جستجوی استاد راهنمای دانشگاهی

Kyros Kutulakosمشاهده پروفایل

استاد

• Computational Imaging
• Computer Vision
• 3D Sensing
• +۹ مورد دیگر

Kyros Kutulakos is a Professor in the Department of Computer Science at the University of Toronto, where he leads research in computational imaging and 3D sensing. His affiliations include the Toronto Computational Imaging Group, Computer Vision Group, Dynamic Graphics Project (DGP), and Vector Institute Group. He teaches graduate and undergraduate courses such as CSC320 (Introduction to Visual Computing) and CSC2530 (Computational Imaging & 3D Sensing). His research interests span computational imaging, non-line-of-sight imaging, single-photon detectors, 3D sensing, and neural rendering. Notable contributions include advancements in structured-light imaging, time-of-flight systems, and super-oscillatory microscopy. He has advised numerous PhD and MSc students, fostering cutting-edge research in imaging technologies. Kutulakos has received prestigious awards, including the Dean’s Research Excellence Award (2023) and multiple best paper prizes (e.g., Marr Prize at ICCV 2023). He has served as program chair for ICCV 2013, ICCP 2010, and CVPR 2003, contributing to academic leadership in computer vision. His work bridges optics, photonics, and computation, with applications in autonomous systems, medical imaging, and astronomy. Current research focuses on extreme imaging scenarios, such as imaging in pitch-black environments and around corners, leveraging novel sensor designs and computational techniques.

Camila Aquinoمشاهده پروفایل

استادیار

• Movement Disorders
• Parkinson's Disease
• Deep Brain Stimulation
• +۵ مورد دیگر

Dr. Camila Aquino serves as Assistant Professor in both the Department of Clinical Neurosciences and Department of Community Health Sciences at the University of Calgary's Cumming School of Medicine, and is a Full Member of the Hotchkiss Brain Institute. As Medical Director of the Deep Brain Stimulation Program, she specializes in Parkinson's disease, essential tremor, dystonia, and chorea management, including EMG-guided botulinum toxin injections. Her educational background includes: M.D. in Medicine from Escola Superior de Ciencias da Santa Casa (2005) M.S. in Neurosciences from Federal University of Sao Paulo (2012) Ph.D. in Neurosciences from Federal University of Sao Paulo (2019) M.S. in Health Research Methods, Clinical Epidemiology from McMaster University (2020) Dr. Aquino's research addresses unmet needs in movement disorders through innovative clinical trial designs for Parkinson's disease, focusing on precision-medicine approaches, early intervention, and outcome optimization. She actively evaluates neuromodulation therapies including Deep Brain Stimulation, Spinal Cord Stimulation, and MRgFUS, with emphasis on expanding indications and improving patient outcomes. As an International Parkinson and Movement Disorder Society member, she chairs the web-based learning committee and serves on evidence-based medicine and outcome measure committees. Analysis of her 15 most recent publications (2021-2025) reveals a cohesive research trajectory centered on Parkinson's disease management, with dominant themes in motor fluctuation treatments, deep brain stimulation methodology, and clinical trial innovation. Her work bridges fundamental clinical practice guidelines with advanced neuromodulation technologies, demonstrating consistent commitment to evidence-based solutions for movement disorders. Her scientific recognition includes: Parkinson Canada research grant Mohammed Al Zaibak Foundation scholarship CAPES scholarship from Brazilian Ministry of Education Dr. Aquino has secured significant research funding supporting clinical trials in Parkinson's disease neuroprotection and neuromodulation therapies. While specific student advisees aren't listed, her leadership of the DBS Program and active clinical trial portfolio indicate substantial mentorship responsibilities. Her grant portfolio emphasizes translational research with direct clinical impact. She directs the University of Calgary's Deep Brain Stimulation Program and contributes to the MRI-guided focused ultrasound initiative. Through her International Parkinson and Movement Disorder Society committee roles, she shapes global educational standards and evidence-based practices in movement disorders.

