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Katherine ElviraView profile

Associate Professor

• Microfluidics
• Drug Discovery
• Artificial Cells
• +5 more

Dr. Katherine Elvira is an Associate Professor and Canada Research Chair (Tier 2) in Microfluidics for Drug Discovery and Healthcare at the University of Victoria's Department of Chemistry. Her research focuses on developing microfluidic technologies for drug discovery, artificial cells, and healthcare applications, emphasizing collaboration with industry and commercialization. She holds a PhD from Imperial College London and prior experience as a Senior Scientist at ETH Zürich. Education: PhD in Chemistry, Imperial College London Senior Scientist and Lecturer, ETH Zürich Research interests include lab-on-a-chip systems, artificial cell membranes, drug delivery systems, and biomimetic prototissues. Her work bridges chemistry, biology, and engineering, with projects ranging from drug discovery to food science (e.g., 'beer-on-a-chip'). Publications and projects highlight advancements in microfluidic device design (e.g., plug-and-play platforms) and biomimetic models for predicting drug behavior. Collaborations with industry include partnerships with Phillips Brewing and StarFish Medical. Awards: Canada Research Chair Tier 2 MSHRBC Scholar Emerging Investigator (Lab on a Chip, 2020) Teaching focuses on analytical chemistry and microfluidics. She advises graduate students and mentors postdocs, emphasizing interdisciplinary training. The Elvira Lab is equipped with advanced CFI-funded facilities and offers funded positions for 2025. Future work includes expanding artificial tissue models, optimizing PDMS alternatives, and fostering industry partnerships for commercializing microfluidic innovations.

Zhao ZhaoView profile

Assistant Professor

• Wearable Systems
• Human-Computer Interaction (HCI)
• Human-Robot Interaction (HRI)
• +4 more

Zhao Zhao is an Assistant Professor at the School of Computer Science, University of Guelph. Her work focuses on wearable systems, human-robot interaction, and gamification for health and education. She holds a PhD from Carleton University (2019) and completed a postdoctoral fellowship at the University of Toronto (2019–2023) before roles at McMaster University and her current position. Education includes a BSc in Computer Science from University of Electronic Science and Technology of China (2011), MSc from Carleton University (2014), and PhD in Electrical and Computer Engineering (2019). Research interests span physiological computing, AI-assisted creativity tools, and adaptive systems leveraging wearable sensors. Key research areas include: 1) Wearable-based gamification for health and education, 2) Emotion sensing via physiological signals, and 3) Human-robot interaction enhanced by wearable data. Her lab uses Empatica EmbracePlus wristbands and Emotiv EEG headsets to analyze real-time physiological responses in diverse interaction scenarios. Recent publications (2020–2025) emphasize personalized exergame systems, child-robot interaction studies, and AI linguistic competency analysis. She actively seeks graduate students and industry partnerships in wearable technology, education tech, and HRI.

Ryan C.N. D'ArcyView profile

Professor

• Neuroscience
• Medical Imaging
• Clinical Neuroscience
• +3 more

Ryan C.N. D'Arcy is a Professor in the School of Computing Science at Simon Fraser University, specializing at the intersection of neuroscience and biomedical imaging. His research focuses on translational neurotechnology, including brain vital signs and neuroimaging techniques for clinical applications. Education: PhD in Neuroscience (Dalhousie University, 2002), MSc in Neuroscience (Dalhousie, 1998), BSc in Psychology and Biology (University of Victoria, 1996). Research interests include systems neuroscience, clinical neuroscience, and neurotechnology development for disorders like brain injury, epilepsy, and Alzheimer's. His work integrates advanced imaging modalities (fMRI, MEG, EEG) with clinical outcomes. Recent articles emphasize neuroplasticity in athletes, concussion biomarkers, and brain vital sign platforms like NeuroCatch®. His studies address cognitive performance in elite athletes, sleep deprivation effects, and neurorehabilitation therapies. Notable contributions include developing the Halifax Consciousness Scanner and advancing MRI-based brain health indices like the Brain Atrophy and Lesion Index (BALI). Collaborative projects focus on translating neuroimaging tools for clinical use in emergency care and long-term disability recovery.

