جست‌وجوی استاد و پژوهشگر

Debajyoti Mondalمشاهده پروفایل

دانشیار

• Information visualization
• Graph drawing
• Computational geometry
• +۶ مورد دیگر

Dr. Debajyoti Mondal is an Associate Professor in the Department of Computer Science at the University of Saskatchewan. His research focuses on algorithms, network visualization, computational geometry, and visual analytics. He holds a PhD from the University of Manitoba and has held postdoctoral positions at the University of Waterloo and Microsoft Research. Mondal's work spans interdisciplinary applications, including collaborations with Saskatoon Transit and academic medicine. He has authored over 100 peer-reviewed publications and secured grants such as NSERC Discovery, CFI, and Canada First Research Excellence grants. His awards include the 2023 New Scholar RSAW Award. Education: Ph.D. in Computer Science, University of Manitoba, 2016 MSc in Computer Science, University of Manitoba, 2012 BSc. Engg. in Computer Science, Bangladesh University of Engineering and Technology, 2009 Research Interests : Algorithms, graph drawing, computational geometry, visual analytics, and interdisciplinary applications in software engineering, transportation, and bioinformatics. His lab (VGA Lab) develops visualization systems for big data analysis. Key Contributions : Advanced theoretical foundations in computational geometry and graph drawing, developed practical visualization tools, and contributed to climate-related projects like Global Water Futures. Grants & Awards : NSERC Discovery Grant (2018-2024) CFI Grant (2021-2025) Microsoft Research Internship (2015-2016) New Scholar RSAW Award (2023) Labs/Teams : Leads the VGA Lab, collaborating with interdisciplinary teams on projects like Clone-World (software clone visualization) and SET-STAT-MAP (mixed data visualization).

Mohammed Khalidمشاهده پروفایل

استاد

• FPGA-based Systems
• Network-on-Chip (NoC) Architectures
• Signal Processing Hardware
• +۳ مورد دیگر

Prof. Mohammed Khalid is a Professor in the Department of Electrical and Computer Engineering at the University of Windsor. He specializes in FPGA-based systems, network-on-chip architectures, and hardware acceleration for signal processing applications. His leadership roles include serving on the executive committee of IEEE Canada. His research focuses on optimizing cryptographic hardware, automotive embedded systems, and efficient algorithm implementations on FPGAs. Key contributions include advancements in PUF-based security mechanisms, high-speed elliptic curve processors, and FPGA-accelerated machine learning algorithms. He has led projects in automotive radar systems and AUTOSAR configuration tools. His work emphasizes practical applications of hardware-software co-design principles. Research Highlights : Development of novel FPGA architectures for real-time signal processing Innovative approaches to resource-efficient cryptographic hardware Pioneering work on hybrid NoC architectures for multi-FPGA systems Awards : IEEE Windsor Section Award (2019) for group leadership Best Student Paper Award (2024) for supervised research by Mohit Sharma Prof. Khalid's 150+ publications span FPGA design methodologies, adaptive signal processing, and embedded systems security. His research group collaborates with industry partners to advance automotive electronics and IoT applications.

Lesley Shannonمشاهده پروفایل

دانشیار

• Computer Engineering
• Reconfigurable Computing
• FPGA CAD Tools
• +۶ مورد دیگر

Lesley Shannon is an Associate Professor in the School of Engineering Science at Simon Fraser University (SFU), specializing in computing system design and reconfigurable computing. She leads the Reconfigurable Computing Lab (RCL), focusing on FPGA-based architectures, heterogeneous multicore systems, and CAD tools. Her academic journey includes a B.Sc. from the University of New Brunswick (1999), M.A.Sc. and Ph.D. from the University of Toronto (2001 and 2006). Her research spans FPGA CAD algorithms, Networks-on-Chip (NoCs), dynamic partial reconfiguration (DPR), and application-specific architectures. Key projects include FUSE (OS abstraction for hardware accelerators), PolyBlaze (multicore system emulation), and uROAMs (microfluidic reconfigurable devices). She has secured funding from NSERC, Xilinx, and Altera, among others. Education: B.Sc., Electrical Engineering (Computer Option), University of New Brunswick, 1999 M.A.Sc., Applied Science, University of Toronto, 2001 Ph.D., Applied Science, University of Toronto, 2006 Roles: NSERC Chair for Women in Science and Engineering (BC/Yukon) Faculty Advisor, SFU WEST (Women in Engineering, Science, and Technology) Her lab employs 5 current students and has graduated 7, including work on FPGA CAD, microfluidics, and embedded systems. Courses taught include Advanced Digital Systems Design and Real-Time/Embedded Systems. Her research emphasizes reducing design time through on-chip profiling and CAD tools, with applications in biomedical imaging and quantum computing. Awards & Grants: NSERC Discovery Grant NSERC Strategic Grant (Lead PI, 2009; Co-PI, 2010) SFU Startup Grant and President’s Research Grant Lab & Collaborations: The RCL develops silicon and non-silicon architectures, including quantum computing and microfluidic systems. Partnerships include industry collaborations and open-source tools like Odin II synthesis framework.

