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Robson De GrandeView profile

Associate Professor

Brock UniversityCanada

Robson E. De Grande is an Associate Professor in the Department of Computer Science at Brock University, Canada. He holds a PhD from the University of Ottawa (2012) and BSc/MSc degrees from the Federal University of São Carlos, Brazil. His research focuses on vehicular networks, intelligent transportation systems, distributed systems, and cloud computing. He serves on program committees for conferences like DS-RT, MobiWac, and MSWiM, and has organized multiple workshops and special sessions. Education: PhD in Computer Science, University of Ottawa, Canada (2012) MSc and BSc in Computer Science, Federal University of São Carlos, Brazil (2006, 2004) Research Interests: Vehicular Networks (5G, Handover Management) Edge Computing and IoT Performance Modeling/Simulation High-Performance Distributed Systems Intelligent Transportation Systems Publications: Over 100 peer-reviewed articles across journals like IEEE Transactions on ITS, Elsevier Internet of Things, and conferences like IEEE ICC and ACM MobiWac. Recent work emphasizes ML-driven vehicular network optimization and distributed simulation frameworks. Teaching: Teaches Advanced Computer Networks (COSC 4P14), Parallel Computing (COSC 3P93), and graduate-level Mobile Cloud Computing courses. Research Team: Supervises PhD/MSc students and undergraduate researchers in topics like vehicular edge computing, traffic prediction, and simulation systems.

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Kenneth R. JacksonView profile

Professor

University of TorontoCanada

Kenneth R. Jackson is a Full Professor of Computer Science at the University of Toronto, where he has been active since 1981. He retired in 2020 but continues research in numerical computation, computational finance, and scientific computing. Born in Montreal and raised in Toronto, Jackson earned all his degrees from the University of Toronto: BSc (1973), MSc (1974), and PhD (1978). He held roles as Gibbs Instructor and Visiting Assistant Professor at Yale University before returning to Toronto. Recognized as an NSERC University Research Fellow, he also served as Associate Chair for Graduate Studies (2002–2005) and President of the Canadian Applied and Industrial Mathematics Society (2001–2003). His research focuses on numerical methods for ODEs, parallel computation, validated solutions, and applications in finance, medical imaging, and climate modeling. He has advised over 30 graduate students, many of whom contributed to groundbreaking work in computational finance and scientific computing. Jackson organized the 2001–02 Thematic Year on Numerical Challenges in Science at the Fields Institute and currently advises YetiWare. He teaches advanced courses in numerical methods, optimization, and computational finance, and has published extensively on topics ranging from high-dimensional ODE systems to GPU-accelerated financial modeling.

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Bryan SarloView profile

Lecturer

Western UniversityCanada

Bryan Sarlo is a Lecturer in the Department of Computer Science at Western University since Fall 2017. He specializes in teaching foundational courses such as CS1033, CS1027, CS2033, and Python programming for non-CS students in the Western Integrated Science (WISc) program. He authored a digital multimedia textbook tailored for CS1033. Education: BSc in Computer Science, Nipissing University MSc in Computer Science (Thesis: AI in Video Game Development), Western University, supervised by Dr. Mike Katchabaw Research Interests: Focus on AI applications in video games, procedural content generation, and educational technology. His MSc work explored AI-driven society simulation in modern video games, with a focus on agent-based modeling and procedural generation techniques. Publications: Notable works include studies on artificial society generation, particle swarm optimization, and visualization frameworks applied to fuel consumption simulation through serious games. These contributions bridge game development, optimization algorithms, and educational tools. Awards: The 'Teaching Awards' section is listed but no specific awards are mentioned in available texts. Advising & Grants: No formal advisees or grants are listed in the provided materials. His role emphasizes teaching and curriculum development rather than direct graduate supervision. Labs/Teams: No specific lab or team affiliations are detailed in the text.

