen's Research Data Centre and previously led the John Deutsch Institute for the Study of Economic Policy (2009–2016). His research focuses on computational methods applied to labour economics, dynamic programming, and structural estimation. Ferrall holds a BA from the University of Wyoming (1984) and a PhD from the University of Minnesota (1990). He has held visiting positions at institutions such as Carnegie Mellon, New York University, and the Norwegian School of Economics. Education: BA Economics & Computer Science (University of Wyoming, 1984); PhD Economics (University of Minnesota, 1990). Research Interests: Labour market dynamics, computational economics, structural estimation, and policy analysis using dynamic programming. Key Contributions: Developed the niqlow software platform for economic model design and estimation, and authored the textbook C4E: Computation for Economists . His publications span topics like unemployment insurance, physician work patterns, and the impact of education quality on labour market outcomes. He has supervised over 20 PhD students, many of whom hold academic or policy roles globally. Ferrall has secured grants totaling millions, including leadership in Canada’s Research Data Centre Network and SSHRC initiatives. His teaching spans advanced econometrics, computational methods, and labour economics at both graduate and undergraduate levels. Grants: Over $30M in funded research, including SSHRC/CIHR initiatives and Canada Foundation for Innovation grants. Administration: Extensive service on university committees, including roles in high-performance computing, graduate programs, and academic review committees. He is affiliated with the Queen’s Research Data Centre and has collaborated with institutions like Statistics Canada and the World Bank. His work bridges theoretical models with practical policy analysis, leveraging computational tools to address complex economic questions.

Pascal Audetمشاهده پروفایل

استاد

• Geophysics
• Seismology
• Plate Tectonics
• +۳ مورد دیگر

Pascal Audet is a Full Professor in the Department of Earth and Environmental Sciences at the University of Ottawa. He holds a BSc from Université de Montréal (2002), an MSc from Université du Québec à Montréal (2004), and a PhD from the University of British Columbia (2008). His research focuses on the rheology, structure, and evolution of the lithosphere, utilizing seismology and potential field analysis. Key themes include subduction zones, the Northern Canadian Cordillera, continental deformation, and planetary lithospheric dynamics. Research interests span geophysics (e.g., seismology, plate tectonics), subduction zone mechanics, and lithospheric structure. His work integrates field studies, computational modeling, and software development (e.g., RfPy, SplitPy) to advance understanding of Earth’s interior. Notable projects include the Western Arctic Regional Network of Seismographs (WARNS) and studies on fluid dynamics in subduction zones. Recent publications highlight advancements in seismic tomography, lithospheric strength, and Arctic tectonics. Audet collaborates globally, contributing to initiatives like the Canadian Cordillera Array and deep learning tools for seismic event detection. His lab, uOttawa Geophysics, fosters interdisciplinary education and geodynamic research.

Alicia Nahmad-Vazquezمشاهده پروفایل

دانشیار

• Digital Fabrication
• Robotic Fabrication
• Architectural Geometry
• +۳ مورد دیگر

Dr. Alicia Nahmad-Vazquez is an Associate Professor of Architecture at the University of Calgary's School of Architecture, Planning, and Landscape (SAPL), where she co-directs the Laboratory for Integrative Design. As a UCalgary Research Excellence Chair, she focuses on bridging robotics, digital fabrication, and traditional building practices to democratize advanced technologies for community empowerment. Her work emphasizes social innovation through participatory design frameworks that integrate technology, architectural geometry, and sustainable construction methods. Affiliations: University of Calgary (SAPL), Laboratory for Integrative Design Roles: Academic, Artist, Entrepreneur (founder of The Circular Factory, MI Toolbox, and Architecture Extrapolated) Her research explores topics such as decentralized manufacturing systems, robotic-assisted fabrication, and community-driven design strategies. She advocates for architecture that prioritizes humanity and sustainable growth, inspired by the vision of cities functioning as nurturing environments. Her entrepreneurial ventures aim to translate academic innovation into real-world applications, such as custom PPE solutions and timber-based micro-factories. Recent publications highlight her focus on human-robot collaboration, multi-objective optimization in facade design, and the integration of advanced materials into construction processes. While specific awards are not listed, her work has garnered international acclaim for its interdisciplinary impact. Dr. Nahmad-Vazquez’s advising and grants reflect her commitment to empowering communities through technology. Her labs and teams, like the Laboratory for Integrative Design, emphasize hands-on experimentation and cross-disciplinary collaboration. She envisions a future where architecture balances technological advancement with social and environmental responsibility.

