جستجوی استاد راهنمای دانشگاهی

• Virtual Reality
• Human-Computer Interaction
• Computer Vision
• +۴ مورد دیگر

Robert S. Allison is a Professor in the Department of Electrical Engineering & Computer Science at York University's Lassonde School of Engineering. His research focuses on human perceptual responses in virtual environments, stereoscopic vision, and eye movement analysis. He is affiliated with the York Centre for Vision Research, Sensorium (Digital Arts & Technology), and the Centre for Innovation in Computing at Lassonde. His research interests include depth perception in natural and virtual environments, human-computer interface design for VR, machine vision applications, and the measurement of human motion. He has supervised multiple graduate students and contributed to over 260 publications. His work spans topics like cybersickness mitigation, display lag effects, and perceptual adaptation in VR. Key grants include NSERC-funded projects on perception in virtual environments and collaborations with institutions like the Australian Research Council. His teaching includes courses on human perception in human-computer interaction and digital logic design. Recent articles highlight advancements in understanding motion perception, VR-induced sickness, and multisensory integration. He collaborates widely, with affiliations including the VISTA program and York's Connected Minds initiative.

Ruth Urnerمشاهده پروفایل

دانشیار

• Machine Learning Theory
• Adversarial Robustness
• Algorithmic Fairness
• +۴ مورد دیگر

Ruth Urner is an Associate Professor in the Department of Electrical Engineering and Computer Science at York University's Lassonde School of Engineering. She holds a PhD in Computer Science from the University of Waterloo (2013) and completed postdoctoral research at Max Planck Institute for Intelligent Systems (Germany), Carnegie Mellon University, and Georgia Tech. She was a Simons-Berkeley Fellow at the Simons Institute in 2017. Research Focus: Dr. Urner develops mathematical foundations for machine learning paradigms including semi-supervised/active learning, transfer learning, and adversarial robustness. Her current work addresses societal impacts of ML through interpretability and fairness frameworks. She leads projects on strategic classification, robust PAC learning, and calibrated model evaluation. Awards & Leadership: Simons-Berkeley Fellowship (2017) Best Paper Award at NIPS 2015 Workshop on Transfer Learning Organizer: Women in Machine Learning Theory workshops (COLT/ALT) Program Committee: NeurIPS, ICML, COLT, ICLR, AISTATS Teaching & Advising: She teaches Machine Learning Theory, Computational Logic, and Introduction to ML at York University. Current student advisees include Master's candidate Alireza Torabian. She has lectured at international summer schools including Hausdorff School on Algorithmic Data Analysis (Germany) and SMILES Summer School (Russia). Affiliations: Faculty affiliate at Vector Institute (Toronto) and collaborator with Max Planck Institute systems. Her lab investigates theoretical guarantees for learning algorithms under distribution shifts and adversarial conditions.

Xujie Siمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Software Engineering
• +۵ مورد دیگر

Xujie Si is an Assistant Professor in the Department of Computer Science at the University of Toronto. He is also a faculty affiliate at the Vector Institute and an affiliate member at Mila - Quebec AI Institute, holding a Canada CIFAR AI Chair. Previously, he served as an Assistant Professor at McGill University's School of Computer Science. Education: Ph.D., Computer and Information Science, University of Pennsylvania (advised by Mayur Naik) M.S., Computer Science, Vanderbilt University B.E. (with Honors), Nankai University Research Focus: His work bridges AI and program reasoning, emphasizing the integration of statistical and logical methods. Key areas include: Static analysis and verification using deep learning/reinforcement learning Neuro-symbolic systems for urban simulation (e.g., LogiCity) Automated theorem proving via LLMs and symbolic reasoning Program repair and compiler fuzzing Recent Article Trends: Recent work focuses on synergizing LLMs with symbolic reasoning (e.g., Olympiad inequality proving), advancing SAT solving with graph neural networks, and applying neuro-symbolic methods to Euclidean geometry formalization. Awards: Canada CIFAR AI Chair (2023) Lab/Teams: Leads research teams exploring program analysis, neuro-symbolic AI, and formal verification at the University of Toronto and Vector Institute.