Xing-Dong YangView profile

Associate Professor

• Human-Computer Interaction (HCI)
• Wearable Computing
• Interactive Systems Design
• +5 more

Xing-Dong Yang is an Associate Professor of Computer Science at Simon Fraser University (SFU) and holds an adjunct appointment as Assistant Professor at Dartmouth College. He directs the XDiscovery Lab and focuses on Human-Computer Interaction (HCI), particularly in developing interactive systems for smart everyday objects such as wearables, garments, and appliances. His research emphasizes accessibility for visually impaired users and prototyping tools for non-specialists. He earned his PhD from the University of Alberta, following degrees from the University of Manitoba and University of Alberta. Affiliations: Simon Fraser University (School of Computing Science), Dartmouth College (Adjunct) Education: PhD, Computer Science, University of Alberta MS, Computer Science, University of Alberta BS, Computer Science, University of Manitoba His research explores novel interactive systems, including tactile interfaces for education, assistive technologies for visual impairments, and innovative input methods for wearables. Key projects include MakeBronze (cultural preservation through interactive crafts), AccessibleCircuits (inclusive electronics for blind users), and systems like iWood and MicroFluID that merge materials science with HCI. His work has been recognized with awards such as the Best Paper Award at UIST'19 and multiple Honorable Mentions at CHI and UIST conferences. He advises a dynamic team of PhD and MSc students, emphasizing hands-on prototyping and industry collaborations through internships at companies like Google, Microsoft, and Apple. Yang has secured grants including an NSF CRII grant for device modulation and an NSF CSR Large grant for health-focused earpiece technology. His lab fosters interdisciplinary innovation, bridging computer science with design, engineering, and cultural studies.

• Human Genetics
• Health Sciences
• Genomics
• +5 more

Mads Kaern is an Associate Professor in the Department of Cellular and Molecular Medicine, specializing in synthetic biology, gene regulation, and systems biology. His research integrates computational modeling with experimental approaches to understand cellular processes and design genetic circuits for biomedical applications. Key areas of focus include epistasis analysis, gene expression variability, and the development of educational programs in BIOSTEM. Research interests span molecular mechanisms of gene regulation, synthetic biology applications, and quantitative analysis of genetic interactions. His work emphasizes interdisciplinary methods combining genomics, bioinformatics, and engineering principles to address complex biological questions. Publications highlight contributions to understanding cellular heterogeneity, improving DNA assembly techniques, and advancing therapeutic strategies through synthetic biology. Educational efforts include initiatives like iGEM-inspired programs to enhance undergraduate research and skill development in biotechnology.

Diala NaboulsiView profile

Professor

• Mobile networks
• Wireless networks
• Network virtualization
• +7 more

Diala Naboulsi is a Professor at the École de technologie supérieure (ÉTS) in the Department of Software Engineering and IT. Her research focuses on mobile networks, wireless systems, and cybersecurity, with a strong emphasis on machine learning applications in network optimization. She holds an M.Eng. from the Lebanese University and M.Sc. and Ph.D. degrees from INSA Lyon. Research Units: Summit Tech Research Chair, LASI Lab, Imagin Lab Expertise: Network virtualization, resource allocation, mobility management, UAV-based computing Her work spans resilience in wireless backhaul networks, energy-efficient frameworks in RAN slicing, and federated learning for privacy-aware traffic forecasting. She has advised numerous doctoral students, including Ahmed Abdelmoaty, Hnin Pann Phyu, and Philippe Lavoie. Key contributions include deep reinforcement learning approaches for network topology optimization and UAV-assisted MEC systems for Industry 5.0. Recent publications highlight advancements in 6G networks, network slicing, and edge computing. Her research aligns with strategic initiatives in sustainable and secure communication systems.

Mohammed KhalidView profile

Professor

• FPGA-based Systems
• Network-on-Chip (NoC) Architectures
• Signal Processing Hardware
• +3 more

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.

• Computer Science
• Computational Sciences
• Algorithms
• +4 more

Andreas (Andi) Bergen is an Assistant Professor in the Teaching Stream within the Computer Science department at the University of Toronto’s Mathematical and Computational Sciences school. His work focuses on foundational areas of computer science, with inferred research interests spanning algorithms, programming languages, software engineering, data structures, and computational theory. Bergen actively contributes to the Computer Science Student Community (CSSC). Research Focus : Core computer science disciplines including algorithm design, software development, and computational problem-solving. Community Involvement : Engages with the Computer Science Student Community (CSSC).

