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Rong Zheng is a Professor in the Department of Computing and Software and a member of the School of Biomedical Engineering at McMaster University, Canada. She holds a Tier-1 Canada Research Chair in Mobile Computing and serves as Acting Chair of the Computing and Software department from July to December 2025. She is also an Associate Member of the Electrical & Computer Engineering department. Education: Ph.D. in Computer Science, University of Illinois, Urbana-Champaign, USA Master of Engineering (thesis) in Electrical Engineering, Tsinghua University, Beijing, China Bachelor of Engineering in Electrical Engineering, Tsinghua University, Beijing, China Dr. Zheng's research lies at the intersection of mobile computing, wireless networking, and machine learning, with a strong focus on applications for aging populations. She directs the NSERC Smart Mobility for the Aging Population CREATE program. Her work encompasses sensor development, wireless network design, and mobile data analytics to address real-world challenges in healthcare, mobility, and data center monitoring. She has developed innovative solutions like the MacQuest campus navigation app and has captured first prize in indoor localization competitions. Her recent publications demonstrate a clear trajectory toward applying wireless sensing technologies (particularly acoustic, Wi-Fi, and mmWave) to health monitoring and mobility assessment for older adults. There's a strong emphasis on developing efficient edge computing solutions that can process data in real-time on resource-constrained devices, as exemplified by her TeamNet framework for collaborative inference on the edge. Her work bridges theoretical advances with practical applications that have social impact. Scientific Awards: Tier-1 Canada Research Chair in Mobile Computing US National Science Foundation CAREER Award (2006) Joseph Ip Distinguished Engineering Fellow (2015-2018) Dr. Zheng leads the Wireless System Research Group (WiSeR) at McMaster University, which has secured significant funding including a $1.65M NSERC CREATE grant for smart mobility research for older adults. Her research has been supported by multiple funding agencies including NSERC, NSF, UH GEAR, and DURIP. She actively mentors graduate students and has developed specialized courses including CAS 772 (Mobile Data Analytics) and CAS 781 (Mobility in the Aging Population). The WiSeR group conducts impactful research on communication, networking, and data analytics issues in Cyber Physical Systems, with applications spanning healthcare, smart infrastructure, and data center monitoring. Their work on data center infrastructure monitoring networks has been featured in EurekAlert and Data Center Dynamics, and they've made significant contributions to indoor localization technology.

• Mobile computing
• Wireless networking
• Cyber physical systems
• +4 more

Maite Taboada is a Distinguished Professor in the Department of Linguistics at Simon Fraser University (SFU), directing the Discourse Processing Lab. She is also an Associate Member of the Cognitive Science Program and School of Computing Science, and affiliated with the Digital Democracies Institute and Visual and Interactive Computing Institute. Her research bridges discourse analysis and computational linguistics, focusing on mechanisms of coherence, discourse parsing, and sentiment analysis. Key projects include analyzing online news comments (SOCC corpus), detecting misinformation (MisInfoText), and monitoring gender representation in media (Gender Gap Tracker/Radar de Parité). Notable research interests span toxic language detection, constructive dialogue systems, and interdisciplinary work between social sciences and engineering. She has led projects funded by SFU and collaborated with organizations like Informed Opinion. Her awards include Fellowship in the Royal Society of Canada. Key contributions include developing the SFU Opinion and Comments Corpus, systems for comment moderation, and frameworks for gender bias analysis using topic modeling. Her work integrates theoretical discourse analysis with applied computational methods, addressing societal challenges like media bias and misinformation.

• Discourse Analysis
• Computational Linguistics
• Natural Language Processing
• +3 more

Florian Shkurti is an Assistant Professor in the Department of Computer Science at the University of Toronto Mississauga (UTM), affiliated with the UofT Robotics Institute, Vector Institute, and Acceleration Consortium. His research focuses on robotics, machine learning, and computer vision, emphasizing safe and effective autonomous systems in dynamic environments. He directs the Robot Vision and Learning (RVL) lab, exploring areas like environmental monitoring, autonomous navigation, and mobile manipulation. Research Interests: His work spans robotics, machine learning, and computer vision. Key areas include robot perception, planning under uncertainty, safe exploration, imitation learning, and applications in field robotics, autonomous vehicles, and chemistry lab automation. He develops methods enabling robots to perceive, reason, and act safely in collaboration with humans. Publications: Recent work includes advancements in safe multitask learning, interactive crowd navigation, and diffusion models for trajectory planning. His research bridges theoretical foundations with real-world applications in environmental science and autonomous systems. Affiliations: Faculty Member, UofT Robotics Institute; Faculty Affiliate, Vector Institute; Faculty Member, Acceleration Consortium. He also holds positions at UTM's Mathematical & Computational Sciences department. Teaching: Courses include Imitation Learning for Robotics, Neural Networks, and Mobile Robotics. He emphasizes hands-on experience with autonomous systems through projects involving RC cars and simulation tools. Labs & Teams: Leads the RVL lab, collaborating on projects like RoboCulture (automated biological experimentation) and SICNav (safe crowd navigation systems). The lab focuses on cross-disciplinary robotics solutions for real-world challenges.

