Tina Zhu, MD is an Adjunct Assistant Professor at Queen’s University and a Full-Time Cardiologist at APEX Heart Centre. She holds dual degrees from the University of Toronto: a Bachelor of Science in Immunology and a Medical Degree. Her clinical training includes Internal Medicine at Western University and Adult Cardiology at Queen’s University, alongside specialized certifications in Level III Echocardiography and Nuclear Cardiology. Her research interests focus on heart failure , women’s heart health , and digital health innovation . She actively explores applications of AI and technology in cardiology, particularly in improving diagnostic workflows and patient care. Dr. Zhu’s academic contributions span AI-driven healthcare solutions, with recent work emphasizing automated planning models, text anonymization, and robust dialogue systems. Her publications reflect interdisciplinary expertise at the intersection of cardiology and computational science. Professional affiliations include Queen’s University and APEX Heart Centre, where she balances clinical practice with academic engagement. No formal awards or grants are explicitly listed in the provided materials.
Dr. Jason Millar is an Associate Professor at the University of Ottawa's School of Electrical Engineering and Computer Science, with a cross-appointment to the Department of Philosophy in the Faculty of Arts. He holds the Canada Research Chair in Ethical Engineering of Artificial Intelligence and Robotics and directs the Canadian Robotics and Artificial Intelligence Ethical Design Lab (CRAiEDL). His work focuses on integrating ethical thinking into engineering workflows, particularly in automated vehicles, healthcare robotics, and military robotics. He provides expert testimony on AI ethics at international forums like the United Nations and advises on policy for autonomous systems. Education: Engineering Physics degree with prior engineering practice before transitioning to academic ethics research. His research emphasizes ethical frameworks for emerging technologies, including privacy preservation in automated systems and liability issues in advanced driver assistance systems. Research Interests: Ethical engineering of AI/robotics, policy development for autonomous systems, human-robot trust dynamics, and societal impacts of automation. His work bridges engineering, philosophy, and law, advocating for interdisciplinary approaches to ethical technology design. Scientific Awards: Canada Research Chair in Ethical Engineering of AI and Robotics (2015–present). Advising & Grants: Advises on policy for autonomous vehicles and military robotics. Has secured grants for ethical AI design and public engagement initiatives. Labs/Teams: Leads the CRAiEDL lab, exploring ethical design principles for robots and AI systems. Collaborates with interdisciplinary teams across engineering, philosophy, and legal disciplines.
Abdelrahman Hussein is a PhD student and Graduate Research Assistant at the School of Computing Science, Simon Fraser University since 2024, advised by Prof. Alaa Alameldeen. His research focuses on optimizing microarchitecture structures for heavily multithreaded workloads in data centers. PhD in Computing Science, Simon Fraser University (2024–Present) MSc in Computing Science, Simon Fraser University (2021–2024) Diploma in Digital Systems Design, Information Technology Institute, Egypt (2017–2018) BSc in Computer Engineering, Mansoura University, Egypt (2012–2017)
Edward W. Thommes is an Adjunct Professor of Mathematics at the University of Guelph and York University. He serves as the Global Modeling Lead in the Modeling, Epidemiology and Data Science (MEDS) team at Sanofi Vaccines, an Affiliate Researcher at the Waterloo Institute for Complexity and Innovation (WICI), and a member of the Strategic Advisory Committee for the Mathematics for Public Health program at the Fields Institute. His research focuses on biomathematics, epidemiology, dynamical systems, and the application of AI in public health modeling. Thommes holds a B.Sc. in Physics from the University of Alberta (1994) and a Ph.D. in Astrophysics from Queen's University (2000). His work bridges theoretical astrophysics and applied epidemiological modeling, with a strong emphasis on infectious disease dynamics and public health policy. He collaborates extensively with institutions like the Fields Institute and Sanofi, addressing challenges such as pandemic preparedness, vaccine efficacy, and health equity. His recent publications analyze influenza vaccine effectiveness, pandemic response strategies, and the impact of mobility patterns on disease spread. He also contributes to interdisciplinary initiatives, including agent-based modeling and causal analysis frameworks for public health decision-making.