Arash Aramiمشاهده پروفایل

دانشیار

• Assistive Robotics
• Human-Robot Interaction
• Machine Learning
• +۶ مورد دیگر

Arash Arami is an Associate Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo, cross-appointed in Systems Design Engineering. He directs the Neuromechanics and Assistive Robotics Laboratory and maintains affiliations with Waterloo Robohub, the Centre for Bioengineering and Biotechnology, Waterloo AI institute, and KITE institute at Toronto Rehab Institute. He earned his Doctorate in Electrical Engineering from EPFL (2014), Master of Science from University of Tehran (2009), and Bachelor of Science from University of Tabriz (2006), all in Control Engineering. His research in Assistive Robotics and Rehabilitation Engineering integrates Machine Learning with Neuromechanics to develop intelligent systems for human movement analysis. Key focus areas include exoskeleton control algorithms, wearable sensor systems, and neural control modeling for rehabilitation applications. Recent publications demonstrate interdisciplinary work spanning robotics, biomedical engineering, and materials science, with emphasis on real-time human locomotion prediction, exoskeleton-human interaction, and data-driven health monitoring solutions. Dr. Arami serves as Chair of the NSERC Scholarship Committee (2021-2023) and mentors graduate students through the Mechatronics Exchange Study program. His teaching includes core courses in control systems, robot manipulators, and biomechanical engineering. The Neuromechanics and Assistive Robotics Laboratory fosters collaborations with clinical partners at Toronto Rehab Institute, focusing on translating robotic innovations into practical rehabilitation tools through interdisciplinary teamwork.

Michael Feeleyمشاهده پروفایل

دانشیار

• Operating Systems
• Distributed Systems
• File Systems
• +۷ مورد دیگر

Michael Feeley is an Associate Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Institute for Computing, Information and Cognitive Systems (ICICS). His research focuses on operating systems, distributed systems, and their applications in scalable file systems, cloud storage, and mobile computing. He leads projects such as the Unico file system, Parallax storage system, and Remus virtual machine replication framework. His research interests include peer-to-peer file systems, mobile ad hoc networks, interference mitigation in wireless networks, and system software for workstation clusters. He has supervised numerous graduate students, contributing to advancements in distributed systems and networking. His work often addresses challenges in resource management, fault tolerance, and performance optimization. Publications span topics like interference detection in WiFi networks, dynamic program analysis (Tralfamadore), and distributed storage solutions. Feeley teaches courses such as CPSC 213, emphasizing operating systems fundamentals. His office is located in CISR 393, with contact details available via email and phone.

• 3D Computer Vision
• Computer Vision
• Machine Learning
• +۴ مورد دیگر

Kwang Moo Yi is an Assistant Professor in the Department of Computer Science at the University of British Columbia (UBC), where he conducts research in computer vision and machine learning. He is affiliated with the Computer Vision Lab, CAIDA (Centre for Artificial Intelligence Decision-making and Action), and ICICS (Institute for Computing, Information and Cognitive Systems) at UBC. Education: B.Sc. from Seoul National University Ph.D. from Seoul National University under Prof. Jin Young Choi Post-doctoral researcher at École Polytechnique Fédérale de Lausanne (EPFL) with Prof. Pascal Fua and Prof. Vincent Lepetit Dr. Yi's research focuses on Visual Geometry with the goal of understanding local environments, adapting to them, and acting within them. His work spans applications in autonomous vehicles, drones, robots, and Augmented/Mixed Reality systems. He employs machine learning, particularly deep learning, as the primary tool for advancing computer vision capabilities. His recent publications demonstrate a strong focus on neural rendering techniques, especially 3D Gaussian Splatting and Neural Radiance Fields (NeRF). The research trends show increasing sophistication in handling occlusions, improving rendering quality, and developing more efficient training methods for neural fields. There's also significant work connecting computer vision with practical applications in industrial settings and energy systems. Dr. Yi serves as an area chair for top computer vision and machine learning conferences including CVPR, ICCV, ECCV, NeurIPS, ICML, and AAAI. He was part of the organizing committee for CVPR 2023. He supervises graduate students including Eric (who recently completed his PhD), Gopal (now at Samsung Research), and Jeong-Gi (joining as a postdoctoral fellow). His teaching includes CPSC 425: Computer Vision and CPSC 533Y: 3D Computer Vision with Deep Learning. Dr. Yi is actively involved with the Computer Vision Lab at UBC, collaborating with researchers across CAIDA and ICICS. His work bridges theoretical computer vision with practical applications in various domains including astronomy, industrial automation, and energy systems.

