جستجوی استاد راهنمای دانشگاهی

Nir Rotenbergمشاهده پروفایل

دانشیار

• Quantum Photonics
• Nanophotonics
• Quantum Optics
• +۳ مورد دیگر

Dr. Nir Rotenberg is an Associate Professor in the Department of Physics, Engineering Physics, and Astronomy at Queen's University. He is affiliated with the Faculty of Arts and Science, the Condensed Matter Physics & Optics group, and the Centre for Nanophotonics. He holds a PhD from the University of Toronto and focuses on quantum photonics and nanophotonics, particularly exploring nonlinear phenomena in solid-state quantum systems. His lab develops novel quantum devices and circuits using nanophotonic platforms, emphasizing single quantum emitter interactions with few photons. Research Interests: Quantum photonics, nanophotonics, quantum optics, nonlinear optics, quantum devices, and solid-state quantum emitters. His work bridges fundamental physics with applications in quantum information processing and photonic technologies. Recent publications highlight advancements in quantum dot positioning, waveguide-QED systems, and reconfigurable photonic circuits. He collaborates internationally and is a member of the Quantum Nanophotonics Lab (QNL), based in Stirling 308H. Dr. Rotenberg's research has implications for quantum computing, secure communication, and advanced optoelectronic systems.

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.

Shahin Kamaliمشاهده پروفایل

دانشیار

• Algorithms Design
• Algorithms Analysis
• Online Algorithms
• +۹ مورد دیگر

Shahin Kamali is an Associate Professor in the Department of Electrical Engineering & Computer Science at York University's Lassonde School of Engineering. Previously, he served as an Assistant Professor at York University (2022-2024) and the University of Manitoba (2017-2022), where he continues to hold an Adjunct Professor position. He completed his Ph.D. in Computer Science at the University of Waterloo in 2014 and was a postdoctoral fellow at MIT's CSAIL lab from 2015-2017. Dr. Kamali received his B.Sc. from the University of Tehran and his M.Sc. from Concordia University, both in Computer Science. He has earned teaching certifications including the Kaufman Teaching Certificate Program from MIT and the Certificate in University Teaching from the University of Waterloo. His research focuses on algorithms' design, analysis, and limitations, with particular emphasis on online problems such as bin packing, paging, list update, and k-Server. His work extends to big-data applications of algorithms in data compression, graph partitioning, resource allocation in the cloud, and algorithmic aspects of blockchain technology. His recent publications (2023-2025) demonstrate a strong focus on learning-augmented algorithms, online computation with predictions, and novel applications in blockchain and graph theory. His research has been supported by multiple NSERC grants since 2010, with recent projects investigating models, applications, and limitations of online algorithms. He has successfully supervised numerous graduate students and serves on various committees related to algorithms conferences and academic governance. University of Waterloo Doctoral Thesis Completion Award (2014) University of Waterloo Mathematics Graduate Experience Award (2008) Dr. Kamali teaches advanced courses in algorithms and data structures and is scheduled to teach Design and Analysis of Algorithms (EECS 3101) in Fall 2025 and Advanced Data Structures (EECS 4101/5101) in Winter 2026. He is actively involved in organizing major conferences, including CCCG and WADS 2025 at York University.

Hatem Abou-Zeidمشاهده پروفایل

استادیار

• 5G/6G Wireless Communications
• Artificial Intelligence
• Immersive Communications
• +۴ مورد دیگر

Hatem Abou-Zeid is an Assistant Professor at the Department of Electrical and Software Engineering in the Schulich School of Engineering , University of Calgary. He holds Adjunct Professor appointments at Queen’s University, Carleton University, and Ontario Tech University, Canada. With a Ph.D. in Electrical and Computer Engineering from Queen’s University (2014), his academic journey includes 7 years of industry research at Ericsson and Cisco , where he led R&D projects resulting in 15+ patents. Queen's University (Ph.D., Electrical and Computer Engineering) Arab Academy for Science, Technology and Maritime Transport (B.Sc. and M.Sc., Electronics and Communications Engineering) His research focuses on 5G/6G wireless networking , immersive communications , and robust machine learning for networks. Recent projects explore trustworthy AI , joint sensing and communication , and pediatric brain-computer interfaces (BCI) . He has published extensively in top venues like IEEE JSAC , GLOBECOM , and IEEE Transactions on Networking , with over 60 publications and 19 patent filings. His scientific awards include the Research Excellence Award 2023 (UCalgary), Early Research Excellence Award 2023 (Schulich), and Best Paper Awards at EMBC 2024 (as advisor) and IEEE ICC 2022 . He leads the WAVES Research Group , mentoring 10+ graduate students and postdocs. Collaborations span institutions like the Hotchkiss Brain Institute and industry partners such as Ericsson and European Space Agency .