Maia Fraserمشاهده پروفایل

دانشیار

• Machine Learning
• Computer Vision
• Neuroscience
• +۴ مورد دیگر

Maia Fraser is an Associate Professor in the Department of Mathematics and Statistics at the University of Ottawa. She holds an MSc and PhD from the University of Chicago and a PhD from Stanford University. Her research spans interdisciplinary areas including machine learning, computational neuroscience, and applied mathematics. Notably, she explores the intersection of AI with structural engineering, focusing on automated damage assessment in concrete and neural mechanisms underlying continual learning. Her work also delves into theoretical aspects of contact geometry and reinforcement learning. Her academic contributions include pioneering methods for damage quantification using digital images, theoretical frameworks for temporal abstractions in neural systems, and algorithmic advancements in decision-making under uncertainty. Fraser’s research often bridges abstract mathematical theory with practical applications, such as optimizing nautical navigation and analyzing fish behavior through spatial learning models. Education: MSc in Mathematics, University of Chicago PhD in Mathematics, University of Chicago PhD in Computer Science, Stanford University Fraser’s recent publications highlight advancements in automated assessment techniques for civil infrastructure, the role of temporal hierarchies in neural organization, and foundational work in reinforcement learning theory. Her interdisciplinary approach reflects a commitment to solving complex problems through collaborative, mathematically rigorous methods.

Francesco Gentileمشاهده پروفایل

استادیار

• Computer-Aided Drug Discovery
• Deep Learning in Drug Discovery
• Structure-Based Virtual Screening
• +۳ مورد دیگر

Francesco Gentile is an Assistant Professor in the Department of Chemistry and Biomolecular Sciences at the University of Ottawa, Faculty of Science. His research focuses on computational strategies for drug discovery, leveraging AI and deep learning to accelerate virtual screening and target unconventional drug targets such as protein-protein interactions. He leads the Gentile Lab, which investigates cancer drug resistance and develops tools like DockBox and Deep Docking for structure-based drug discovery. Education: PhD in Computational Physics from the University of Alberta (2014-2019), postdoctoral training at the Vancouver Prostate Centre under Art Cherkasov. Awards include Alberta Innovates Scholarship and CIHR Fellowship. Research interests span AI-driven drug discovery, chemical space exploration, and synergistic therapies for cancer. The lab collaborates with the Ottawa Institute of Systems Biology and AI4Science@uOttawa. Key publications include work on SARS-CoV-2 protease inhibitors, LRRK2 domain targeting, and AI in early-stage drug discovery. Over 20 students and postdocs have been advised, with active projects in PROTAC design and computational modeling. Lab members include postdocs, graduate students, and undergraduates from diverse backgrounds. Current tools developed include Pose Ensemble GNNs and PROTACable pipelines.

Terri Lovellمشاهده پروفایل

استادیار

• Organic Chemistry
• Fluorescence Microscopy
• Chemical Biology
• +۴ مورد دیگر

Terri Lovell is an Assistant Professor in the Department of Chemistry and Biomolecular Sciences at the University of Ottawa, part of the Faculty of Science. Her research focuses on designing fluorophores for biological applications, including super-resolution microscopy and single-molecule imaging. She holds a PhD in Organic Chemistry from the University of Oregon and completed a postdoctoral fellowship in super-resolution microscopy at McGill University. Education: PhD in Chemistry, University of Oregon (2016-2020) NSERC Postdoctoral Fellow, McGill University (2020-2024) MSc in Polymer Science, University of Oregon (2015-2016) BSc in Chemistry, Memorial University of Newfoundland (2011-2015) Research Interests: Dr. Lovell develops fluorophores with enhanced photostability, designs novel fluorescent scaffolds (e.g., nanohoops), and establishes methods for analyzing protein dynamics at the single-molecule level. Her work bridges organic synthesis, computational modeling, and microscopy to advance biological imaging techniques. Recent Work Trends: Her publications emphasize fluorophore design for viral RNA analysis (e.g., SARS-CoV-2), photoprotection strategies for cyanine dyes, and biocompatible nanohoops for live-cell imaging. These studies address critical challenges in high-resolution microscopy and biomedical diagnostics. Awards: Natural Sciences and Engineering Research Council PostDoctoral Fellow Award (2021) Knight Campus Transitioning Scholar Fellowship (2020) Qalipu Mi’kmaq First Nation Band Post-Secondary Support (2015) Lab & Team: The Lovell Lab at the University of Ottawa focuses on advancing fluorophore technology and microscopy methods. Current projects include developing probes for thick-tissue imaging and improving signal-to-background ratios in super-resolution setups. Students and postdocs in the lab work on synthesis, computational modeling, and microscopy applications.