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Marius ParaschivoiuView profile

Professor

Concordia UniversityCanada

Marius Paraschivoiu is a Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University, within the Faculty of Engineering and Computer Science. His research focuses on computational fluid dynamics (CFD), finite element methods, and aerodynamic simulations with applications to wind energy systems, acoustic simulations, and turbulence modeling. He holds a PhD in engineering and has expertise in parallel computing and urban wind energy potential assessment. His work emphasizes optimizing vertical axis wind turbine (VAWT) performance in urban environments, including roof-mounted installations, wake interactions, and turbulence effects. Paraschivoiu has extensively studied the impact of building geometry, corner placements, and fluid-structure interactions on turbine efficiency. His CFD-based analyses address challenges like mesh adaptation, multiphase flows, and real-gas modeling for hydrogen systems. Key research themes include improving wind energy harvesting through innovative turbine designs, mitigating aerodynamic noise, and enhancing flow uniformity in complex configurations. Paraschivoiu’s contributions span over 50 peer-reviewed articles, with recent focus on urban microclimate effects, VAWT array optimization, and turbine blade morphing concepts. He maintains an active research website at Concordia University and collaborates on applied projects involving CFD validation and industrial gas turbine combustor emissions.

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Mikael EklundView profile

Professor

Ontario Tech UniversityCanada

Dr. Mikael Eklund is a Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, within the Faculty of Engineering and Applied Science. He holds a PhD (2003), MSc (1996), and BSc (1989) in Electrical and Computer Engineering from Queen’s University. His research focuses on Autonomous Systems , Nonlinear System Identification and Control , Health Informatics , and Pervasive and Mobile Computing . He has expertise in medical image processing, robotic vehicles, and smart sensors for assisted living. Education and Work Experience : - PhD (Electrical and Computer Engineering), Queen’s University (2003) - MSc and BSc from Queen’s University (1996, 1989) - Visiting Postdoctoral Scholar at UC Berkeley (2003–2006) - Adjunct Assistant Professor at Queen’s University (2003) - Former Teaching Fellow at Queen’s University (1996–2001) - Industrial experience in flight control system engineering (CAE Inc., 1989–1996) Research Contributions : - Developed SensorNet, a wireless infrastructure for assisted living. - Advanced methods for nonlinear system identification in chemical processes and aerospace systems. - Pioneered real-time UAV safety protocols and model predictive control algorithms for aerial pursuit-evasion games. - Explored EMG signal processing for hand force estimation and MEG signal source localization in neuroscience. Teaching and Outreach : - Teaches courses like Medical Image Processing and Electric Circuits. - Active in interdisciplinary projects like the ITALH initiative for elder tech integration. - Presented at conferences such as IEEE EMBC, ACC, and CDC, emphasizing healthcare IT and autonomous systems.

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James StewartView profile

Professor

Queen's University at KingstonCanada

James Stewart is a Professor at Queen's University's School of Computing. His research focuses on biomedical computing and surgical navigation systems. Education: Ph.D. in Computer Science from Cornell University (1992) Location: Office Goodwin 732 Contact: Phone 613 533-3156 Research Interests Professor Stewart's work bridges computer graphics, image processing, and medical applications. Key areas include: Computer-assisted surgical navigation 3D medical visualization Geospatial data representation Robust geometric computation Human-computer interaction in clinical settings Medical imaging uncertainty analysis Scientific Awards Best Poster Award (2013) for 'Image-guided Osteochondral Autologous Autografting of the Ankle' Publications His publications span multiple domains including: Computer graphics algorithms Medical imaging techniques Geospatial visualization Biomedical engineering applications Surgical navigation systems Robust geometric computation

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Bin LiView profile

Associate Professor

University of WaterlooCanada

Bin Li is an Associate Professor and Associate Chair of Actuarial Science in the Department of Statistics and Actuarial Science at the University of Waterloo. He holds a PhD in Applied Mathematical and Computational Sciences (2013, University of Iowa), and master's and bachelor's degrees in Computational Mathematics from Xi’an Jiaotong University (2008 and 2005, respectively). His research focuses on quantum optics and optical engineering, particularly in developing robust laser-driven systems for quantum light sources, solid-state emitters, and trapped ion quantum computing. He has pioneered techniques like Notch-filtered Adiabatic Rapid Passage (NARP) and advanced femtosecond pulse engineering for high-performance quantum systems. His work bridges theoretical quantum physics with experimental optical innovations. Research interests include: Optical driving schemes for quantum emitters Adiabatic inversion and rapid passage methodologies Individual ion addressing in quantum simulators Spin dynamics in 2D perovskite materials Publications span 2018–2025, emphasizing advancements in quantum engineering, ultrafast optics, and atomic-scale systems. While no scientific awards are explicitly listed, his impactful contributions to quantum technologies suggest active recognition in the field. Advising and grants: No specific advisees or grants are documented in the provided texts, though his research activities imply involvement in graduate supervision and funding programs.