• Robotics
• Machine Learning
• Computer Vision
• +6 more

Dr. Saeed Gazor is a full Professor in the Department of Electrical and Computer Engineering at Queen's University. He holds a cross-appointment in the Department of Mathematics and Statistics. His research focuses on signal processing applications in electrical energy systems, communications, and medical imaging. He has supervised postdoctoral fellows Babak Ghaffari and Yaser Esmaeili Salehani. Professional affiliations include Senior Member IEEE and membership in the Institution of Engineering and Technology. Education: PhD (1994) in Signal and Image Processing from Télécom ParisTech; M.Sc. (1989) and B.Sc. (1987) from Isfahan University of Technology with highest honors. Academic roles include former Assistant Professor at Isfahan University of Technology (1995–1998) and research associate at University of Toronto (1999). Research interests span detection theory, smart energy systems, hyperspectral imaging, and medical signal processing. Notable contributions include innovations in radar signal processing, sparse signal reconstruction, and adaptive filtering. Active in academic service, including editorial roles in IEEE journals. Awards: Professional Engineer designation from Professional Engineers Ontario. Over 200 peer-reviewed publications with recent focus on AI-driven hyperspectral analysis, robust beamforming, and energy-efficient communication systems. Labs/Teams: Leads signal processing research initiatives at Queen's, collaborating on projects involving smart energy grids, distributed radar networks, and biomedical signal analysis. Current work emphasizes integrating deep learning with traditional signal processing techniques.

• Signal Processing
• Electrical Energy Systems
• Communications and Networks Technologies
• +7 more

Nicola Nicolici is a Professor in the Department of Electrical and Computer Engineering at McMaster University. His research focuses on methods and algorithms for the design of digital integrated circuits and systems, with significant contributions in manufacturing test, post-silicon validation and debug. His work has expanded to include embedded systems, low-energy computing, and custom hardware-accelerated computing systems. Professor Nicolici's research interests span multiple areas of digital system design and validation. His early work focused on manufacturing test methodologies and power-aware testing strategies for integrated circuits. More recently, he has made significant contributions to post-silicon validation techniques, including constrained-random stimuli generation, trace signal selection, and bit-flip detection. His research has evolved to address emerging challenges in embedded computing systems, low-energy design, and specialized hardware acceleration for various applications including deep neural networks and signal processing. His recent publications reveal a strong trend toward hardware acceleration for specialized computing tasks. The research spans matrix multiplication algorithms (Strassen and Karatsuba), memory system optimization (DDR5 calibration), FPGA-based radar processing, and neural network acceleration. His work consistently bridges theoretical algorithm development with practical hardware implementation considerations, particularly focusing on precision analysis, fault tolerance, and energy efficiency. The research demonstrates a clear progression from traditional digital circuit testing to more complex system-level validation and acceleration techniques. Professor Nicolici has been actively involved in teaching courses related to system-on-chip design and test, digital systems, and embedded systems. His teaching portfolio includes advanced courses such as System-on-Chip (SOC) Design and Test and Digital Systems Design , reflecting his expertise in the field. While specific grant information isn't detailed in the provided text, his extensive publication record suggests ongoing research funding support. His research has contributed significantly to the fields of digital circuit testing, post-silicon validation, and hardware acceleration. The work has practical applications in semiconductor manufacturing, embedded systems design, and specialized computing architectures. His recent focus on neural network acceleration and memory system optimization reflects the evolving landscape of computer architecture research.