Brian Surgenorمشاهده پروفایل

استاد

• Mechanical Engineering
• Machine Vision Systems
• Autonomous Vehicles
• +۳ مورد دیگر

Professor Brian Surgenor is a faculty member at Queen's University's Department of Mechanical and Materials Engineering, part of the Smith Engineering faculty. He holds a B.Sc. (1977), M.Eng. (AECL/Whiteshell), and Ph.D. (1983) in Mechanical Engineering from Queen's University. His research focuses on machine vision systems for automation, autonomous vehicle navigation, and mechatronic system design education. He has held key administrative roles including Department Head (1993-2002), Associate Dean (2008-2013), and Vice-Dean (2013-2016). His work emphasizes interdisciplinary innovation, such as the Mitchell Hall design project and contributions to Ingenuity Labs. Education: B.Sc. Mechanical Engineering, Queen's University (1977) M.Eng. Engineering Physics, McMaster University (AECL/Whiteshell) Ph.D. Mechanical Engineering, Queen's University (1983) Research interests include: - Pneumatic servosystems - Intelligent algorithms for machine vision - Off-road autonomous vehicle systems - Mechatronics education methodologies - Hybrid powertrain systems for vehicles His recent publications (2017–2024) explore autonomous systems, machine vision applications, and fuel cell hybrid technologies. Notable trends include advancements in UAV-based infrastructure inspection, terrain-adaptive autonomous driving, and low-cost machine vision solutions for small part sorting. His work bridges theoretical control systems with practical industrial automation challenges. He has contributed to laboratory design for CDIO curricula and pioneered mechatronics education through problem-based learning. His administrative leadership has shaped Queen's engineering graduate programs and research infrastructure. Currently involved in Ingenuity Labs, fostering cross-disciplinary innovation.

Angelica Limمشاهده پروفایل

استادیار

• Human Robot Interaction
• Affective Computing
• Multimodal Perception and Learning
• +۶ مورد دیگر

Angelica Lim is an Assistant Professor of Professional Practice and Rajan Family Scholar in the School of Computing Science at Simon Fraser University. Her research focuses on Human Robot Interaction, Affective Computing, and Multimodal Perception with applications in healthcare and developmental robotics. She holds a PhD in Informatics from Kyoto University (2014), an M.Sc. from Kyoto University (2012), and a B.Sc. in Computing Science from SFU (2008). Her work bridges robotics and human-centered AI through projects like the ROSIE Lab, exploring emotion-aware systems, socially assistive robots, and VR programs for aging populations. Key contributions include benchmarking emotional speech recognition (BERSting), developing embodied emotion models for robots, and co-designing healthcare technologies with patient partners. Recent publications emphasize ethical AI, multimodal perception systems, and human-robot collaboration in dynamic environments. Teaching includes courses on software engineering, artificial intelligence, and introductory computer science. Her research has been applied in dementia care through VR programs, robotic companionship for older adults, and emotion-aware human-robot communication systems. Current initiatives focus on inclusive HRI design and sim2real methodologies for underrepresented data in affective computing.

Stephen Brownمشاهده پروفایل

استاد

• Field-Programmable Gate Arrays (FPGAs)
• Computer Architecture
• CAD Algorithms
• +۴ مورد دیگر