Telex M. N. Ngatchedمشاهده پروفایل

دانشیار

• 5G and 6G enabling technologies
• Optical wireless communications
• Hybrid optical wireless and radio frequency communications
• +۲ مورد دیگر

Telex M. N. Ngatched is an Associate Professor in the Department of Electrical & Computer Engineering at McMaster University, where he has been since January 2023. Previously, he held positions as a Postdoctoral Fellow at the University of KwaZulu-Natal (2006-2007), Research Associate at the University of Manitoba (2008-2012), and faculty at Memorial University (2012-2022). He is currently accepting graduate students. Education: BSc in Electronics, University of Yaoundé, Cameroon MSc in Electronics, University of Yaoundé, Cameroon MScEng (Cum Laude) in Electronic Engineering, University of Natal, South Africa PhD in Electronic Engineering, University of KwaZulu-Natal, South Africa Research Interests: Dr. Ngatched's work spans next-generation wireless systems, including optical/RF hybrid communications, underwater networks, and AI/ML applications for 5G/6G infrastructure. His research addresses signal processing challenges and optimization methods for reconfigurable intelligent surfaces in smart environments. Awards & Honors: Grenfell Campus Research Award (2020) IEEE WCNC Best Paper Award (2019) Carnegie African Diaspora Fellowship (2016) South African Sugar Miller’s Teaching Award (2007) Professional Engineering licensure (P. Eng.) Professional Activities: He serves as Area Editor for IEEE Open Journal of the Communications Society, Associate Technical Editor for IEEE Communications Magazine, and organizes major IEEE conferences (e.g., VTC, GLOBECOM). Teaches courses on optical wireless communications, signals, and communication systems.

Vaughn Betzمشاهده پروفایل

استاد

• Field-Programmable Gate Arrays (FPGAs)
• Computer-Aided Design (CAD)
• Hardware Acceleration
• +۴ مورد دیگر

Vaughn Betz is a Professor in the Department of Electrical and Computer Engineering at the University of Toronto, Faculty of Applied Science and Engineering. He is also a Distinguished Visiting Professor at Cerebras Systems and Faculty Affiliate at the Vector Institute for Artificial Intelligence. His research focuses on creating efficient programmable hardware (FPGAs), computer-aided design (CAD) programs to optimize hardware systems, and hardware accelerators for compute-intensive applications like deep learning. He developed the widely used VPR FPGA CAD flow and co-founded Right Track CAD, acquired by Intel/Altera. Education BSc in Electrical Engineering, University of Manitoba (1991) M.S. in Electrical and Computer Engineering, University of Illinois at Urbana–Champaign (1993) PhD in Electrical and Computer Engineering, University of Toronto (1998) Research Focus Betz's research spans FPGA architecture innovation, CAD tool development, and hardware acceleration methods. Key areas include: Creating FPGA architectures optimized for deep learning inference Developing datacenter-friendly FPGAs with embedded NoCs Mapping deep learning applications to programmable hardware CAD tools for FPGA debugging and context switching Hardware acceleration for medical applications like photodynamic cancer therapy Awards and Honors Fellow of IEEE, NAI, and Engineering Institute of Canada Professional Engineers of Ontario Medal for Engineering Excellence (2016) 13 best/most significant paper awards NSERC/Intel Industrial Research Chair in Programmable Silicon Google Faculty Research Award (2020) Multiple teaching awards including Gordon R. Slemon Award (2016) Research Leadership Betz leads the Verilog-to-Routing (VTR) project and co-directs the Intel/Vmware Crossroads 3D FPGA Academic Research Centre. His research is sponsored by NSERC, Intel, Google, AMD, IBM, and others.