James R. Greenمشاهده پروفایل

استاد

• Machine Learning
• Biomedical Informatics
• Computational Biology
• +۹ مورد دیگر

James R. Green is a Professor in the Department of Systems and Computer Engineering at Carleton University , where he has been a faculty member since 2005. He holds a PhD from Queen's University and is a licensed Professional Engineer (P.Eng.) and Senior Member of IEEE. His work integrates machine learning, biomedical informatics, and high-performance computing. His educational background includes: B.A.Sc. in Systems Design Engineering, University of Waterloo (1998) M.Sc.(Eng.), Queen's University (2000) PhD, Queen's University (2005) Dr. Green's research focuses on machine learning challenges in biomedical informatics , particularly class imbalance and rare event prediction. Key areas include protein structure, function, and interaction prediction; microRNA detection in unique species; non-contact neonatal monitoring; and accelerating scientific computing via parallel architectures like the Cell BE processor. His lab has developed several widely used bioinformatics tools such as PIPE, ProtDCal, and PCI-SUMO. His recent publications reflect a strong trend in computational biology and machine learning , with applications in proteomics, genomics, and medical diagnostics. He has published over 100 peer-reviewed papers and secured funding from NSERC, CIHR, CFI, ORF, OCE, MITACS, and IBM. Scientific and teaching recognitions include: Three teaching awards NSERC Best Project Award (twice: 2006-2007 and 2007-2008) Multiple student projects resulting in conference papers (e.g., CMBEC) He has supervised numerous undergraduate capstone projects in areas such as assistive technologies, robotic systems, and bioinformatics. His teaching portfolio includes courses in Pattern Classification, Machine Learning, Computer Architecture, and Biomedical Engineering. He leads an active research group that bridges computer engineering and life sciences, fostering interdisciplinary collaboration. Lab and research team initiatives include: Development of open-access web servers for protein analysis Collaborations with biologists and clinicians Integration of hardware and software for medical applications

Tony Whiteمشاهده پروفایل

استاد مدعو

• Artificial Intelligence
• Swarm Intelligence
• Genetic Algorithms
• +۴ مورد دیگر

Dr. Tony White is an Adjunct Professor in the School of Computer Science at Carleton University. He holds a Ph.D. from Carleton (2000), an M.A. from Cambridge, and a B.A. in Theoretical Physics. His research focuses on complex adaptive systems, including influence measurement in social networks and swarm intelligence applications. He leads the Complex Adaptive Systems Group and has extensive industry experience, previously working at Nortel. Education: Bachelor of Theoretical Physics, Cambridge University (1981) Master of Physics, Cambridge University (1981) Master of Computer Science, Carleton University (1993) Ph.D. in Electrical Engineering, Carleton University (2000) Research Interests: Artificial Intelligence Swarm Intelligence Genetic Algorithms Neural Networks Recommender Systems Search Engines His work explores influence dynamics in social networks, adaptive information systems, and evolutionary computation. Recent publications address neural network topologies, distributed control strategies, and embedded systems administration. He has also contributed to trust models, referral networks, and traffic signal optimization. Dr. White’s research bridges theoretical computer science and practical applications in robotics, network management, and autonomous systems. Labs/Teams: Leads the Complex Adaptive Systems Group, focusing on interdisciplinary approaches to complex systems and swarm intelligence.

Mikael Eklundمشاهده پروفایل

استاد

• Autonomous Systems
• Nonlinear System Identification and Control
• Health Informatics
• +۳ مورد دیگر

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.

Cristiano Politowskiمشاهده پروفایل

استادیار

• Software Engineering
• Video Game Development
• Artificial Intelligence for Software Engineering (AI4SE)
• +۳ مورد دیگر

Cristiano Politowski is an Assistant Professor in the Department of Computer Science at Ontario Tech University's Faculty of Science. His research focuses on software engineering for video games, automated testing, AI4SE, and empirical studies. He holds a Ph.D. in Software Engineering from Concordia University (2022), an M.Sc. in Computer Science from Universidade Federal de Santa Maria (2017), and a B.Sc. in Computer Science from Universidade Regional do Estado do Rio Grande do Sul (2014). Prof. Politowski has extensive postdoctoral experience at Université de Montréal (GEODES group) and École de Technologie Supérieure (ÉTS), focusing on game engine architecture, requirements specification, and certifiable RTOS systems. He has organized workshops like ASE4Games 2021/2022 and FaSE4Games 2024, emphasizing game software engineering. His research interests span video game development challenges, software testing methodologies, and leveraging AI for software engineering. Notable projects include analyzing game engine subsystem coupling, assessing video game balance with autonomous agents, and curating datasets like PlayMyData. Prof. Politowski has secured $20K from MITACS for a 5G infrastructure project during the pandemic and received the Concordia Accelerator Award (2021). His work has been published in venues like MSR, ICSE, and IEEE Transactions.