Richard Simonمشاهده پروفایل

دانشیار

• Rock Mechanics
• Mining Engineering
• Geotechnics
• +۴ مورد دیگر

Richard Simon is an Associate Professor in the Department of Civil, Geological and Mining Engineering at Polytechnique Montréal. He holds leadership roles as Publications Director of his department and Administrative Director of the Institute for Research in Mining and Environment (IRME) UQAT-Polytechnique. His educational background includes a B.Eng. and M.Sc.A. from Polytechnique Montréal and a Ph.D. from McGill University. Dr. Simon teaches courses including Introduction to Mine Operations, Underground Mining, and Rock Mechanics I. His research focuses on rock mechanics, numerical modeling, mining engineering, and geotechnical applications in mining environments. His extensive publication record demonstrates consistent focus on numerical modeling of rock behavior, mine stability analysis, and backfill mechanics. Recent work emphasizes computational geomechanics applications in mining operations, including stress analysis in backfilled stopes, slope stability in open pits, and optimization of mining layouts. Environmental aspects of mining, particularly contaminant transport in fractured rock, also feature prominently. Dr. Simon has supervised 6 doctoral and 8 master's students working on topics ranging from numerical seismic assessment in mines to rock fracture mechanics. He secured significant research funding including $900,000 (2017) for a metals circular economy project and led three new IRME research initiatives (2015). He directs research activities at IRME UQAT-Polytechnique and collaborates extensively within the mining geomechanics research community. His expertise is regularly featured in media outlets including La Presse+ and Les Affaires.

K. Rajibul Islamمشاهده پروفایل

دانشیار

• Quantum Information Processing
• Trapped Ion Quantum Simulation
• Quantum Computing
• +۴ مورد دیگر

K. Rajibul Islam is an Associate Professor at the University of Waterloo, affiliated with the Institute for Quantum Computing (IQC) and the Department of Physics and Astronomy. He holds a joint appointment with the Perimeter Institute for Theoretical Physics and co-founded Open Quantum Design and Lightflow Optics Inc. His research focuses on quantum information processing, quantum simulation, and trapped ion systems, with applications in quantum computing and entanglement studies. Education: Ph.D. in Physics (2012, University of Maryland), M.Sc. in Physics (2007, Tata Institute of Fundamental Research), B.Sc. in Physics (2005, Jadavpur University). Postdoctoral research at Harvard University (2012–2015) and MIT (2015–2016). Research Interests : Quantum simulation of spin models, quantum computing with trapped ions, entanglement measurement, frustrated spin systems, and quantum materials. His lab, QITI (Quantum Information with Trapped Ions), develops scalable quantum simulators and open-access quantum computers like 'QuantumIon.' Awards : Fellow of the American Physical Society (2024), VAIBHAV Fellowship (2024), Excellence in Teaching Award (2024), Early Researcher Award (2019), and Distinguished PhD Dissertation Award (2012–13). Teaching : Courses include PHYS 701 (Graduate Quantum Physics), PHYS 234 (Quantum Physics I), PHYS 393 (Physical Optics), and PHYS 256 (Geometrical and Physical Optics). He emphasizes outreach via initiatives like Bigyan.org.in , a Bengali-language science platform. Lab and Collaborations : Active in developing trapped-ion quantum hardware, including ion trap designs, optical addressing systems, and holographic control methods. Collaborates on quantum algorithms, machine learning for quantum systems, and experimental quantum thermodynamics.