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.

Andy Yeمشاهده پروفایل

دانشیار

• Field-programmable gate array (FPGA) architectures
• Computer-Aided Design (CAD) tools for FPGAs
• Logic synthesis
• +۵ مورد دیگر

Dr. Andy Ye is an Associate Professor in the Department of Electrical, Computer, and Biomedical Engineering at Ryerson University, where he conducts research and teaches courses in advanced digital systems. Education : PhD (2004), MASc (1999), and BASc (1996) from the University of Toronto Research Interests focus on: Field-programmable gate array (FPGA) architectures Computer-Aided Design (CAD) tools for FPGAs and VLSI Logic synthesis and hardware implementation Digital communication algorithms and computer vision systems Publication Trends demonstrate expertise in FPGA area modeling, motion estimation architectures, and VLSI design optimization across multiple IEEE and ACM venues. Scientific Achievements : Best Paper Award (2016) at International Conference on Field Programmable Logic and Applications Teaching Contributions include graduate-level FPGA design (EE 8219), low-power digital circuits (ELE 734), and fundamental network theory (ELE 302). He maintains active supervision availability for students.

Christian Muiseمشاهده پروفایل

استادیار

• Artificial Intelligence
• Automated Planning
• Machine Learning
• +۶ مورد دیگر

Christian Muise is an Assistant Professor at Queen's University's School of Computing, part of the Faculty of Arts and Science. He holds a PhD (2014) in Artificial Intelligence from the University of Toronto, where he was advised by Sheila McIlraith and J. Christopher Beck. His research focuses on automated planning under uncertainty, combining planning with learning for applications like goal-oriented dialogue systems and multi-agent coordination. He previously held postdoctoral roles at the University of Melbourne's Agentlab and MIT's CSAIL, and was a Research Staff Member at the MIT-IBM Watson AI Lab. Education: PhD in Artificial Intelligence, University of Toronto (2014) MSc in Computer Science, University of Toronto (2009) BSc in Computer Science, Carleton University (2007) Research Interests: His work bridges automated planning and machine learning, emphasizing robustness in uncertain environments. Key areas include non-deterministic planning, model acquisition with large language models (LLMs), and human-aware planning. He explores applications in healthcare (e.g., treatment response prediction), robotics (autonomous navigation), and dialogue systems for safety-critical domains. Current projects include developing explainable planning systems and mitigating bias in AI decision-making. Awards: Scotiabank Scholar (Scotiabank Centre for Customer Analytics) Advising & Labs: Leads the Mu Lab, supervising PhD and Master's students in topics like model acquisition, dialogue systems, and planning bias. Active in open-source tools (e.g., L2P, MACQ library) to democratize planning research. Collaborates on projects like PRP Rebooted and FixMyPlan to advance FOND planning and LLM integration. Labs/Teams: Mu Lab at Queen’s University, focusing on planning under uncertainty, AI safety, and neuro-symbolic systems.

Daler N. Rakhmatovمشاهده پروفایل

دانشیار

• Reconfigurable architectures
• Energy-efficient computing
• Electronic design automation
• +۹ مورد دیگر

Daler N. Rakhmatov is an Associate Professor in the Electrical and Computer Engineering Department at the University of Victoria . His research focuses on energy-efficient computing architectures for biomedical imaging applications, including ultrasound systems and embedded systems optimization. He is also involved in hardware/software co-design and battery management systems. Education: Bachelor of Science (BSc) in Engineering, University of Rochester Master of Science (MSc) in Engineering, University of Arizona Doctor of Philosophy (PhD) in Engineering, University of Arizona Professional Engineer (PEng) designation Research Interests: Rakhmatov's work emphasizes four core areas: 1. Low-complexity biomedical ultrasound imaging techniques for energy efficiency. 2. Configurable hardware/software architectures for computation-intensive tasks. 3. Analytical models for battery dynamics in embedded systems. 4. Model-driven configuration algorithms for energy-constrained applications. Teaching: Rakhmatov teaches courses such as ECE 242 (Discrete Structures) , ECE 355 (Microprocessor Systems) , and advanced topics like ECE 568 (System-on-Chip Engineering) . Students & Alumni: Rakhmatov supervises PhD and MASc/MEng students in biomedical imaging and embedded systems. Notable alumni include: - Hamad Alrimeih (PhD, Cryptographic Hardware Acceleration) - Mohammed Albulayli (PhD, Ultrasound Imaging Reconstruction) - Solmaz Khezerloo (MASc, Gradient-Driven Beamforming) Labs & Collaborations: His research integrates with the University of Victoria's biomedical engineering and embedded systems communities. He is a member of the Cadence University Program .