Fabian Parschمشاهده پروفایل

استادیار

• Quantitative Differential Geometry
• Topology

Fabian Parsch is an Assistant Professor in the Department of Mathematics at the University of Toronto. He holds a PhD in Mathematics (2019) and has been recognized for his teaching excellence through multiple awards, including the Best First Year Instructor Award and Ida Bulat Teaching Award. His research focuses on Quantitative Differential Geometry and Topology , particularly geodesic nets and varifolds. His work bridges theoretical exploration with computational approaches, as evidenced by his publications in the Journal of Differential Geometry and Experimental Mathematics. He has received prestigious accolades like the Vanier Canada Graduate Scholarship and actively contributes to academic governance as a member of the University of Toronto Academic Board (2020–2023). Fabian also combines his mathematical expertise with software development, having founded SAMS-ON GmbH in 2005.

Nashid Shahriarمشاهده پروفایل

استادیار

• Computer Networks
• 5G Mobile Networks
• Resource Allocation
• +۵ مورد دیگر

Nashid Shahriar is an Assistant Professor in the Department of Computer Science at the University of Regina, Faculty of Science. His research addresses resource allocation challenges in next-generation networks including 5G, elastic optical networks, cloud infrastructures, and IoT systems. He holds a Ph.D. in Computer Science from the University of Waterloo, an M.Sc. from Bangladesh University of Engineering and Technology (BUET), and a B.Sc. from BUET. His work leverages optimization, machine learning, and AI for network management. Recent publications focus on 5G network slicing, intrusion detection, and NFV security. Research emphasizes practical AI-driven solutions for telecommunications and cloud systems.

William D. Bishopمشاهده پروفایل

دانشیار

• Engineering Education
• Configurable Computing
• Parallel and Distributed Systems
• +۵ مورد دیگر

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

Mohamed Elamienمشاهده پروفایل

استادیار

• Circuit Theory
• CMOS Integrated Circuits
• Analog and Mixed-Signal Circuit Design
• +۷ مورد دیگر

Dr. Mohamed Elamien is an Assistant Professor in the Department of Electrical and Computer Engineering at McMaster University . His research focuses on automating high-performance integrated circuit (IC) design, addressing Power-Performance-Area (PPA) challenges in semiconductors, and developing self-powered platforms for emerging technologies like biomedical and IoT applications. He holds a BSc (Highest Honors) and MSc from the University of Sharjah (2015–2017), and a PhD in Electrical and Computer Engineering from the University of Calgary (2021). Prior to academia, he worked as a senior analog/mixed-signal circuit design engineer at Synopsys (2022). Education: BSc (Highest Honors) in Electrical & Electronics Engineering – University of Sharjah (2015) MSc in Electrical & Electronics Engineering – University of Sharjah (2017) PhD in Electrical & Computer Engineering – University of Calgary (2021) His research interests span analog and mixed-signal circuit design , CMOS integrated circuits , biomedical technologies , and energy-efficient systems . He has developed innovative designs for oscillators, filters, and low-power circuits with applications in IoT and healthcare. His work emphasizes automation and symbolic math tools to streamline circuit synthesis. Dr. Elamien has published extensively in top-tier journals like IEEE Transactions on VLSI Systems and IEEE Transactions on Microwave Theory and Techniques , focusing on topics such as all-pass filters , low-power oscillators , and AI-driven circuit design . His articles often address challenges in high-frequency communication systems and noise reduction . Awards: Alberta Innovates Graduate Student Award (2020 – Technology Category) Alberta Graduate Excellence Scholarship (2019–2020) 2022 Schulich School of Engineering Graduate Student Research Excellence Award He currently teaches ELECENG 2CJ4: Circuits and Systems and ELECENG 3TP3: Signals and Systems , emphasizing advanced circuit analysis and systems theory. His lab explores next-generation circuit architectures for energy-efficient and biomedical applications.