Heather PengView profile

Associate Professor

• Marine Hydrodynamics
• Naval Architecture
• Ship Design
• +11 more

Heather Peng is an Associate Professor in the Faculty of Engineering and Applied Science at Memorial University of Newfoundland, where she has been a faculty member since 2008. She holds a B.Sc. and M.A.Sc. in Naval Architecture from Dalian University of Technology and a Ph.D. in Naval Architecture/Marine Hydrodynamics from Dalhousie University. A licensed professional engineer (P.Eng.), she brings extensive industrial experience from Martec Limited and Oceanic Consulting Corporation to her academic role. Education: B.Sc. in Naval Architecture, Dalian University of Technology M.A.Sc. in Naval Architecture, Dalian University of Technology Ph.D. in Naval Architecture/Marine Hydrodynamics, Dalhousie University Her research focuses on marine and ship hydrodynamics, with applications to the design and safety evaluation of ships and offshore structures. Key areas include numerical simulation of ship motions and wave loads, hydrodynamic interactions of multiple floating bodies, coupled dynamics of moored systems, dynamic positioning in challenging environments (including ice), hull form optimization, and renewable wave energy conversion. Her work integrates advanced computational methods with practical engineering challenges in marine systems. Although no publications are listed in the provided text, her research profile suggests strong engagement in computational marine hydrodynamics and offshore system dynamics, with relevance to both academic and industrial sectors in ocean engineering. Professional Affiliations and Recognition: P.Eng. (Professional Engineer) Dr. Peng has advised graduate students and contributed to engineering education and research at Memorial University. Her prior industry experience enhances her applied research and mentoring. She has not received any listed awards in the provided material. Her research likely involves collaboration with ocean engineering firms and government agencies, though specific grants are not mentioned. Laboratories and Research Teams: While not explicitly named, her work implies involvement in marine hydrodynamics and offshore systems research groups within the Faculty of Engineering and Applied Science, potentially associated with ocean technology or renewable energy initiatives at Memorial University.

Sébastien MosserView profile

Associate Professor

• Software Engineering
• Software Architecture
• DevOps
• +6 more

Sébastien Mosser is an Associate Professor in the Department of Computing and Software at McMaster University's Faculty of Engineering since January 2022. He previously held the same position at Université du Québec à Montréal (2019-2021) and Université Côte d’Azur (2012-2022). His research focuses on scalable software composition, domain-specific languages, and modeling, applied to cloud computing, cyber-physical systems, and micro-services architecture. PhD (2010) and MSc (2007) in Computer Science from Université Nice – Sophia Antipolis Developed the Abstract Composition Engine (ACE) for software composition automation Active in industry collaboration with technology transfer experience Registered P.Eng. license in Québec (since December 2021) His work addresses safety-critical software challenges through formal methods and industrial partnerships, particularly in the McMaster Centre for Software Certification (McSCert). As Undergraduate Advisor for Software Engineering, he combines academic leadership with technical innovation.

Telex M. N. NgatchedView profile

Associate Professor

• 5G and 6G enabling technologies
• Optical wireless communications
• Hybrid optical wireless and radio frequency communications
• +2 more

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.

Sivan SabatoView profile

Associate Professor

• Interactive machine learning
• Machine learning theory
• Fairness in machine learning
• +3 more

Sivan Sabato is an Associate Professor at McMaster University's Department of Computing and Software , a Canada CIFAR AI Chair, and faculty member at the Vector Institute of Artificial Intelligence . She holds a joint appointment at Ben-Gurion University's Department of Computer Science while on leave. Her research focuses on machine learning theory, active learning algorithms , and fairness in machine learning . Education: PhD in Computer Science, Hebrew University of Jerusalem Postdoctoral Fellowship, Microsoft Research New England Her theoretical work develops interactive learning frameworks that optimize information costs through algorithmic interaction patterns. Recent publications emphasize differential privacy and discriminative feature analysis with applications to healthcare and social data. She serves as Action Editor for Journal of Machine Learning Research and organizes conference tracks including ICML 2022-2023 and ALT 2021 . Awards include the Alon Scholarship and Google Anita Borg Memorial Scholarship . Advising: Actively supervises Computer Science PhD and MSc students through McMaster's Faculty of Engineering. Research interns can apply via the Vector Institute program with Summer 2026 opportunities.

Alina Maria DulipoviciView profile

Associate Professor

• Cybersecurity / Information Security
• Employee safety behaviors
• Organizational culture favorable to the protection of information assets
• +6 more