• Digital Integrated Circuit Design
• Hardware Testing
• Post-Silicon Validation
• +7 more

Dr. Marzieh Amini is an Associate Professor at Carleton University, cross-appointed to the School of Information Technology and Department of Systems and Computer Engineering . She coordinates the Optical Systems and Sensors undergraduate program and leads research in computer vision, sensor fusion, and biomedical signal processing . PhD in Electrical and Computer Engineering (2016), Concordia University Postdoctoral Fellow (2020), McGill University Research Interests focus on autonomous vehicle perception systems integrating machine learning and statistical modeling . Her work addresses multi-sensor integration for reliable operation in diverse environments, including biomedical applications and critical infrastructure monitoring . Recent publications emphasize wildfire management , LiDAR-based infrastructure monitoring , and adverse weather adaptation in autonomous systems . She has received grants from NSERC, NRC, and FRQNT . Honors & Awards include: Volunteer Recognition Awards (IEEE Montreal, 2022 & 2019) FRQNT Postdoctoral Fellowship (2018) IEEE ISCAS Travel Support (2016) Professional Service includes leadership roles in IEEE committees and conference organization.

• Computer Vision
• Sensor Fusion
• Autonomous Vehicles
• +7 more

Jean-François Frigon is a Full Professor in the Department of Electrical Engineering at Polytechnique Montréal, specializing in wireless communication systems and signal processing. His research spans adaptive systems, MIMO technologies, and energy-harvesting networks. Research Focus: Wireless communications, signal processing algorithms, and MIMO systems Collaborations: LORLAB, IVADO, POLY-GRAMES, GERAD Recent Publications: 15+ articles on topics including regenerative satellite payloads, machine learning for beamforming, and mmWave system optimization. His work emphasizes AI integration in 5G/6G and sustainable wireless solutions. Awards: Recipient of NSERC Discovery Grant funding in 2022. Collaborated with Ericsson on AI-driven 5G sustainability projects. Lab Affiliations: Active in LORLAB (Laboratoire de recherche en radiocommunications) and POLY-GRAMES microwave research center.

• Wireless Communications
• Signal Processing
• Adaptive Systems
• +3 more

Catherine Neish is an Associate Professor in the Department of Earth Sciences at The University of Western Ontario. She serves as the Associate Director of Research for Western Space and is a Co-Investigator on NASA's Dragonfly mission to Titan. Her research focuses on planetary radar observations, impact cratering processes, and the geological evolution of planetary surfaces, particularly on the Moon, Titan, and other Solar System bodies. Ph.D. in Planetary Sciences, University of Arizona (2008) B.Sc. in Combined Honours Physics and Astronomy, University of British Columbia (2004) Her recent publications highlight studies on lunar impact crater thermophysics, Titan's impact melt dynamics, and radar-based analyses of planetary surfaces. She has contributed to missions including Lunar Reconnaissance Orbiter (Mini-RF), Cassini RADAR, and Dragonfly. Scientific Awards: College of New Scholars, Royal Society of Canada (2021) Early Researcher Award, Ontario (2017) Minor Planet 16972 Neish (2017) AGU Ron Greeley Award (2014) NASA Postdoctoral Fellowship (2012) NASA Group Achievement Award (2010) NSERC Postgraduate Scholarship (2005-2008) Julie Payette-NSERC Research Scholarship (2004-2005) Dr. Neish supervises a dynamic lab with current and former students investigating planetary geology, impact cratering, and remote sensing. Her work bridges field studies (e.g., Earth analogs), laboratory experiments, and spacecraft data analysis.

• Planetary Science
• Radar Geology
• Impact Cratering
• +3 more

Jagath Samarabandu is a Professor in the Department of Electrical and Computer Engineering at Western University. He holds a Ph.D. and M.S. in Electrical Engineering from SUNY Buffalo, and a B.Sc. in Electronics and Telecommunication Engineering from the University of Moratuwa, Sri Lanka. His academic career spans since joining Western University in 2000, with prior post-doctoral experience at SUNY Buffalo and industry work at Life Imaging Systems Inc. Education: Ph.D. Electrical Engineering, SUNY Buffalo M.S. Electrical Engineering, SUNY Buffalo B.Sc (Eng) Electronics and Telecommunication, University of Moratuwa His research focuses on Artificial Intelligence, Machine Learning, Image Analysis, and Cyber Security , with applications in biomedical imaging, network intrusion detection, and civil infrastructure monitoring. He has supervised numerous graduate students working on topics ranging from chromosome analysis to smart grid security. Recent publications highlight his work in medical AI applications (auditory processing disorder diagnosis), industrial time-series analysis (using contrastive predictive coding), and network security frameworks (INSecS system development). He has contributed to 3D ultrasound segmentation, prostate motion compensation algorithms, and synthetic aperture radar systems. Key projects include NSERC-funded intelligent home monitoring systems for elderly care and low-cost synthetic aperture radar development for search-and-rescue applications.