Abbas Samaniمشاهده پروفایل

استاد

• Biomedical Engineering
• Medical Imaging
• Computational Modeling
• +۵ مورد دیگر

Prof. Abbas Samani is a Professor at the Department of Electrical and Computer Engineering and holds a joint appointment in the Department of Medical Biophysics at Western University . He is a core faculty member of the Biomedical Engineering Graduate Program and an Associate Scientist at Imaging Research Laboratories of Robarts Research Institute . His academic journey includes a Ph.D. from the University of Waterloo, an M.Sc. from the University of Tehran, and a B.Sc. from Amirkabir University of Technology. His research focuses on biological tissue computational modeling and its applications in medical imaging, intervention, and image analysis . He develops computer/image-assisted tools for minimally invasive disease diagnosis and therapy , targeting heart disease, cancer, and lung disease . Key projects include myocardium biomechanical modeling , handheld medical devices for breast cancer screening , and lung disease diagnostics via CT image segmentation . His recent publications emphasize ultrasound elastography , finite element modeling , and inverse problems in biomechanics , primarily in journals like IEEE Transactions on Computational Imaging and Translational Oncology . His work spans both computational modeling and medical device development . Selected Graduate Supervision : Ph.D. Candidates : Seyed Hassan Haddad, Elham Karami, Seyed Mohammad Hesabgar Graduated Ph.D. Students : Ali Sadeghi Naini, Seyed Reza Mousavi M.Sc. Students : Cristian Linte, Patrick Courtis, Joseph O'Hagan, Hatef Mehrabian, Hirad Karimi, Hosein Amooshahi, Seyed Mohammad Hesabgar, Nastaran Ghadarghadr, Shadi Shavakh, Ehsan Salamati, Ehsan Omidi Teaching Contributions : Graduate: BME9519B/CAMI9519B/ECE9202B/ECE9022B - Advanced Image Processing and Analysis , MBP9530A - Human Biomechanics and Biomedical Applications Undergraduate: ECE4438B - Advanced Image Processing and Analysis , ES1050 - Introductory Engineering Design and Innovation Studio , MBP3330F - Human Biomechanics and Biomedical Applications Research Affiliations : Robarts Research Institute - Associate Scientist at Imaging Research Laboratories Western University - Core Faculty, Biomedical Engineering Graduate Program

Olga Vekslerمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Deep Learning
• +۶ مورد دیگر

Olga Veksler is a Professor at the University of Waterloo's Department of Computer Science, part of the Faculty of Mathematics. She holds a Ph.D. and M.Sc. from Cornell University (1999) and a B.A. from New York University (1995). Her research focuses on computer vision, machine learning, and discrete optimization, with notable contributions to image segmentation, graph algorithms, and deep learning integration. Her work emphasizes semantic segmentation, salient object detection, and efficient optimization techniques for graphical models. Education: Ph.D. in Computer Science, Cornell University, 1999 M.Sc. in Computer Science, Cornell University, 1999 B.A. in Computer Science, New York University, 1995 Her research explores intersections between machine learning and traditional computer vision challenges, particularly leveraging graph-based optimization and CRF models. Recent trends in her work include weakly supervised learning, sparse non-local CRF applications, and test-time adaptation strategies for salient object detection. She has pioneered methods for shape priors in multi-object segmentation and efficient graph-cut algorithms. Her advising and grant activities are foundational to her research, though specific grant details are not listed here. She maintains a lab focused on advancing computer vision through algorithmic innovation, with contributions to both theoretical frameworks and practical applications in medical imaging and scene understanding.

Ali Lazrakمشاهده پروفایل

دانشیار

• Asset Pricing
• Corporate Finance
• Behavioral Finance
• +۵ مورد دیگر

Ali Lazrak is an Associate Professor at the Sauder School of Business , University of British Columbia , specializing in Finance . He holds the Peter Lusztig Professorship in Finance and teaches courses such as International Financial Markets and Institutions and Theory of Finance (2024-2025). His research bridges Political Economy , Asset Pricing , and Behavioral Finance , with a focus on ESG concerns , Voting Theory , and Time Inconsistency . Education: ENSAE (B.Sc.), Sorbonne (M.Sc.), Toulouse (Ph.D.) Contact: Henry Angus Building (HA 872), +1 604.822.9481, ali.lazrak@sauder.ubc.ca His work explores group decision-making in corporate investment, green finance (e.g., the green premium in ESG markets), and time-inconsistent preferences in continuous games. Recent publications highlight how responsible consumption and demand elasticity shape asset prices, and how institutional divestiture impacts harmful asset stranding through informational and economic channels. Scientific accolades include the Jacob Gold & Associates Best Paper Prize (2019), Best Paper Awards at HEC-McGill, UBC, Luxembourg, and Stanford conferences, and the Peter Lusztig Professorship . His methodological expertise spans stochastic control , recursive utility , and dynamic equilibrium analysis .