Alina Maria Dulipovici is an Associate Professor in the Department of Information Technology at HEC Montréal. She also serves as Deputy Director of Training at the Multidisciplinary Institute for Cybersecurity and Cyberresilience (IMC 2 ) and is a member of the Information Systems Research Group (GReSI). Additionally, she works as an associate researcher at the French-speaking Center for the Computerization of Organizations (CEFRIO). Her educational background includes: M. Sc. (Management) from HEC Montréal PhD in Computer Information Systems from Georgia State University Professor Dulipovici's research focuses on cybersecurity and information security, with particular emphasis on employee safety behaviors, organizational culture related to information asset protection, and data protection risk management. Her work also explores knowledge sharing in organizations, ethics and privacy considerations, knowledge management systems, and strategic IT alignment. She employs qualitative research methods to investigate how organizations can better protect their information assets through understanding employee behaviors and organizational culture. Her recent publications demonstrate a strong focus on the intersection of human behavior and cybersecurity. She examines how values shape knowledge sharing practices and how age affects innovation with IT. Her work bridges theoretical frameworks with practical applications in organizational settings, particularly in the Canadian context where privacy laws like Quebec's Law 25 are shaping organizational practices. Professor Dulipovici actively supervises graduate students, having directed 3 master's theses and 17 supervised project management activities in the past five years. Her students' work covers cybersecurity governance, security posture visualization, privacy-enhancing technologies, conversion funnel development, and various aspects of cybersecurity implementation in organizational contexts. She is currently involved in a major cybersecurity research project called the "Insider Threat Alliance," which received nearly $5.4 million in funding from the Natural Sciences and Engineering Research Council of Canada and MITACS. Through the IMC 2 , she collaborates with research teams from Université de Montréal and Polytechnique Montréal on developing the Insider Threat Sentinel tool, which combines proactive access control with reactive malicious behavior detection using AI techniques. Her contribution focuses on the economic and sociotechnical dimensions of insider threat management.

Shideh Kabiri AmeriView profile

Associate Professor

• 2D material based electronic devices
• Wearables
• Bioelectronics
• +3 more

Dr. Shideh Kabiri Ameri serves as Associate Professor in the Department of Electrical and Computer Engineering at Queen's University, where she joined in September 2018 after completing postdoctoral research at the University of Texas at Austin. Her interdisciplinary expertise bridges nanomaterials engineering and biomedical applications, with particular focus on developing imperceptible wearable sensors for continuous health monitoring. Her educational foundation includes: PhD in Electrical Engineering (2015) from Tufts University Master's and Bachelor's degrees in Physics (solid state) AS degree in Medical Laboratory Sciences Dr. Ameri's research program centers on 2D material-based electronic devices for wearable bioelectronics, human-machine interfaces (HMI), and mobile healthcare systems . Her lab pioneered graphene electronic tattoos (GETs) that achieve unprecedented skin conformity while recording high-fidelity physiological signals. Current work emphasizes ultrasoft hydrogel-based sensors that eliminate motion artifacts and enable months-long wear without skin irritation, representing a paradigm shift from conventional rigid medical devices toward truly imperceptible health monitors. Analysis of her 40+ publications reveals a strategic evolution from fundamental nanomaterial characterization toward clinically viable systems. Recent work (2021-2025) demonstrates increasing sophistication in multimodal sensing (simultaneous ECG/EEG/temperature), reusable sensor architectures , and wireless power integration . The trajectory shows clear progression from lab prototypes to FDA-pipeline devices, particularly in cardiac and neurological monitoring applications. Her scientific recognition includes: Rising Star in EECE 2017 award Dr. Ameri leads the Ameri Nano Research Group which operates advanced nanofabrication facilities for developing next-generation bioelectronic interfaces. Her research has attracted significant media attention from BBC, IEEE Spectrum, and Phys.Org, highlighting real-world impact in remote patient monitoring. The group actively collaborates with medical institutions to translate innovations into point-of-care diagnostics, with current projects focusing on in-ear physiological monitors and strain-neutralized neural recording systems. The research team maintains strong industry partnerships for commercializing soft bioelectronics, with particular emphasis on creating accessible health monitoring solutions for underserved communities through low-cost manufacturing approaches.

Vahab KhoshdelView profile

Assistant Professor

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

Vahab Khoshdel is an Assistant Professor in the Department of Electrical and Computer Engineering at the Price Faculty of Engineering, University of Manitoba. His research bridges machine learning, deep learning, computer vision, robotics, and medical imaging, with applications in rehabilitation robotics, microwave/ultrasound imaging, stored grain monitoring, and precision agriculture. Education: 2021, Ph.D. Biomedical Engineering, University of Manitoba 2017, Ph.D. Mechanical Engineering, Ferdowsi University of Mashhad 2013, M.Sc. Mechatronic Engineering, University of Shahrood 2011, B.Sc. Robotics Engineering, University of Shahrood Research Interests: Khoshdel specializes in applying generative AI, neural networks, and optimization techniques to medical imaging and robotics. His work includes microwave/ultrasound breast imaging, impedance control for rehabilitation robots, and AI-driven agricultural monitoring systems. Publication Trends: His recent articles emphasize machine learning workflows for medical diagnostics, deep learning in multimodal imaging, and neural networks in rehabilitation robotics. Key subfields include 3D imaging, inverse scattering, tissue classification, and sEMG signal analysis. Contact: Vahab.Khoshdel@umanitoba.ca