• Artificial Intelligence
• Explainable AI
• Machine Learning
• +5 more

Keyvan Hashtrudi-Zaad is a Professor in the Department of Electrical and Computer Engineering at Queen's University, affiliated with the Smith School of Engineering and the Ingenuity Labs Research Institute. His expertise spans robotics and control systems, with a focus on haptics, telerobotics, tele-rehabilitation, autonomous vehicles, and medical robotics. He holds the email addresses keyvan.hashtrudi-zaad@queensu.ca and khz@queensu.ca, and his office is located in Walter Light Hall, Room 427. Research Interests: His research emphasizes human-robot interaction, haptic interfaces, autonomous systems, and mechatronics. Key areas include kinesthetic haptics, collaborative teleoperation systems, energy storage systems for electric vehicles, and medical robotics applications such as needle deflection estimation and rehabilitation robotics. His work bridges theoretical control systems with practical applications in healthcare and autonomous technologies. Publications: His recent work addresses challenges in haptic system stability, energy-efficient inverters for electric vehicles, and teleoperation networks. Notable projects include a cable-driven parallel robot for stroke rehabilitation and a study comparing DC/BLDC actuators for haptic feedback. His research often integrates sensor fusion, nonlinear control, and dynamic modeling to solve real-world problems. Awards and Recognition: While specific awards are not listed, his extensive publication record and leadership in interdisciplinary robotics initiatives highlight his contributions to the field. He is part of the Interactive Robotics and Intelligent Systems (IRIS) Laboratory, advancing innovations in medical robotics and autonomous systems. Grants and Collaborations: His work likely involves collaborations across engineering and medical disciplines, supported by grants focused on robotics, control systems, and healthcare technologies. The IRIS Lab serves as a hub for developing cutting-edge solutions in haptic training systems and assistive robotics.

• Haptics
• Telerobotics
• Tele-rehabilitation
• +5 more

Dr. Yun Zhang is a Professor and Canada Research Chair in the Department of Geodesy and Geomatics Engineering at the University of New Brunswick. He holds a PhD from the Free University of Berlin and has pioneered research in remote sensing, image processing, and computer vision since 2000. His patented technologies are licensed to global companies including PCI Geomatics and DigitalGlobe. Research Focus: Optical/radar image processing, digital photogrammetry, AI applications in geomatics, and sensor fusion for UAV systems. His work enables advanced geospatial analysis across environmental, urban, and defense sectors. Distinctions: First Giuseppe Inghilleri Award (ISPRS 2012) NSERC Synergy Innovation Award from Governor General of Canada (2011) ASPRS Talbert Abrams Grand Award (2005) Featured in CFI 20th Anniversary Book for breakthrough innovations Technology Impact: Solutions deployed by NASA, USGS, Google Earth, and DND Canada across five continents. Recognized among top 9 Canadian research achievements in AUTM's global case studies alongside MIT and Stanford innovations.

• Remote Sensing
• Image Processing
• Computer Vision
• +4 more

Benoit Champagne is a Full Professor in the Department of Electrical and Computer Engineering at McGill University, Montreal. His research focuses on statistical signal processing, with applications in wireless communications, multi-antenna systems, and adaptive filtering. He has held academic positions since 1990, including roles at INRS-Telecom before joining McGill in 1999. He teaches graduate and undergraduate courses such as ECSE 305 (Probability and Random Signals), ECSE 512 (Digital Signal Processing), and ECSE 617 (Array Signal Processing). Education: B.Eng. (Electrical Engineering) and M.Sc. (Physics) from Université de Montréal (1983, 1985), Ph.D. in Electrical Engineering from University of Toronto (1990). His research spans signal detection/estimation, speech enhancement, MIMO systems, and physical layer security, with over 150+ publications in top journals and conferences. He has supervised numerous graduate students and holds grants from NSERC, CFI, and industry partners like Nortel and Bell Canada. His work emphasizes practical implementations, including hybrid analog/digital beamforming for mmWave systems and energy-efficient resource allocation in D2D communications. He has contributed to IEEE standards through editorial roles (e.g., IEEE Transactions on Signal Processing) and conference organization (e.g., IEEE VTC 2016). Current research explores machine learning integration with signal processing for next-generation wireless systems. Notable contributions include advancements in subspace tracking, cognitive radar systems, and distributed adaptive filtering. His lab collaborates internationally, addressing challenges in 5G/6G networks, massive MIMO, and secure communications.