Pirathayini Srikanthaمشاهده پروفایل

دانشیار

• Game Theory
• Large-scale Optimization
• Distributed Control
• +۵ مورد دیگر

Pirathayini Srikantha serves as Associate Professor in the Department of Electrical Engineering & Computer Science at York University's Lassonde School of Engineering, holding a Tier 2 Canada Research Chair in Reliable and Secure Power Grid Systems with critical national security implications for Canada's power infrastructure. Her academic foundation includes: B.A.Sc. in Systems Design Engineering from University of Waterloo (2009) M.A.Sc. in Electrical and Computer Engineering from University of Waterloo (2013) Ph.D. from University of Toronto's Edward S. Rogers Sr. Department of Electrical and Computer Engineering (2017) Professor Srikantha's research centers on game theory, large-scale optimization, and distributed control to enable adaptive power grid operations. Her work addresses cybersecurity vulnerabilities in smart grids through distributed coordination frameworks and develops transactive energy market mechanisms that incentivize grid support during congestion. By integrating AI breakthroughs, she focuses on creating systems that automatically infer, predict, and respond to power disturbances while enhancing infrastructure resilience against evolving threats. Her publication trajectory reveals consistent innovation in grid security and optimization, with increasing emphasis on AI-driven solutions for grid resilience since 2015. Key thematic evolution shows progression from foundational distributed control (2015-2017) to sophisticated cybersecurity applications (2018-2021), consistently appearing in premier venues like IEEE Transactions on Smart Grid. Her scholarly impact is recognized through: Best paper award at IEEE Smart Grid Communications Runner-up best poster award at ACM Women in Computing As Canada Research Chair holder, she directs a federally funded research program addressing critical grid vulnerabilities, while serving as Associate Editor for IEEE Transactions on Smart Grid. Her work bridges theoretical advances in game-theoretic security with practical grid applications, though specific student mentorship details aren't publicly enumerated in source materials. Her research group operates at the intersection of electrical engineering and computer science, developing next-generation tools for grid operators through collaborations with Canadian energy infrastructure stakeholders.

Gul N. Khanمشاهده پروفایل

استاد

• Embedded Systems
• Hardware/Software Co-design
• Network-on-Chip (NoC)
• +۷ مورد دیگر

Dr. Gul N. Khan is a Professor in the Department of Electrical, Computer and Biomedical Engineering at Toronto Metropolitan University (formerly Ryerson University). He has held academic positions at the University of Saskatchewan, Nanyang Technological University, RMIT University, and Quaid-i-Azam University. His career spans over three decades with a focus on embedded systems , network-on-chip (NoC) , and heterogeneous computing . Education: Ph.D. (Imperial College, 1989), M.Sc. (Syracuse University, 1982), B.Sc. (UET Lahore, 1979) Dr. Khan’s research interests include hardware-software co-design , CPU-GPU systems , fault-tolerant computing , and smart RFID systems . His work has led to over 125 refereed publications and three US patents. His recent publications highlight advancements in GPU auto-tuning , NoC synthesis , and digital time interpolators . Despite being listed in a Google Scholar block with unrelated public health topics, these appear to be errors, as his core expertise remains in computer engineering. Dr. Khan has supervised numerous graduate projects in embedded systems and SoC design . He served as Program Director for Computer Engineering from 2004–2015 and leads the Microsystems Research Lab at Toronto Metropolitan University.