Carson Leungمشاهده پروفایل

استاد

• Big Data Science
• Data Mining
• Machine Learning
• +۵ مورد دیگر

Dr. Carson Kai-Sang Leung is a Full Professor in Computer Science at the University of Manitoba's Faculty of Science. He founded and directs the Database & Data Mining Lab. His research focuses on big data science, data mining, machine learning, health informatics, and visual analytics. He holds SMIEEE and SMACM fellowships, reflecting his contributions to the field. Education: B.Sc., M.Sc., and Ph.D. from the University of British Columbia (UBC). Research interests include human-centered exploratory data mining, image databases, and scalable algorithms. He emphasizes user-driven constraints in mining processes and has developed techniques like the segment support map and OSSM for optimized frequency counting. His work on subimage queries in large image databases addresses real-world challenges in visual data retrieval. Publications span data mining, healthcare analytics, and transportation systems. His lab collaborates on projects like visual analytics for motor vehicle accidents and environmental data science for smart cities. He is affiliated with institutions such as the Institute of Industrial Mathematical Sciences (IIMS) and TRLabs. Key awards: Senior Member of IEEE (SMIEEE) and Senior Member of ACM (SMACM).

Patrick Haydenمشاهده پروفایل

پژوهشگر ارشد

• Quantum Information Science
• Quantum Communication
• Quantum Cryptography
• +۲ مورد دیگر

Patrick Hayden is a Research Fellow in the Department of Physics at Stanford University specializing in Quantum Information Science, focusing on communication protocols for large-scale quantum information processing including noise-resistant quantum state transmission and cryptographic protection methods. Education: PhD in Physics from Oxford University BSc in Mathematics and Physics from McGill University His research expertise spans quantum information theory with emphasis on: Reliable quantum communication through noisy media Quantum encryption against unauthorized manipulation Minimizing communication in multi-party quantum processing Publications demonstrate foundational contributions to quantum cryptography and information theory, particularly in uncertainty relations and quantum commitment protocols. Awards: Outstanding Young Computer Science Researcher Prize, Canadian Association of Computer Science (2011) Sloan Research Fellowship (2007) No information is available regarding students advised or research grants secured by Hayden. He is affiliated with Stanford's Quantum Information Science research group, building on early high-school work at Quantum Software Systems which presaged his current research focus.

Yves Blaquièreمشاهده پروفایل

استاد

• Microelectronics
• VLSI and ASIC Design
• FPGA-Based Systems
• +۶ مورد دیگر

Yves Blaquière is a Professor in the Department of Electrical Engineering at École de Technologie Supérieure. He is affiliated with the Communications and Microelectronic Integration Laboratory (LaCIME), focusing on microelectronics, integrated circuit design, and power integrity in advanced electronic systems. His research spans VLSI/ASIC design, FPGA-based reconfigurable computing, MEMS for avionics, and radiation effects on electronics. Aeronautics and Aerospace Intelligent and Autonomous Systems Microelectronics and VLSI Power Integrity Modeling MEMS Switch Design Radiation-Resilient Circuits His recent publications highlight innovations in GHz-range power integrity for SiP, FPGA-based SHEPWM inverters, and MEMS switches for avionic power systems. Collaborations with researchers like Frédéric Nabki and Nicolas Constantin reflect his focus on industrial applications and technology transfer. Professor Blaquière co-supervises PhD candidates including Hachem Bensalem, Gabriel Nobert, and Abdurrashid Hassan Shuaibu, covering topics such as heterogeneous optimization, power converter modeling, and MEMS switch development. His work contributes to wafer-scale prototyping platforms like WaferBoard and advanced tools for radiation testing in FPGAs. LaCIME, under his involvement, emphasizes equity, diversity, and inclusion, offering students opportunities to engage in cutting-edge projects from materials to communication protocols. The lab's expertise includes micro/nanofabrication, photonic microsystems, and signal processing.

Andrej Bogdanovمشاهده پروفایل

استاد

• Cryptography
• Computational Complexity
• Pseudorandomness
• +۶ مورد دیگر

Andrej Bogdanov is a Professor at the University of Ottawa in the School of Electrical Engineering and Computer Science . He earned his B.S. and M.Eng. from MIT and Ph.D. from UC Berkeley . Before joining Ottawa, he held positions at the Chinese University of Hong Kong , ITCS (Tsinghua) , DIMACS (Rutgers) , and the Institute for Advanced Study . He has served as a Visiting Professor at the Tokyo Institute of Technology (2013) and the Simons Institute (2017, 2021). Research Interests : Computational complexity, cryptography foundations, pseudorandomness, one-way functions, property testing, quantum algorithms, and sublinear-time algorithms. Teaching : Courses on Discrete Mathematics, Great Algorithms, Computational Complexity, and Cryptography at University of Ottawa, Chinese University of Hong Kong, and Rutgers University. Publications : 15+ recent works in TCC , CRYPTO , ICALP , RANDOM , and journals like Journal of Cryptology and Theory of Computing . Service : Program co-chair for SAC 2026 , and committee member for major conferences including CRYPTO , TCC , Eurocrypt , and FOCS . Advising : 12 current and former Ph.D./M.Phil. students, with postdoctoral advisees at institutions like IIT Palakkad and Academia Sinica . His work bridges theoretical computer science with applications in cryptography, quantum computing, and network security.