• Statistical Signal Processing
• Multi-antenna Processing
• Signal Detection and Estimation
• +9 more

Sorin P. Voinigescu is a Professor in the Department of Electrical and Computer Engineering at the University of Toronto's Faculty of Applied Science and Engineering. He joined the university in 2002 and has been a full professor since 2007. His industrial experience includes roles at Nortel Networks and as CTO/co-founder of Quake Technologies (acquired by AMCC). He co-founded Peraso Technologies Inc. (NASDAQ-listed) in 2008. Education: M.Sc. in Electronics, Polytechnic Institute of Bucharest (1984) Ph.D. in Electrical and Computer Engineering, University of Toronto (1994) His research investigates nano-scale devices, integrated circuits, and systems operating beyond 500 GHz, with applications in quantum computing, telecommunications, radiometry, and sensing. Current research themes include: Elevated-temperature monolithic quantum processors in silicon Terahertz sampling techniques for analog/mixed-signal processing mm-wave radios, sensors, radars, and imagers Energy-efficient Tb/s photonic transceivers Awards and Honors: NORTEL’s President Award for Innovation (1996) Best Paper Award, IEEE CICC (2001) Best Paper Award, IEEE CSICS (2005) Beatrice Winner Award, IEEE ISSCC (2008) Fellow of the IEEE He advises 10+ graduate students (PhD and MASc candidates) and has supervised over 30 alumni. Research is supported through industry collaborations and access to leading semiconductor technologies. He directs the mm-wave and THz Integrated Circuits Research Group, operating an advanced test lab with DC-700 GHz measurement capability, cryogenic probe stations, and 120 Gb/s BERT equipment. The lab supports quantum processor characterization and mm-wave system development.

• Quantum Computing
• Terahertz Electronics
• Millimeter-Wave Integrated Circuits
• +5 more

Joni Storie is an Associate Professor in the Geography Faculty at the University of Winnipeg. She holds an office in Lockhart Hall (5L05) and teaches courses including Mapping in a Global World, Intro Remote Sensing, Advanced GIS, and Advanced Remote Sensing. Her research focuses on land-use/land-cover mapping, map automation with machine learning tools, spatial statistics, and terrestrial/aquatic resource management. Teaching expertise spans Regional & Physical Geography, Resource Conservation & Management, and Geomatics (GIS & Remote Sensing). Her work integrates geospatial technologies with environmental challenges, including flood mitigation, mangrove ecosystem analysis, and food environment patterning in urban areas. Research outputs emphasize remote sensing applications in coastal conservation, surface water detection, and vegetation dynamics. Over 13 peer-reviewed articles since 2004 demonstrate sustained academic contributions to geomatics and environmental geography. Current activities include advising on geomatics projects and contributing to the University of Winnipeg’s Geography program infrastructure.

• Geomatics
• Remote Sensing
• GIS
• +6 more

George Shaker is an Adjunct Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Canada, and Lab Director of the Wireless Sensors and Devices Laboratory at the Schlegel-UW Research Institute for Aging. He is also Chief Scientist at Spark Technology Labs. His research focuses on wireless sensor technologies for healthcare, autonomous systems, and IoT. He earned his bachelor's from Cairo University and master's/PhD from the University of Waterloo. Education: Bachelor’s degree, Cairo University, Egypt Master’s degree, University of Waterloo, Canada PhD, University of Waterloo, Canada Research Interests: Dr. Shaker’s work spans advanced wireless sensor systems for healthcare monitoring, UAVs, and automotive applications. His lab developed the MIRADA initiative for aging populations and pioneered radar-based non-invasive glucose monitoring. Key areas include mm-wave radar, antenna design, bioelectromagnetics, and machine learning integration. He has co-authored over 200 publications and holds 35+ patents, collaborating with companies like Google, Apple, and Toyota. Recent Article Trends: His 2025 work emphasizes AI-driven radar systems for activity recognition, bio-sensing metasurfaces, and UAV classification using digital twins. Projects include 4D radar imaging, low-cost milk quality monitoring, and smart furniture for cardiac health. Awards: IEEE AP-S Best Paper Award IEEE MTT-S Graduate Fellowship arXiv Top Downloaded Medical Article URSI Young Scientist Award Multiple student awards (see full list above) Advising & Grants: He advises graduate students in ECE and has led projects funded by NSERC and industry partners. His students have won Velocity Fund, NASA Tech Briefs, and Canadian Space Agency awards. Collaborates with over 40 companies including Amazon, Microsoft, and Medella Health. Labs & Initiatives: Leads the Wireless Sensors & Devices Lab and co-founded MIRADA, a smart apartment for aging healthcare. Active in Spark Labs for wireless innovation.

• Wireless Sensor Technologies
• Biomedical Engineering
• Antennas and Propagation
• +5 more