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Ying WangView profile

Professor

Ontario Tech UniversityCanada

Dr. Ying Wang is a Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, part of the Faculty of Engineering and Applied Science. Her research focuses on RF/microwave circuits, millimeter-wave technology, antennas, and computer-aided design. She holds a PhD from the University of Waterloo (2000), and earlier degrees from Nanjing University of Science and Technology, China. Education: PhD (Electrical Engineering), University of Waterloo, 2000 Master of Applied Science (Electronic Engineering), Nanjing University of Science and Technology, 1996 Bachelor of Engineering (Electronic Engineering), Nanjing University of Science and Technology, 1993 Research Interests: Dr. Wang specializes in microwave filter design, millimeter-wave systems, antenna arrays, and neural network applications in electromagnetic optimization. Her work emphasizes practical implementations in wireless communication systems, satellites, and high-frequency devices. Recent projects include optimizing amplifier stability in CMOS technology and developing advanced multiplexing networks. Publications: Her publications span neural network modeling for microwave filters, millimeter-wave amplifier design, and multiplexer synthesis. Key themes include high-dimensional optimization techniques, scalable circuit models, and cross-disciplinary applications of artificial intelligence in electromagnetics. Professional Background: Prior to academia, Dr. Wang worked as a Senior Member of Technical Staff at COM DEV International (2000–2007), contributing to industrial microwave system development. She currently teaches courses such as Microwave and RF Circuits (ELEE 4750U) and Antenna Theory and Design (ENGR 5695G).

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William D. BishopView profile

Associate Professor

University of WaterlooCanada

William D. Bishop is the Director of Admissions for the Faculty of Engineering at the University of Waterloo and an Associate Professor, Teaching Stream in the Department of Electrical and Computer Engineering. He leads the Engineering Admissions Team and teaches courses in engineering design, digital design, and embedded systems. His research focuses on engineering education, configurable computing, and multimedia processing. Education: Ph.D. in Electrical and Computer Engineering (2003), University of Waterloo M.A.Sc. in Electrical Engineering (1996), University of Waterloo B.A.Sc. in Computer Engineering/Management Science (1994), University of Waterloo Research Interests: Engineering education methodologies and outcomes Field-programmable gate arrays (FPGAs) for general-purpose computing Image processing and multimedia system optimization Hardware/software co-design for embedded systems Awards: Unsung Hero Award (2024) James A. Field Teaching Excellence Award (2006, 2011) Ontario Volunteer Service Award (2019) Teaching & Service: Teaches ECE 124, ECE 224, and ECE 327 Oversees admissions for all undergraduate engineering programs Professional memberships: PEO, OSPE, CEEA, IEEE Industrial Experience: Co-op at Atlantis Aerospace (1992-1993): Developed flight simulation engines Co-op at Motorola Corporation (1991-1992): Ported software to OS/2 platform