Stephen Brown is a Professor at the University of Toronto within the Department of Electrical and Computer Engineering under the Faculty of Applied Science and Engineering. He earned his B.A.Sc and M.A.Sc in Electrical Engineering from the University of Toronto and New Brunswick, respectively, and a Ph.D. in Electrical Engineering from the University of Toronto (1992). His career spans over two decades in academia and industry collaboration. Education : B.A.Sc, University of New Brunswick M.A.Sc, University of Toronto Ph.D, University of Toronto Professor Brown’s research focuses on field-programmable gate arrays (FPGAs) , CAD algorithms , and computer architecture , with applications in machine learning and high-level synthesis . He is a principal investigator in the LegUp project , an open-source high-level synthesis framework that bridges software and hardware design. His work also extends to optimizing FPGA interconnect delays, physical synthesis, and logic block architectures. Key trends in his publications include advancements in high-level synthesis tools, FPGA architecture evaluation, and timing-driven design methodologies. His contributions often intersect with design automation , resource sharing , and embedded systems . Scientific Awards : NSERC 1992 Doctoral Prize Hart Professorship for Innovation in Teaching (2017) Multiple teaching excellence awards Best Paper Award at ICCAD 1990 Best Paper Award nomination at Canadian Conference on VLSI (1989) As Director of the FPGA University Program at Intel Corporation, he leads industry-academia initiatives. His teaching portfolio includes courses like ECE253 (Digital Logic) and ECE1733F (Switching Theory).

Chitra Ranganمشاهده پروفایل

استاد

• Quantum Control
• Nanoplasmonics
• Light-Matter Interactions
• +۳ مورد دیگر

Dr. Chitra Rangan is a Professor in the Department of Physics at the University of Windsor and serves as the Associate Dean of the Faculty of Graduate Studies. She holds cross-appointments in Chemistry and Biochemistry (2008–2011) and has been a Visiting Associate Professor at the University of Michigan (2006–present). Her research focuses on quantum control, nanoplasmonics, and light-matter interactions, with applications in clinical diagnostics and quantum computing. She leads the BiopSys NSERC Strategic Network and contributes to Mathematics of Information Technology and Complex Systems (MITACS) . Education: Ph.D. in Physics, Louisiana State University (2000) M.Sc., Indian Institute of Technology, Madras (1993) B.Sc., University of Madras (1991) Affiliations: Ontario Physics Education Network (PI) NSERC Evaluation Committee (2018) International Day of Light Steering Committee (2018) Her research interests span quantum control theory, nanoplasmonic biosensors, and optimization in medical physics. She has advised over 40 students, many of whom pursue advanced degrees or careers in academia and industry. Notable grants include NSERC, CFI, and Mitacs funding. Publications highlight advancements in quantum state initialization, nanoplasmonic sensor design, and trapped-ion qubit control. Awards include the CAP Medal for Teaching and UWindsor Research Excellence (Emerging Scholars). Dr. Rangan actively promotes science outreach, organizing events like Science Rendezvous Windsor and delivering public lectures on quantum mechanics and medical physics. She has mentored dozens of students through co-op programs and summer projects, emphasizing hands-on learning and interdisciplinary collaboration.

Trevor Barnesمشاهده پروفایل

استاد

• Economic Geography
• Political Ecology
• Urban Studies
• +۸ مورد دیگر

Trevor Barnes is a Professor in the Department of Geography at the University of British Columbia (UBC), with affiliations to the Faculty of Arts and the Science and Technology Studies program. His work bridges historical geography, economic geography, and critical political ecology, focusing on the intersections of capitalism, colonialism, and spatial governance. Education: PhD in Geography, University of Minnesota (1983) MA in Geography, University of Minnesota BSc in Economics, University College London His research spans Cold War geographies, the role of geographers in intelligence work, colonial and capitalist environmental impacts, and the critical analysis of market-driven approaches to biodiversity. Recent publications examine ideological landscapes, pragmatist economic geography, and the legacies of influential geographers like Cole Harris and David Lowenthal. Key trends in his work include: Analysis of capitalist spatial practices in environmental governance Historical connections between academic disciplines and military-industrial complexes Decolonial approaches to knowledge production and land politics Critical engagement with GIS and big data in Cold War contexts Scientific awards include: Distinguished University Scholar Fellow of the Royal Society of Canada Fellow of the British Academy Barnes has supervised numerous doctoral students, including Max Cohen (PhD Geography, 2024, on Marx’s suppressed theory of history). His collaborations with scholars like Eric Sheppard and Brett Christophers have produced foundational texts on radical geography and economic theory. His fieldwork and archival research inform comparative studies of urban governance, including climate policy in Durban and Portland, and the socioecological impacts of infrastructure projects like the Trans Mountain Pipeline.