Amir-massoud Farahmandمشاهده پروفایل

دانشیار

• Reinforcement Learning
• Machine Learning
• Computer Science
• +۴ مورد دیگر

Amir-massoud Farahmand is an Associate Professor at the Polytechnique Montréal (Department of Computer and Software Engineering) and a Status-Only Associate Professor at the University of Toronto (Department of Computer Science). He is also a Core Academic Member at Mila (Quebec AI Institute). His research focuses on computational and statistical mechanisms for designing efficient reinforcement learning (RL) agents and adaptive algorithms. Dr. Farahmand's research spans reinforcement learning, optimal transport, adversarial robustness, and model-based methods. He has extensively studied regularization in RL, distributional approaches, and algorithm design for stability and convergence. His textbook Lecture Notes on Reinforcement Learning (2021) emphasizes mathematical intuition over algorithmic collections. Recent publications highlight trends in high-update-ratio RL, distributional equivalence, and self-prediction for task understanding. He is actively involved in teaching, having previously instructed courses on machine learning, neural networks, and RL at the University of Toronto. Scientific Awards : Ontario Early Researcher Award (2024) for Accelerated Reinforcement Learning Algorithms Dr. Farahmand has mentored numerous students, including his first PhD graduate Yangchen Pan (now at Oxford) and MSc students like Allen Bao (AMD) and Farnam Mansouri (University of Waterloo). He is currently recruiting graduate students at Polytechnique Montréal and Mila for 2025 admissions.

G.K. Knopfمشاهده پروفایل

استاد

• Product Design & Advanced Manufacturing
• 3D Shape Reconstruction
• Laser Microfabrication
• +۵ مورد دیگر

Dr. G.K. Knopf is a Professor in the Department of Mechanical & Materials Engineering at Western University, Canada. He holds a Ph.D. (1991), M.Sc. (1987), and B.E. (1984) from the University of Saskatchewan. His work bridges product design, advanced manufacturing, and bio-inspired technologies. Research Focus: Dr. Knopf’s research spans 3D shape reconstruction , laser microfabrication , micro-optics , and bioelectronic imaging arrays . Recent projects emphasize light-driven actuators , flexible electronics , and graphene-based inks for printing circuits on unconventional substrates like silk and paper. Publications: Over 150 peer-reviewed works, including two edited CRC Press volumes ( Smart Biosensor Technology , Optical Nano and Micro Actuator Technology ). Key contributions involve non-lithographic fabrication , bacteriorhodopsin photodetectors , and self-organizing feature maps for data visualization. Awards/Patents: Co-inventor of two U.S. patents (6,542,249 for 3D surface measurement; 7,573,024 for bioelectronic imaging arrays). Teaching: Leads graduate courses in Medical Device Design and Optomechatronic Systems , as well as undergraduate Mechatronics and Medical Device Development courses.

• Artificial Intelligence
• Operations Research
• Revenue Management
• +۳ مورد دیگر

Yuri Levin is a Professor at the Smith School of Business, Queen’s University, where he holds the Stephen J.R. Smith Chair of Analytics and serves as Founding Executive Director of the Smith School of Business Analytics and AI. He also leads the Scotiabank Centre for Customer Analytics. His research focuses on Analytics & AI, with expertise in revenue management, dynamic pricing, and strategic consumer behavior. Levin holds a Ph.D. in Operations Research from Rutgers University and degrees in Economics and Applied Mathematics from Belarus State University. Levin’s academic contributions include co-winning the 2013 INFORMS Revenue Management and Pricing Practice Prize and the 2009 INFORMS COIN-OR Cup. He has advised companies like Scotiabank, Loblaws, and McDonald’s on pricing strategies and consumer analytics. As an Associate Editor of Operations Research , he shapes academic discourse in operations research and pricing strategies. Education: Ph.D. in Operations Research, RUTCOR, Rutgers University (2001) B.S. in Economics, Belarus State University (1998) M.S. (Honours) in Applied Mathematics, Belarus State University (1998) His research explores dynamic pricing models under social influence, strategic consumer behavior, and revenue management in hospitality and retail industries. He has pioneered methodologies for optimizing pricing strategies in networked markets and developed algorithms for cargo capacity management. Awards: 2010 Queen’s School of Business Award for Research Achievement 2003 New Researcher Achievement Award Levin’s teaching spans MBA, Master of Management Analytics (MMA), and executive education programs, covering analytical decision-making and pricing optimization. His advisory work includes roles as a Visiting Professor at the Skolkovo Moscow School of Management and the University of Cambridge’s Judge School of Business.