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Sheldon AndrewsView profile

Associate Professor

École de Technologie SupérieureCanada

Sheldon Andrews is an Associate Professor of Software Engineering and IT at École de technologie supérieure (ETS) in Montreal, Canada, with an adjunct appointment in Computer Science at McGill University. He is a member of the Multimedia Research Laboratory and has established himself as a leading researcher in physics-based computer animation and simulation. Andrews earned his Ph.D. in Computer Science from McGill University (2015), MASc in Electrical and Computer Engineering from the University of Ottawa (2007), and B.Eng. in Computer Engineering from Memorial University (2004). His academic journey reflects a strong foundation in both theoretical and applied aspects of computer engineering and graphics. His research focuses on real-time physics simulation, articulated mechanism simulation, 3D character animation, motion capture, computational contact mechanics, and virtual environment modeling. Andrews' work bridges the gap between theoretical physics and practical applications in computer graphics, with particular emphasis on creating physically plausible animations that can run in real-time. His research has significant implications for video games, virtual reality, and robotics applications. Analysis of his recent publications (2022-2025) reveals a strong trend toward increasingly sophisticated physics-based character animation techniques, with growing integration of machine learning approaches. His work spans multiple subfields including collision detection, deformable object simulation, vehicle physics, and reinforcement learning for character control, demonstrating both breadth and depth in his research program. VRIPHYS 2012 best paper award for 'Policies for goal directed multi-finger manipulation' Andrews has advised numerous graduate students through their PhD and Master's degrees, with many going on to positions at major companies like DNEG, CM Labs Simulations, and AMD. His professional service is extensive, having served as Program Chair for SCA 2025 and MIG 2024, Conference Chair for I3D 2019, and on program committees for major conferences including SIGGRAPH, SCA, and MIG for multiple years. He has also been active in the Montreal SIGGRAPH Chapter as Secretary from 2018-2021. As a core member of the Multimedia Research Laboratory, Andrews collaborates with researchers across multiple disciplines to advance the state of the art in physics-based simulation. His lab maintains strong industry connections, including a visiting researcher position at Roblox Research, ensuring that theoretical advances translate to practical applications in gaming and virtual environments.

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Vladimir OkhmatovskiView profile

Professor

University of ManitobaCanada

Dr. Vladimir Okhmatovski is a Full Professor in the Department of Electrical and Computer Engineering at the University of Manitoba, affiliated with the Price Faculty of Engineering. His research focuses on fast algorithms in electromagnetics, quantum computing, and high-performance computing. He holds a Ph.D. from the Moscow Power Engineering Institute and has held academic and industry roles globally. He has received prestigious awards including the 2017 Intel Outstanding Researcher Award. Education: Ph.D., Antennas and Microwave Circuits, Moscow Power Engineering Institute, 1997 M.S., Radiophysics and Electronics, Moscow Power Engineering Institute, 1996 Research Interests: Dr. Okhmatovski develops advanced computational methods for electromagnetics, including tensor train decompositions and quantum algorithms. His work addresses challenges in signal integrity, layered media analysis, and inverse scattering. He leads efforts in applying quantum computing to solve matrix equations and has pioneered fast direct solvers using H-matrices. Awards: 2017 Intel Outstanding Researcher Award 1996 Best Young Scientist Report (VI International Conference on Mathematical Methods in Electromagnetic Theory) 2007 Outstanding ACES Journal Paper Award Advising & Grants: He mentors students in climate change research through collaborations with the Centre for Earth Observation Science. His funded projects include quantum computing applications and Arctic sea ice remote sensing. He chairs technical committees for IEEE MTT-S and AP-S. Labs/Teams: His research group focuses on electromagnetic modeling, quantum algorithms, and layered media analysis. Collaborations include the Churchill Marine Observatory for Arctic studies.

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O. Remus Tutunea-FatanView profile

Professor

Western UniversityCanada

O. Remus Tutunea-Fatan is a Professor in the Department of Mechanical & Materials Engineering at Western University, with cross appointments in Biomedical Engineering and Electrical and Computer Engineering. His work focuses on laser polishing, CNC machining, and surface structuring for drag reduction and biomedical applications. Ph.D. in Mechanical Engineering, The University of Western Ontario M.E.Sc. and B.E.Sc. in Mechanical Engineering, Transilvania University, Romania Research interests include: Advanced CAD/CAM frameworks Laser remelting process optimization Biomedical device design Composite manufacturing techniques Surface topography analysis Artificial intelligence in process control Recent publications indicate expertise in: Laser polishing of metallic surfaces Riblet microstructures for drag reduction AI-driven process monitoring 5-axis machining error compensation Scientific recognition includes: Edward G. Pleva Award for Excellence in Teaching (Western University, 2023) Dr. Terry Base Memorial Teaching Award (2022 co-winner, 2021, 2019) R. Mohan Mathur Award (Faculty of Engineering, 2020) University Students' Council Teaching Honour Roll (2011-2012) Prof. Tutunea-Fatan serves as Associate Chair for Graduate Research Programs (2025-2027) Acting Associate Dean for Undergraduate Studies (2023-2024) Acting Chair, Department of Mechanical and Materials Engineering (2021-2022) He supervises over 40 graduate students and collaborates with industry partners including DuPont Safety and Construction, General Motors, and Active Industrial Solutions Inc.