Ridha Khedriمشاهده پروفایل

استاد

• Cybersecurity
• Formal Methods in Software Engineering
• Information Security Ontology
• +۶ مورد دیگر

Ridha Khedri is a Professor in the Department of Computing and Software at McMaster University . His research spans formal methods in software engineering, cybersecurity, information security ontology, network segmentation, and covert channels analysis. Full Professor since 2000 Contact: khedri@mcmaster.ca Research Interests : Prof. Khedri develops algebraic frameworks for software security, with recent work on network segmentation , ontology engineering , and covert channel detection . His interdisciplinary efforts include hybrid machine learning-ontology models for environmental predictions (e.g., river ice breakup) and digital twin healthcare systems . Article Trends : His 15 most recent works (2016-2025) focus on network security , knowledge representation , and formal verification . Notable trends include automated security testing , ontology modularization , and multi-context reasoning systems . Teaching : He has taught courses like Software Design (CAS 703), Discrete Mathematics (SFWRENG 2DM3), and Algebraic Methods in Software Engineering (CAS 738) since 2017.

Daniel Royمشاهده پروفایل

استاد

• Machine Learning
• Statistical Learning Theory
• Foundations of Statistics
• +۱۱ مورد دیگر

Daniel Roy is a Full Professor at the University of Toronto, holding cross-appointments in the Department of Statistical Sciences, Computer Science, Electrical and Computer Engineering, and the Department of Computer and Mathematical Sciences at UTSC. He is also a Canada CIFAR AI Chair and Research Director at the Vector Institute, reflecting his leadership in AI and machine learning research. His educational background includes a PhD, MEng, and BSc in Computer Science from MIT, where his doctoral work earned the MIT EECS Sprowls Award. Prior to joining Toronto, he was a Newton International Fellow at the Royal Society and a Research Fellow at Emmanuel College, University of Cambridge. His research centers on foundational principles in machine learning, statistics, and probabilistic reasoning. Key interests include statistical learning theory, Bayesian nonparametrics, probabilistic programming, and information-theoretic generalization. His work bridges theoretical computer science, mathematical logic, and applied probability. His recent publications, appearing in ICML, NeurIPS, COLT, and JMLR, reflect a strong focus on theoretical advances in generalization, online learning, and stochastic optimization. Themes include minimax rates, conditional mutual information, and the role of data in PAC-Bayes bounds. His group has made foundational contributions to probabilistic programming, including work on Church and the computability of conditional probability. NSERC Discovery Accelerator Supplement Ontario Early Researcher Award Google Faculty Research Award Newton International Fellowship MIT EECS Sprowls Award Daniel Roy advises numerous PhD students and postdoctoral researchers, many of whom have gone on to prestigious positions in academia and industry. His group actively collaborates with leading researchers in machine learning and statistics. He is also an Action Editor for the Journal of Machine Learning Research and Transactions of Machine Learning Research, underscoring his role in shaping the field. He leads a vibrant research group focused on theoretical machine learning and probabilistic modeling, and maintains active collaborations with institutions such as MIT, Cambridge, and the Vector Institute. He is also the founder and maintainer of the probabilistic-programming.org wiki, a key resource in the community.