Alagan Anpalaganمشاهده پروفایل

استاد

• Wireless Communication
• Radio Resource Management
• Green Communication
• +۷ مورد دیگر

Alagan Anpalagan is a Full Professor in the ELCE Department at Toronto Metropolitan University, previously Ryerson University. He holds a PhD in Electrical Engineering from the University of Toronto. His research focuses on radio resource management (RRM), green communication, IoT networks, and wireless communication systems. He directs the WINCORE Lab, specializing in radio access & networking (RAN) and cross-layer design. Dr. Anpalagan has authored/co-edited multiple books and holds IEEE Fellow status (2024). He has received awards including the Ryerson Sarwan Sahota Distinguished Scholar Award (2022) and the IEEE Canada Outstanding Engineering Educator Medal (2018). He has served in editorial roles for IEEE Communications Surveys & Tutorials and led industry collaborations with companies like Bell Mobility and IBM. Education: B.A.Sc. in Electrical Engineering, University of Toronto M.A.Sc. in Electrical Engineering, University of Toronto Ph.D. in Electrical Engineering, University of Toronto Research Interests: His work spans RRM, energy-efficient networks, cognitive communication, and smart grid technologies. Recent projects include digital twin applications in IoT and 6G-based user localization for emergencies. Publications: His 15 most recent articles include studies on network routing protocols, IoT scheduling with digital twins, and AI-driven disaster response systems. These reflect his focus on integrating AI and edge computing into next-gen communication systems. Awards: Recognized for both research and teaching excellence, including IEEE Fellowships and institutional awards for graduate education and service. Labs/Teams: Lead researcher at the WINCORE Lab, collaborating with academia and industry on wireless resource management and heterogeneous networks. The lab’s alumni network includes over 100 researchers.

• Parallel and Distributed Computing
• Database Systems
• Network-Centric Computing
• +۲ مورد دیگر

Professor Ajit Singh is a faculty member in the Department of Electrical and Computer Engineering at the University of Waterloo , affiliated with the Faculty of Engineering . His expertise spans Parallel and Distributed Computing , Database Systems , Network-Centric Computing , and Software Architecture and Design . Education: BSc (BIT, India) MPhil (Jawaharlal Nehru University, New Delhi) MSc and PhD (University of Alberta) Research & Industrial Work: Founded SlipStream Data (acquired by Research in Motion/BlackBerry) to accelerate internet content delivery on low-bandwidth networks. Consulted for IBM Canada, Bell Canada, Nortel, and other tech firms. Current projects include Energy Efficient Mobile Computing and Processing Data Streams . Advising & Students: Current advisees: Liton Chakraborty, Mohammad Mursalin Akon, Rajesh Palit, Tan Wang. Past students include Dhrubajyoti Goswami, Afzal Mawji, and others. Research Themes: Focuses on scalable caching, distributed systems, and energy-efficient computing. Explores disk-based optimization for stream joins and parallel architectures.

James Youngمشاهده پروفایل

استاد

• Human-Computer Interaction
• Human-Robot Interaction
• Robotics
• +۶ مورد دیگر

James Young is a Professor in the Department of Computer Science at the University of Manitoba, within the Faculty of Science. He holds a PhD and specializes in Human-Computer Interaction (HCI) and Human-Robot Interaction (HRI). His work focuses on designing socially intelligent robots, trust calibration in HRI, and ethical implications of robotic systems. He leads the HCI Lab, collaborating closely with Japanese robotics researchers, and has pioneered projects like the SnuggleBot companion robot and frameworks for robot capability labeling. Education: PhD in Computer Science Research interests include social robotics, teleoperation systems, and human-robot collaboration. He has explored applications in mental health support, disability inclusion, and cultural reconciliation through virtual reality. His lab emphasizes interdisciplinary approaches, combining engineering, psychology, and design principles. Current research includes designing anti-bullying interventions using robots, privacy-friendly robot interfaces, and exploring the societal impact of AI systems. He actively mentors graduate students in HCI and robotics, with funding opportunities for exceptional candidates. His work has been showcased in venues like HRI conferences and ACM publications, emphasizing both technical innovation and ethical considerations. Collaborations extend to international partnerships and industry applications in healthcare and education.