جست‌وجوی استاد و پژوهشگر

Maryam Mehri Dehnaviمشاهده پروفایل

دانشیار

• High-Performance Computing
• Cloud Computing
• Machine Learning
• +۳ مورد دیگر

Maryam Mehri Dehnavi is an Associate Professor of Computer Science at the University of Toronto and a Principal Research Scientist at NVIDIA. She holds the Canada Research Chair in Parallel and Distributed Computing. Her research group, ParaMathics, focuses on scalable numerical methods, high-performance libraries, and compilers for cloud and parallel computing platforms. Her research interests span cloud computing, machine learning, numerical analysis, and compiler optimization. She has been recognized with awards including the Ontario Early Researcher Award (2021) and an NSF CRII grant. She has advised numerous students, many of whom have achieved notable academic and industry roles. Teaching: Applied Parallel Computing, Parallel Computing, Cloud Computing Leadership Roles: General Chair of PPOPP 2023, Keynote Speaker at SIAM PP 2024 Labs/Teams: ParaMathics Research Group Her work bridges theoretical advances in numerical methods with practical applications in high-performance computing, emphasizing efficiency and scalability across diverse architectures.

Nandita Vijaykumarمشاهده پروفایل

استادیار

• Computer Architecture
• Compilers
• Systems
• +۵ مورد دیگر

Nandita Vijaykumar is an Assistant Professor in the Computer Science Department at the University of Toronto and the Department of Computer and Mathematical Sciences at the University of Toronto Scarborough. She leads the embARC Research Group, affiliated with the Vector Institute and Robotics Institute. Her work focuses on computer architecture, compilers, and systems, with a particular emphasis on the interplay between programming models, systems, and architectures. She holds a Ph.D. and M.S. from Carnegie Mellon University (2019), advised by Prof. Onur Mutlu and Prof. Phil Gibbons. She has held roles at Intel Labs, AMD, Microsoft, and Nvidia, and was a visiting student at ETH Zurich's Systems Group. Her research bridges computer architecture/systems with robotics, computer vision, and deep learning. Key projects include optimizing GPU algorithms, differential privacy in hardware, and 3D neural graphics. She mentors over 30 graduate and undergraduate students across Ph.D., MSc, and internship programs, fostering innovation in distributed systems and machine learning infrastructure. Nandita’s recent publications address challenges in differentiable rendering, distributed robotics, and energy-efficient computing. Her work on frameworks like DPWatch and DiffusionRenderer highlights her contributions to privacy-aware hardware and neural rendering. Collaborations with industry and academic institutions underscore her commitment to practical, cross-disciplinary solutions.

Brendan Freyمشاهده پروفایل

استاد

• Machine Learning
• Bioinformatics
• Genomics
• +۳ مورد دیگر

Brendan Frey is a Professor in the Departments of Communications and Biomedical Engineering at the University of Toronto, cross-appointed in the Banting and Best Department of Medical Research, the Centre for Cellular and Biomolecular Research, and the Department of Computer Science. He holds the Edward S. Rogers Sr. Endowed Chair in Engineering and is a Canada Research Chair (Tier 1). His research focuses on developing machine learning algorithms for addressing challenges in genome biology, including gene expression analysis, alternative splicing inference, and computational modeling of biological systems. Notable contributions include the sum-product algorithm, affinity propagation, and image epitomes techniques. Frey’s awards include the John C Polanyi Award, NSERC Steacie Fellowship, and Fellowships from AAAS and IEEE. He advises six graduate students and two postdoctoral fellows, many of whom have become prominent academics and industry leaders. Education: Studies in Canada, United States, and United Kingdom (specific degrees not listed). Consulting: Technical Advisor to Microsoft Research India and consultant for international companies.