Joseph Emersonمشاهده پروفایل

دانشیار

• Quantum Information Processing
• Foundations of Quantum Theory
• Quantum Computing
• +۳ مورد دیگر

Joseph Emerson is an Associate Professor at the University of Waterloo's Department of Applied Mathematics and a faculty member at the Institute for Quantum Computing (IQC). He is also a Fellow of CIFAR's Quantum Information Science program and CEO of Quantum Benchmark, a startup specializing in quantum computing error diagnostics. His research focuses on scalable quantum error correction, foundational quantum theory, and protocols like randomized benchmarking, now a global standard for quantum gate characterization. Emerson earned a BSc from McGill University, an MSc in experimental nuclear physics, and a PhD in theoretical physics from Simon Fraser University. His postdoctoral work at MIT and the Perimeter Institute explored quantum randomness and decoherence. He has held roles at IQC since 2005, advancing quantum computing's practical implementation through error suppression and validation techniques. Research Highlights Developed randomized benchmarking for error diagnostics across quantum platforms. Framework for unitary t-designs applied to quantum algorithms and thermodynamics. Investigated contextuality in quantum mechanics as a computational resource. Awards & Recognition Early Researcher Award (Ontario, 2008–2013) CIFAR Quantum Information Science Fellow NSERC Postdoctoral Fellowship (2003–2005) Labs & Affiliations Emerson leads research teams at IQC and collaborates with Perimeter Institute and industry partners. His work bridges theoretical foundations with practical tools for quantum computing scalability.

• Cell division
• Stem cell biology
• Germline stem cells
• +۵ مورد دیگر

Jean-Claude Labbé is Full Professor in the Department of Pathology and Cell Biology, Faculty of Medicine, Université de Montréal, and Principal Investigator of the “Cell Division and Differentiation” research unit at the Institute for Research in Immunology and Cancer (IRIC). Recruited in 2005, he leads an internationally recognized program that exploits the nematode C. elegans to decipher the molecular logic governing stem cell division, polarity and tissue organization. Education & Training: PhD in Biochemistry, Université de Montréal (supervisors: Luis A. Rokeach & Siegfried Hekimi) Postdoctoral Fellow, Department of Biology, University of North Carolina at Chapel Hill, USA (with Bob Goldstein) Postdoctoral Fellow, Institute of Biochemistry, ETH Zurich, Switzerland (with Monica Gotta) Research Focus: His laboratory investigates how germline stem cells balance self-renewal and differentiation through oriented divisions that maintain contact with the distal tip cell niche, and how syncytial germline architecture is established, expanded and maintained. These studies integrate advanced live-cell imaging, quantitative image analysis, genetics and biochemistry, and provide fundamental insights relevant to mammalian development, tissue regeneration and cancer. Funding & Awards: Canada Research Chair in Cell Division and Differentiation (2006–2016) CIHR New Investigator Award (2005–2006) Ongoing operating grants from CIHR, NSERC and the Cancer Research Society Team & Mentorship: He currently mentors several graduate students (Mohamed Réda Zellag, Kimia Zarnani, Léa Lacroix) and research associates within a vibrant, collaborative environment at IRIC.

Kuljeet Kaurمشاهده پروفایل

استاد

• Cloud Computing
• Edge/Fog Computing
• Internet of Things (IoT)
• +۷ مورد دیگر

Kuljeet Kaur is a Professor in the Department of Electrical Engineering at École de technologie supérieure (ÉTS) in Montreal, Canada. Her research is conducted through the LACIME (Communications and Microelectronic Integration Laboratory), a renowned research unit focusing on communications and microelectronic integration. She maintains an active research program with numerous publications and student supervision activities. Professor Kaur's research spans multiple interconnected domains focused on next-generation computing and communication systems. Her primary research axes include Sensors, Networks and Connectivity; Intelligent and Autonomous Systems; and Software Systems, Multimedia and Cybersecurity. Within these broad areas, she specializes in Cloud Computing, Edge/Fog Computing, Internet of Things (IoT), Cybersecurity, Privacy, Federated Learning, and Energy Management. Her work bridges theoretical foundations with practical implementations in intelligent transportation systems, healthcare applications, and smart grid technologies. Analysis of Professor Kaur's recent publications reveals a strong focus on security and privacy challenges in emerging computing paradigms. A significant portion of her work addresses federated learning approaches that maintain data privacy while enabling collaborative AI model training. Her research also demonstrates expertise in edge computing architectures, particularly for IoT applications, with emphasis on energy efficiency and security. The publications show consistent interdisciplinary collaboration across computer science, electrical engineering, and transportation domains. Professor Kaur actively supervises multiple graduate students at various levels. Her supervision portfolio includes doctoral candidates working on topics like decentralized AI networks and secure federated learning, as well as master's students focusing on edge AI for IoT applications, sensor drift compensation, and zero trust architecture for IoT. She also guides project students working on practical implementations of AI for smart grid optimization and secure IoT protocols. Her research is conducted within the LACIME laboratory, which brings together researchers working on everything from micro- and nanofabrication processes to communication protocols and signal processing. The lab provides a transdisciplinary environment where Professor Kaur's work on cyber-physical systems and secure communications benefits from complementary expertise in integrated circuit design and microsystems.