Steven Bednarski is a Full Professor of History at St. Jerome's University, federated with the University of Waterloo. He holds academic appointments at the University of Toronto's Centre for Medieval Studies and Queen's University. His work focuses on medieval European history, particularly late medieval Provence and England, with specializations in environmental history, criminal justice, gender studies, and microhistory. Bednarski directs the Medieval D.R.A.G.E.N. Lab, a digital humanities initiative advancing environmental and climate studies through technology. He has secured significant SSHRC grants, including a $2.5M Partnership Grant, to support interdisciplinary projects like Environments of Change, exploring medieval climate-human interactions. His award-winning teaching includes mentoring students in fieldwork at Herstmonceux Castle and co-authoring his book A Poisoned Past with undergraduates. Education includes a B.A. (York University, 1995), M.A. (University of Toronto, 1996), and PhD (Université du Québec à Montréal, 2002). Awards include the D2L Innovation Award (2017) and the University of Waterloo Distinguished Teacher Award (2011). Research spans medieval criminal records, microhistories of marginalized figures, and digital reconstructions of historical sites. Current projects include a book on Sir Herbert Paul Latham and collaborative work on 3D scanning archaeological artifacts.
Maura Grossman is a Research Professor at the University of Waterloo. She specializes in legal technology, electronic discovery (eDiscovery), and the ethical implications of artificial intelligence (AI) in judicial and healthcare contexts. Her work bridges computer science, law, and healthcare policy, focusing on challenges like AI-generated evidence in courts, fairness in data sharing, and algorithmic bias mitigation. She actively participates in initiatives such as the TREC tracks to advance technology-assisted review methodologies. Her research interests include high-recall retrieval systems, user-specific AI explanations, and the societal impact of generative AI. Notably, she explores how courts can adapt to AI-generated materials, particularly in national security cases, and advocates for frameworks ensuring health data sharing aligns with welfare and ethical standards. Recent publications highlight trends in regulatory responses to AI, data governance for synthetic health ecosystems, and the intersection of queer/disability studies with generative AI. Grossman’s contributions to eDiscovery protocols, including unbiased validation and tool comparisons, have shaped legal technology standards. While no specific awards are noted, her extensive collaboration in TREC projects and peer-reviewed outputs underscore her leadership in empirical legal tech research. She has advised on projects addressing long-term care financing and open science metrics, reflecting a commitment to interdisciplinary problem-solving.
Xue Liu is a Professor and William Dawson Scholar at McGill University's School of Computer Science, affiliated with the Department of Mathematics and Statistics (courtesy appointment) and the Department of Electrical and Computer Engineering. He holds positions as Vice President R&D and Chief Scientist at Samsung AI Center Montreal, and serves as Chair (2021-2023) of ACM SIGBED. His research focuses on intelligent computing, cyber-physical systems, sustainable computing, AI/ML applications, IoT, and blockchain technologies. Dr. Liu has received multiple Best Paper Awards from conferences such as IEEE GLOBECOM, IEEE HPCC, and IEEE/ACM IWQoS. He is a Fellow of the Canadian Academy of Engineering (FCAE) and IEEE (FIEEE). His work bridges academia and industry, with entrepreneurial ventures including advisory roles at Infinity Stones Inc., TandemLaunch, and Aerial Technologies. He co-edits the Journal of Blockchain Research and serves on editorial boards of major journals like ACM Transactions on Cyber-Physical Systems and IEEE Transactions on Networking. Key research contributions include innovations in blockchain infrastructure, smart grid optimization, and AI-driven systems. His labs, including the Cyber-Physical Intelligence Lab and MILA affiliation, advance interdisciplinary research in machine learning, robotics, and networked systems. Dr. Liu mentors startups and advises initiatives like Learnable Inc., integrating AI into education and healthcare. Education Affiliations: McGill University School of Computer Science (prestige rankings include top 25 globally per QS 2023) Awards: Multiple Best Paper Awards, FCAE & FIEEE Fellowships Labs: Cyber-Physical Intelligence Lab, MILA, CIM, SYTACom Publications: Over 150 peer-reviewed articles, including books on cloud computing, smart grids, and cyber-physical systems
Yajing Liu is an Associate Professor and Canada Research Chair in Earthquake Seismology at McGill University's Department of Earth and Planetary Sciences. Her research focuses on earthquake mechanics, fault behavior, and anthropogenic seismicity, particularly induced by hydraulic fracturing. She combines geophysical observations with advanced numerical modeling to improve earthquake hazard prediction. Education: PhD (2007, Harvard University) and BSc (2001, Peking University). Professional experience includes roles at Woods Hole Oceanographic Institution and Princeton University. She leads the SCEC SEAS benchmark project, advancing community code verification for earthquake and aseismic slip simulations. Notable work includes discovering a novel type of slow-slip hydraulic fracturing-induced earthquakes in British Columbia and studying induced seismicity links to methane emissions. Research emphasizes subduction zones, fault geometry effects, and crustal stress dynamics. She has advised PhD student John Onwuemeka (JGR 2021) and secured NSERC strategic grants. Current projects explore seismic hazard mitigation in unconventional energy extraction and fault system interactions. Key awards: Canada Research Chair in Earthquake Seismology Labs/teams: SEAS community code project, McGill seismic hazard research group