Paul Calamaiمشاهده پروفایل

استاد

• Operations Research
• Nonlinear Optimization
• Bilevel Optimization
• +۵ مورد دیگر

Paul Calamai is a Professor in the Department of Systems Design Engineering at the University of Waterloo, and is affiliated with the Waterloo Institute for Sustainable Energy. His research focuses on resource management, optimization methods, and the integration of operations research with geographical information systems (GIS). He holds a BSc, MSc, and PhD from the University of Waterloo (1977–1983). Research Interests : Bilevel optimization, societal and environmental systems, nonlinear optimization, facility location, and resource allocation. His work emphasizes developing robust decision-support tools for operational strategy analysis in constrained resource environments. Recent Work Trends : His publications from 2005–2011 emphasize multi-objective optimization, evolutionary algorithms, and spatial data modeling. Key themes include dynamic combinatorial problem-solving, ant colony systems, and applications in land-use planning and manufacturing systems. Advising & Grants : Currently accepting graduate applications in optimization and systems design. His research has addressed challenges in bioenergy planning, vehicle routing, and active suspension systems through interdisciplinary collaborations. Labs/Teams : Active within the Waterloo Institute for Sustainable Energy, focusing on bioenergy systems and sustainable resource management strategies.

Elliot Creagerمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Algorithmic Fairness
• +۳ مورد دیگر

Elliot Creager is an Assistant Professor at the University of Waterloo's Faculty of Engineering , Department of Electrical and Computer Engineering. He directs the Socially Embedded Machine Intelligence (SEMI) Lab , focusing on reliable and equitable AI systems that prioritize user data autonomy. His interdisciplinary research bridges technical machine learning with sociology and policy implications, and he actively mentors students across multiple institutions (University of Toronto, York University, Vector Institute). Recent research trends include algorithmic fairness in sequential decision-making, differential privacy applications, and LLM auditing frameworks . Collaborative projects span institutions like University of Toronto, York University, and Vector Institute. His work addresses fluid simulation generalization , invariant learning , and collective action algorithms . Scientific achievements include a CIFAR AI Catalyst Grant (2024) and recognition as NeurIPS 2022 Top Reviewer . As an active Area Chair for ICML 2025 and NeurIPS 2025, he contributes to advancing equitable AI standards. Current advisees include MASc and postdoc researchers, with former students from undergraduate programs.

Jeremy Cooperstockمشاهده پروفایل

استاد

• Human-Computer Interaction
• Haptics
• Multimodal Interfaces
• +۵ مورد دیگر

Jeremy Cooperstock is a Professor in the Department of Electrical & Computer Engineering at McGill University . He directs the Shared Reality Lab and is affiliated with the Centre for Intelligent Machines (CIM) . His research focuses on intelligent systems , haptics , and multimodal interfaces , with applications in accessibility, medical technology, and VR/AR environments. Educational Roles: Teaches courses such as ECSE424/542 (Human-Computer Interaction) and ECSE526 (Artificial Intelligence). Past courses include Embedded Systems and Operating Systems, with notable contributions to curriculum development in systems programming. Research Highlights: Developed Autour and Mimic projects for accessible multimodal interfaces and remote communication. Explores haptic feedback systems for clinical environments, wearable devices, and emergency response. Advances in tactile signal processing, including vibrotactile communication and physiological feedback integration. Labs & Teams: Shared Reality Lab: Focuses on accessible technologies and immersive experiences. CIM collaborations in AI-driven solutions for healthcare and human-computer interaction.

Christophe Dubachمشاهده پروفایل

دانشیار

• Data-Parallel Language Design
• Hardware Design Space Exploration
• Heterogeneous Computing
• +۴ مورد دیگر

Christophe Dubach is an Associate Professor at McGill University, jointly appointed in the Department of Electrical and Computer Engineering (ECE) and the School of Computer Science (CS). He holds a Canada CIFAR AI Chair at Mila. Previously, he was a Reader (Associate Professor) at the University of Edinburgh until 2019. His research focuses on data-parallel language design, high-level code generation for parallel hardware (GPUs/FPGAs), hardware design space exploration, and applying machine learning to these areas. He has advised numerous PhD and MSc students on topics like FPGA-based high-level synthesis, neural networks, and compiler optimization. Education: PhD in Informatics (2009, University of Edinburgh), MSc in Computer Science (2005, EPFL, Switzerland). Teaching includes courses on compiler design, computer organization, and high-level synthesis. His projects include Lift (a functional IR for GPU code generation) and High-Level Synthesis of Neural Networks on FPGAs. Collaborators include Michel Steuwer, Lu Li, and others in the fields of compilers, machine learning, and parallel computing.