Adele Diamondمشاهده پروفایل

استاد

• Developmental Cognitive Neuroscience
• Executive Functions
• Prefrontal Cortex
• +۶ مورد دیگر

Adele Diamond is a Professor at the University of British Columbia 's Faculty of Medicine , Department of Psychiatry . She pioneers Developmental Cognitive Neuroscience and challenges traditional educational and medical paradigms through her work on executive functions (EFs) and their modulation by dopamine , stress , and educational interventions . Her educational background includes: Philosophy of Science, London School of Economics (1972) B.A. in Psychology and Sociology & Anthropology, Swarthmore College (1975) Ph.D. in Developmental Psychology, Harvard University (1983) Postdoctoral Fellowship in Neuroanatomy, Yale University School of Medicine (1982-1985) Research focuses on: EFs ( cognitive flexibility , working memory , self-control ) and their neural bases in prefrontal cortex Gene-environment interactions like COMT gene polymorphism and sex differences under stress Interventions: mindful movement , Tools of the Mind curriculum, physical activity , and the arts Key scientific awards include: Fellow, Royal Society of Canada Huttenlocher Award (Flux Society for Developmental Cognitive Neuroscience) Two Honorary Doctorates (University of Cambridge, Erikson Institute) She mentors PhD students in Neuroscience, Population and Public Health, and Interdisciplinary Studies. Her lab at UBC's Centre for Brain Health and BC Children's Hospital Research Institute integrates neuroimaging (fMRI) with genetic analysis and intervention studies . Recently organized the 4-day international conference 'A Joyous Celebration' uniting 400+ attendees from 45 countries.

Ramadan El Shatshatمشاهده پروفایل

دانشیار

• Power Distribution Systems
• Smart Grids
• Energy Management
• +۴ مورد دیگر

Ramadan El Shatshat is an Associate Professor (Teaching Stream) and Director of the Electric Power Engineering Program at the University of Waterloo's Department of Electrical and Computer Engineering. He holds a PhD from the University of Waterloo (2001) and is a registered Professional Engineer in Ontario. His research focuses on distribution system engineering, smart grids, renewable energy integration, and electric vehicle impact analysis. Dr. El Shatshat has received multiple awards, including the James A. Field Teaching Excellence Award (2016) and the University of Waterloo Outstanding Performance Award (2010, 2017, 2021). He teaches courses like ECE 360 (Power Systems and Smart Grids) and ECE 668 (Distribution System Engineering). Education: PhD in Electrical Engineering, University of Waterloo (2001) MSc in Electrical Engineering, University of Garyounis, Libya (1992) BSc in Electrical Engineering, University of Garyounis, Libya (1984) Research Interests: Smart grids and microgrids Optimization for distribution systems Electric vehicles and renewable energy integration AI-based monitoring techniques Awards: 2021 University of Waterloo Outstanding Performance Award 2018 Marsland Faculty Fellowship 2016 James A. Field Teaching Excellence Award Advising & Grants: Supervised/co-supervised 26 students (undergraduate, master's, doctoral, and postdoctoral) His work spans over 50 peer-reviewed publications and patents in fault detection, voltage control, and EV integration.