J. Blustein is an Associate Professor in the Faculty of Computer Science at Dalhousie University, with a cross-appointment in the School of Information Management, Faculty of Management. His research centers on improving how people interact with and make sense of digital information, particularly through human-computer interaction, visualization, and web-based systems. Research Interests: Dr. Blustein's work spans several interconnected domains including human-computer interaction, hypertext, digital libraries, annotation systems, text analytics, e-learning, and information seeking behaviors. He emphasizes interdisciplinary and collaborative research, often conducted through the HAIKU research group, aiming to enhance user understanding and engagement with digital content. Publication Trends: His scholarly output reflects a sustained focus on how users annotate, organize, and derive meaning from digital texts. From early work on personal glossaries on the web to field studies on marginal annotation, his research explores the cognitive and practical aspects of sensemaking in digital environments, contributing significantly to web science and digital library design. Honors and Funding: Funding support from CFI, NSERC, and SSHRC Cross-appointed Associate Professor, School of Information Management Advising and Grants: Dr. Blustein is actively involved in research mentorship and has secured competitive research funding from major Canadian agencies. While specific advisees are not listed, he indicates that fellowship opportunities are available, suggesting ongoing student supervision and research team development. Labs and Research Groups: He is associated with the HAIKU research group, which serves as the primary vehicle for his interdisciplinary research initiatives in information interaction and user-centered systems.
Samer Lahoud is an Associate Professor and University Research Chair at the Faculty of Computer Science, Dalhousie University, where he leads research in wireless networks, IoT, and resource optimization. He joined Dalhousie in 2023 after holding academic positions at the University of Rennes and Saint Joseph University in Lebanon, and working as a researcher at IRISA laboratory and as a research engineer at Nokia Bell Labs Europe. His educational background includes a PhD in Computer Science and Networks from IMT Atlantique, Rennes (2006), and a Habilitation (HDR) from Université Paris-Saclay (2023), both in France. Dr. Lahoud's research focuses on enhancing wireless network performance through adaptive and energy-efficient solutions. Key areas include radio resource allocation in cellular and LPWAN, full-duplex communications, and game-theoretic models for multi-operator networks. His work bridges theoretical models with real-world applications in smart agriculture, smart cities, and industrial IoT. He has made significant contributions to LoRaWAN propagation modeling and developed open-source simulators for RL-based resource allocation. His recent publications reflect a strong trend toward intelligent, learning-based, and game-theoretic approaches for optimizing LPWANs, 5G RAN slicing, and full-duplex networks. The articles emphasize energy efficiency, reliability, and scalability in IoT systems, with increasing integration of machine learning and federated learning paradigms. University Research Chair - Established Scholar, Dalhousie University Dr. Lahoud has co-supervised over 10 students, including postdoctoral researchers, PhD, and master's candidates. He has led multidisciplinary research projects funded by national and international agencies, particularly in LPWAN for smart agriculture. He also played a key role in establishing a joint IoT master's program between Saint Joseph University and Paris-Saclay University. He leads a research team focused on wireless systems and has developed open-source tools such as the LoRa-MAB simulator and FDOFDMA-Simulator. His lab fosters international collaboration between institutions in Canada, France, and Lebanon, promoting student mobility and knowledge transfer.
Qiang Ye is a Professor in the Faculty of Computer Science at Dalhousie University, Halifax, Canada. His research focuses on mobile and wireless networks, network security, machine learning, Internet of Things, and data analytics. He is actively involved in advancing systems research and supervising graduate students in these domains. Research Interests: Mobile and Wireless Networks : Design and optimization of next-generation wireless communication systems. Network Security : Ensuring robustness and privacy in networked environments. Machine Learning : Application of AI techniques to network and system problems. Internet of Things (IoT) : Scalable and secure IoT architectures. Data Analytics : Extracting insights from large-scale network and sensor data. Dr. Ye is currently recruiting self-motivated graduate students, particularly PhD candidates, and encourages interested applicants to contact him with their CV and transcripts. Scientific Awards: No awards listed in the provided text. Advising and Grants: Dr. Ye is actively recruiting PhD and graduate students for research in his lab. While specific grants are not mentioned, his ongoing research activities suggest active funding support. He emphasizes self-motivated students for collaborative research. Labs and Research Teams: He is affiliated with the Systems research cluster within the Faculty of Computer Science, focusing on building and analyzing advanced computing and networking systems.