Michael Janzenمشاهده پروفایل

دانشیار

• Virtual Camera Selection
• Serious Game Modules
• Camera Trap Image Processing
• +۳ مورد دیگر

Dr. Michael Janzen is an Associate Professor in the Department of Computing Science at The King's University. He holds a PhD from the University of Saskatchewan, an M.Sc. from the University of Guelph, and a B.Sc. from Brock University. His research focuses on virtual camera selection using semi-ring constraint satisfaction problems (SCSPs), serious game modules, and camera trap image processing for ecological studies. His work intersects computer science, environmental monitoring, and AI ethics. Education includes: PhD in Computing Science, University of Saskatchewan M.Sc. in Computer and Information Science, University of Guelph B.Sc. in Computers and Physics, Brock University Research interests emphasize practical applications of AI and computational methods in virtual environments, wildlife monitoring, and educational gaming. Recent projects include developing automated systems for wildlife fence design analysis and image screening tools for ecological data. His work bridges theoretical computer science with real-world challenges in conservation and technology ethics.

Xue Dong Yangمشاهده پروفایل

استاد

• Computer Graphics
• Image Processing
• Visualization

Xue Dong Yang is Professor of Computer Science at University of Regina specializing in computer graphics, image processing, and visualization. Research includes hair modeling, 3D object recognition, and facial recognition systems.

Michael Leblancمشاهده پروفایل

دانشیار

• UI/UX Design
• Web-Based Design
• 3D Design
• +۴ مورد دیگر

Michael Leblanc is an Associate Professor at Nova Scotia College of Art and Design (NSCAD) since 1990, concurrently serving as a Visiting Professor at Foshan University, China. He holds an Hon. BA from the University of Guelph and an MFA from York University, specializing in drawing and printmaking. His academic leadership roles include 15 years as Chair of the Division of Design and two years directing NSCAD's Master of Design program. Education: Hon. BA (University of Guelph), MFA (York University) Research focuses on UI/UX design, web-based systems, and 3D design with a focus on data-driven applications. Collaborative work includes a Mitacs Accelerate grant ($100k) with Saint Mary’s University to address medication adherence in elderly patients through smart home monitoring systems. Prior industry roles include Creative Director positions at Origin BioMed, PhotoPoint, Knowledge House, and ITC Learning. His creative practice spans exhibitions like The Technology of Good Intentions (2013) and the 2016 biography of Canadian War Artist Eric Aldwinckle. Grants: Mitacs Accelerate Grant (2021), Collaborative interdisciplinary healthcare tech project Labs/Teams: Leads NSCAD's interdisciplinary design initiatives with Saint Mary’s University computer science students through grant-funded internships.

• Interactive 3D Graphics
• User Interface Design
• Virtual Environments
• +۵ مورد دیگر

Mark Green is a Professor in the Faculty of Science at Ontario Tech University. His research focuses on human-computer interaction, 3D graphics, and digital media communication. He leads work in light field displays, holography, and graphics hardware design. Education: PhD in Computer Science from the University of Toronto (1985). Research highlights include pioneering Canada's first Virtual Reality (VR) laboratory at the University of Alberta in 1986, which housed the nation's first HMD and CAVE system. He developed the open-source MR Toolkit, distributed globally to thousands of researchers. Current interests span formal design methods for interfaces, authoring tools for virtual environments, and VLSI applications in graphics. No specific grants, advising records, or article lists are detailed in the provided text.