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Salma EmaraView profile

Assistant Professor

University of TorontoCanada

Salma Emara is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Toronto within the Faculty of Applied Science & Engineering. Her academic journey includes a B.Sc. in Electronics and Communications Engineering from the American University in Cairo (2018) and a Ph.D. in Computer Engineering from the University of Toronto (2022), supervised by Professor Baochun Li. Her research spans two domains: (1) technical work in reinforcement learning for computer networking , including adaptive bitrate selection, edge caching, and congestion control; and (2) pedagogical work focused on debugging skill development for beginner programmers and leveraging natural language processing in engineering education . She emphasizes hands-on learning through in-class activities and problem-solving assignments. Publication trends reveal a focus on reinforcement learning in networking (2018–2023) and a parallel interest in educational technology (2024). Her recent work (e.g., TextCraft ) explores NLP-driven resource recommendation for textbooks, while earlier projects (e.g., Cascade , Pareto ) address network optimization through machine learning. Scientific awards include: Faculty of Applied Science & Engineering Early Career Teaching Award (2025) Departmental Teaching Awards (2022–2024) Shortlisted for TATP Teaching Assistant Excellence (2022)

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Zhangxing (John) ChenView profile

Professor

Memorial University of NewfoundlandCanada

Zhangxing (John) Chen is a Professor in the Schulich School of Engineering at the University of Calgary , specializing in the Department of Chemical and Petroleum Engineering . His research focuses on industrial and applied mathematics, computational science, reservoir simulation, and modeling of multi-phase flow in porous media, with applications to the oil and energy sectors, CO2 sequestration, and semiconductor device simulations. He holds the NSERC Industrial Research Chair in Reservoir Simulation and the AITF (iCORE) Industrial Chair in Reservoir Modeling , leading collaborative projects with industry giants like Suncor, Nexen Energy, and China National Petroleum Corp. His work has resulted in 15 patents and a stellar publication record of 16 books and over 500 refereed journal papers. Key Research Areas: Industrial and Applied Mathematics, Reservoir Simulation, Porous Media Flow, CO2 Sequestration, Semiconductor Device Simulations Scientific Awards: CAIMS-Fields Industrial Mathematics Prize (2017) Dr. Chen has trained over 100 graduate students and postdocs, emphasizing advanced computing algorithms and practical applications in energy recovery. His contributions bridge theoretical mathematics with real-world industrial challenges.

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Moritz HeimpelView profile

Associate Professor

University of AlbertaCanada

Moritz Heimpel is an Associate Professor of Physics at the University of Alberta's Faculty of Science. His research focuses on planetary dynamics, particularly the fluid dynamics and magnetohydrodynamics of planetary interiors and atmospheres, with applications to Mercury, Earth, Jupiter, Saturn, Uranus, Neptune, and exoplanets. He teaches courses in environmental geophysics and geophysical imaging of Earth's interior. His work explores zonal flows, vortices, and dynamo action in giant planets, using numerical models to simulate thermal convection and magnetic field generation. Notable contributions include studies on Jupiter's equatorial jets, Saturn's atmospheric features, and Mercury's core dynamics. He has published extensively on topics like planetary gravity harmonics, magnetic field modeling, and paleomagnetic signatures. Heimpel's research integrates computational methods with observational data from missions like Juno and Cassini, advancing understanding of planetary heat transfer, atmospheric dynamics, and core processes. His teaching emphasizes geophysical imaging techniques for environmental applications, including hydrogeology and climate change monitoring. Despite his extensive publication record, no academic awards or grants are explicitly mentioned in the provided texts. His research group's focus on ice giants and exoplanets suggests ongoing exploration of planetary evolution and internal structure dynamics.

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