Hua Luمشاهده پروفایل

استاد

• Experimental Mechanics
• Reliability of Structures and Devices
• Solid Mechanics
• +۵ مورد دیگر

Dr. Hua Lu is a Professor in the Department of Mechanical, Industrial, and Mechatronics Engineering at Toronto Metropolitan University. His research focuses on experimental mechanics and reliability analysis of microelectronic packaging and mechatronic systems. He is affiliated with the Laboratory for Experimental Mechanics Research and actively contributes to advancements in thermal-mechanical performance characterization. Education: BSc, Tianjin University, 1968 MSc, Tianjin University, 1982 PhD, Stony Brook University, 1989 Dr. Lu's research interests center on experimental solid mechanics, with emphasis on microelectronic packaging reliability, thermal-mechanical behavior of thin structures, and optical methods for deformation measurement. His work bridges mechanical engineering with electronics manufacturing, focusing on failure prediction and performance optimization of advanced packaging technologies. He applies inverse methods, computer vision, and fiber-optic sensing to real-world reliability challenges in microsystems. The recent publications highlight a strong trend in developing and applying advanced experimental techniques—particularly inverse modeling, optical diagnostics, and sensor integration—to assess reliability in microelectronics. These works span disciplines including mechanical behavior of materials, thermal analysis, and structural health monitoring, with consistent focus on flip-chip and PBGA technologies. Professional Affiliations: Surface Mounting Technology Association (SMTA) International Dr. Lu leads the Laboratory for Experimental Mechanics Research, where experimental techniques are developed and applied to structural and electronic system reliability. While specific grant details and student advising records are not listed, his publication record indicates active research supervision and project leadership in experimental mechanics and microelectronics packaging. His work supports innovation in durable, high-performance electronic systems.

Ahmad Varvani-Farahaniمشاهده پروفایل

استاد

• Fatigue Fracture Analysis
• Cyclic Plasticity and Ratcheting
• Stress Analysis
• +۱۰ مورد دیگر

Ahmad Varvani-Farahani is a Professor in the Department of Mechanical, Industrial, and Mechatronics Engineering at the Faculty of Engineering and Architectural Science, Toronto Metropolitan University. His work focuses on enhancing the structural integrity and safety of mechanical systems in automotive, aerospace, and medical fields through advanced modeling of material failure. Education: BSc in Mechanical Engineering, University of Tabriz (1990) MASc in Mechanical Engineering, University of Waterloo (1994) PhD in Mechanical Engineering, University of Waterloo (1998) His primary research interests include Fatigue Fracture Analysis , Cyclic Plasticity and Ratcheting , Stress and Finite Element Analysis , Composite Materials , and Biomechanics , with applications in durability and risk assessment of engineering components. He also investigates biomaterials, artificial tissues, and implants, bridging mechanical engineering with healthcare innovation. The recent publications reflect a strong trend in developing energy-based and critical-plane models for fatigue and ratcheting under multiaxial and asymmetric loading, particularly in steel alloys and pressurized systems. These works contribute significantly to damage mechanics and structural reliability across industries. No specific scientific awards are mentioned in the provided text. Dr. Varvani-Farahani is actively involved in research supervision and education, teaching advanced courses such as Advanced Fatigue Fracture Analysis , Materials Selection for Engineering Design , and Biomechanics . He leads the Multiaxial Fatigue Research Facilities lab, which develops innovative solutions for challenging engineering problems related to material degradation and failure. His research has practical implications for improving the safety and longevity of critical infrastructure and medical devices.

Snezana Mitrovic Minicمشاهده پروفایل

استاد مدعو

• Operations Research
• Discrete Optimization
• Graph Theory
• +۷ مورد دیگر

Snezana Mitrovic Minic is an Adjunct Professor in the Department of Mathematics at Simon Fraser University, Surrey. She holds a PhD in Computing Science from Simon Fraser University, an MSc in Applied Mathematics from the University of Belgrade, and a BSc in Mathematics from the same institution. PhD : School of Computing Science, Simon Fraser University MSc : Applied Mathematics Program, Faculty of Electrical Engineering, University of Belgrade BSc : Faculty of Mathematics, University of Belgrade Her research lies at the intersection of operations research and applied discrete mathematics, with focus areas including discrete optimization, graph theory, vehicle routing, scheduling, and algorithm design. She has conducted significant research on the dynamic pickup and delivery problem with time windows (PDPTW), contributing benchmark test instances widely useful in algorithmic development. She has collaborated with leading researchers such as Prof. Abraham Punnen, Prof. Peter Borwein, Prof. Gilbert Laporte, Prof. Binay Bhattacharya, and Dr. Emina Krcmar on projects involving integer programming, health care modeling, and heuristic methods in logistics and forestry. Her teaching portfolio includes courses such as MATH 343, MATH 157, CMPT 307, and CMPT 201, covering calculus, discrete mathematics, data structures, and algorithms. Dr. Mitrovic Minic is professionally affiliated with major operations research societies: IFORS (International Federation of Operational Research Societies) CORS (Canadian Operational Research Society) EURO (Association of European Operational Research Societies) EWG Transportation (EURO Working Group on Transportation) INFORMS (Institute for Operations Research and the Management Sciences) She has over ten years of industry experience as a software engineer and analyst in real-time control systems, bridging theoretical research with practical software development. Her academic work is supported by a strong technical background and active participation in the global OR community.