• Computer Science
• Software Systems Development
• Secure Computing
• +۲ مورد دیگر

Quinn Baker serves as Lab Coordinator and Instructor in the Department of Computing Science at The King's University. Their role involves laboratory coordination and teaching across Computing Science programs, including streams such as Software Systems Development, Secure Computing, and Computer Graphics & Visualization. Quinn is reachable at quinn.baker@kingsu.ca .

• Real-time Physics Simulation
• Character Animation
• Computer Science
• +۳ مورد دیگر

Sheldon Andrews is a Professor of Software & IT Engineering at the École de technologie supérieure in Montreal, Canada. His research focuses on real-time physics simulation, character animation, and interactive systems. He specializes in integrating computational methods with visual and haptic feedback, particularly in dynamic environments. Research interests include developing algorithms for realistic simulations, such as friction modeling, texture synthesis, and inverse kinematics. His work bridges computer graphics, robotics, and software engineering, with applications in interactive hand simulation and motion gaming. Notable contributions include papers on fingertip appearance modeling (MIG 2013), Hessian matrix-based kinematics (MIG 2017), and friction-visual coupling (SCA 2021). His open-source projects, such as hessianIK and slrbs , provide tools for academic and industrial use. He maintains an active GitHub repository for research code and collaborates on projects like real-time physics engines and data-driven animation techniques. No academic awards are explicitly listed in the provided texts.

Li Xiمشاهده پروفایل

دانشیار

• Polymer Materials and Manufacturing
• Process Systems Engineering
• Fluid Mechanics
• +۵ مورد دیگر

Dr. Li Xi is an Associate Professor of Chemical Engineering at McMaster University, specializing in multiscale molecular modeling of polymer materials, flow turbulence, and polymer fluid dynamics. His research integrates computational fluid dynamics (CFD) and molecular simulation to address challenges in energy, environment, and biomedical applications. He holds a Ph.D. from the University of Wisconsin-Madison and completed postdoctoral research at MIT, focusing on polymer materials and pharmaceutical manufacturing. Education: Ph.D., Chemical Engineering, University of Wisconsin–Madison (2009) Postdoctoral, Chemical Engineering, MIT (2009–2013) B.S., Chemical Engineering, Zhejiang University (2004) Research Interests: Multiscale modeling of polymer materials for targeted properties Turbulent flow dynamics and drag reduction mechanisms Rheology and polymer processing-structure-property relationships Advanced materials and smart manufacturing systems Labs & Resources: Led research group at McMaster (visit www.xiresearch.org ) Focus areas: polymer materials, process systems engineering, micro-nano systems Teaching: Instructor for CHEM ENG 3D04 (Thermodynamics), CHEM ENG 3L03 (Laboratory Skills), and supervising graduate students

Imran Ahmadمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Dr. Imran Ahmad is a Professor in the School of Computer Science at the University of Windsor. He holds a Ph.D. in Computer Science from Wayne State University (1997), with prior degrees in Applied Physics (Electronics) from Karachi and an M.S. in Computer Science from Michigan. His research focuses on computer vision, machine learning, and image processing, including applications in traffic analysis, generative AI, and medical imaging. He has authored over 50 publications since 1995, with recent work emphasizing deep learning for vehicle detection, human activity recognition, and generative models. Education: B.Sc., M.Sc. in Applied Physics (Electronics) – Karachi M.S. in Computer Science – University of Michigan Ph.D. in Computer Science – Wayne State University, Michigan, USA (1997) Research Interests: Dr. Ahmad’s work bridges theoretical and applied computer science. Key areas include: Advanced computer vision techniques for real-world systems (e.g., traffic monitoring, medical diagnostics) Generative AI for image and video synthesis Deep learning optimization and transfer learning Human activity recognition using stereo trajectories and motion analysis Agent-based simulations for crowd behavior modeling Key Publications Trends (2020–2025): Recent work emphasizes: Generative models for text-to-image/video synthesis Transfer learning for cross-domain image classification 3D trajectory analysis for activity detection Vehicle detection/classification systems Accessibility tools for color vision deficiency