• Cardiology
• Interventional Cardiology
• Coronary Artery Disease
• +۳ مورد دیگر

Elvin Kedhi, MD, PhD is an Investigator at the Research Institute of the McGill University Health Centre (RI-MUHC) at the Glen site, where he is affiliated with the Cardiovascular Health Across the Lifespan Program. As a faculty member at McGill University's Faculty of Medicine, he contributes to both clinical practice and academic research in cardiology. Dr. Kedhi's research focuses on interventional cardiology, particularly coronary artery disease management, fractional flow reserve techniques, and clinical trials comparing different treatment approaches for cardiovascular conditions. His work often involves complex clinical scenarios including patients with diabetes, high bleeding risk, and multivessel coronary disease. He has pioneered research on thin-cap fibroatheroma identification and its clinical implications, as well as optimal dual antiplatelet therapy durations following stent implantation. His recent publications demonstrate a strong emphasis on comparing transcatheter and surgical approaches for treating patients with combined aortic valve stenosis and coronary artery disease. Dr. Kedhi frequently collaborates with international research teams across Europe and North America, contributing to large-scale multicenter clinical trials that shape current cardiovascular treatment guidelines. Active researcher in interventional cardiology clinical trials Focus on optimizing treatment strategies for complex coronary artery disease Expertise in fractional flow reserve and intravascular imaging techniques International collaborations across multiple continents Dr. Kedhi maintains an active clinical research program with numerous ongoing studies examining innovative approaches to cardiovascular disease management. His work bridges the gap between technological advances in cardiac interventions and practical clinical applications that improve patient outcomes.

Eleodor Nichitaمشاهده پروفایل

دانشیار

• Nuclear Reactor Design
• Neutron and Radiation Transport
• Reactor Kinetics and Control
• +۳ مورد دیگر

Dr. Eleodor Nichita is an Associate Professor in the Department of Energy and Nuclear Engineering at the University of Ontario Institute of Technology (UOIT), part of the Faculty of Engineering and Applied Science. He holds a PhD in Nuclear Engineering from Georgia Institute of Technology (USA) and additional degrees from McMaster University and the University of Bucharest. His research focuses on neutron transport, reactor kinetics, advanced nuclear reactor design, and radionuclide production. He teaches a wide range of courses including reactor physics, neutron detectors, and medical imaging applications of radiation. Education: PhD in Nuclear Engineering, Georgia Institute of Technology, United States MS in Health Physics, Georgia Institute of Technology MS in Medical Physics, McMaster University BS in Engineering Physics, University of Bucharest, Romania Research interests emphasize mathematical modeling for nuclear systems, neutronic design of advanced reactors, and production of medical isotopes like Mo-99. His work addresses reactor safety, lattice homogenization techniques, and SCWR (supercritical water-cooled reactor) dynamics. Over 50 peer-reviewed papers and book chapters reflect his contributions to CANDU reactor analysis, PHWR fuel bundle design, and educational innovations in nuclear engineering. Advising and grants: While specific student names are not listed, his extensive teaching portfolio (including graduate-level reactor physics courses) indicates active mentoring. Research grants likely support his work on reactor kinetics and SCWR technology. Lab affiliations: His research is conducted through the Energy Systems and Nuclear Science Research Centre (ERC) at UOIT, focusing on numerical methods and experimental validation for reactor analysis.