Haim Dubossarsky is a Lecturer at the School of Electronic Engineering and Computer Science, Queen Mary University of London, with a secondary affiliation as an Affiliated Lecturer in the Language Technology Lab at the University of Cambridge. His research bridges artificial intelligence, natural language processing, and cognitive science, with specialized focus areas including: Computational modeling of lexical semantic change across languages Intersections of linguistics, cognition, and neuroscience Robustness and interpretability in NLP systems Cross-lingual transfer learning for low-resource scenarios His publication trends (2022-2025) reveal concentrated work in semantic change detection methodologies, with innovations in evaluation frameworks (LSC-Eval), multilingual applications (SenWiCh), and model comparisons (GPT vs. BERT). Recent expansions include cognitive neuroscience integrations for narrative processing and sentiment-aware diachronic analysis. A consistent theme is improving NLP robustness through topological analysis, adversarial training, and logical reasoning frameworks. Dubossarsky contributes to the Language Technology Lab at Cambridge, focusing on interdisciplinary approaches to language modeling. No information is available regarding awards, students, or grants in the provided materials.
Thomas J Rivera is an Assistant Professor of Finance at the Desautels Faculty of Management, McGill University. He holds a PhD in Economics and Decision Sciences from HEC Paris (2020), an M.Sc in Economics from Toulouse School of Economics (2012), and an MA in Economics and Finance from Barcelona Graduate School of Economics (2011). Current affiliation: Desautels Faculty of Management, McGill University Research focus: Theoretical issues in DeFi, blockchain economics, banking stability, corporate finance, and incomplete information Member of the Finance Theory Group Education: PhD, HEC Paris, Economics and Decision Sciences (2020) M.Sc, Toulouse School of Economics (2012) MA, Barcelona Graduate School of Economics (2011) Research Interests: His work bridges blockchain economics and traditional finance. Key areas include decentralized finance (DeFi) protocols, proof-of-work vs proof-of-stake mechanisms, liquidity modeling in decentralized exchanges, corporate signaling under information asymmetry, and banking regulation. His research employs economic modeling to address technical challenges in blockchain systems and financial markets. Scientific Contributions: Thomas has published in top journals like Review of Financial Studies, Management Science, and Review of Finance. His recent work includes economic models of decentralized exchanges, equilibrium staking dynamics, and corporate finance implications of blockchain technology. He has been recognized with the PBCSF Award for Best Paper in Fintech (2024). Recognition: PBCSF Award - Best Paper in Fintech (2024) Mentioned in multiple research recognitions at McGill Desautels Faculty of Management
Sylvain Baillet serves as Adjunct Professor of Neurology and Neurosurgery, Biomedical Engineering, and Computer Science at McGill University, and Professor of Neuroscience at Université de Montréal. He is Director of the Centre de recherche at CHUM and Director of Research & Innovation at CHUM, working primarily through the Montreal Neurological Institute-Hospital (The Neuro), a leading bilingual academic healthcare institution and McGill research/teaching institute. Dr. Baillet graduated from Ecole Normale Supérieure Paris-Saclay in Applied Physics and earned his PhD summa cum laude in Physics from University of Paris (Paris-XI). His distinguished international career includes positions as Research Associate at the University of Southern California, tenured Principal Investigator at CNRS in France (2000), Head of the Brain Imaging group at La Salpetriere University Hospital (2005), and Associate Professor at the Medical College of Wisconsin (2008) before joining McGill University in 2011. As a global leader in brain imaging and multimodal electrophysiology, Dr. Baillet's research focuses on understanding the nature and macroscopic mechanisms of large-scale, network brain activity across time scales from milliseconds to the lifespan. His lab takes a multi-disciplinary approach blending imaging, multi-scale electrophysiology, cognitive and clinical neuropsychology, biophysics, computational models and data science. Rather than specializing in specific brain functions, his work seeks common denominators across neurological phenomena with particular expertise in magnetoencephalography (MEG) for time-resolved brain imaging. His recent publications demonstrate a strong trajectory toward applying advanced neuroimaging techniques to understand Parkinson's disease, Alzheimer's disease, psychosis, and chronic pain, while maintaining significant contributions to open science infrastructure. His work shows increasing integration of genetics with neurophysiology, attention to sustainability in neuroimaging, and development of predictive models for neurological conditions. Dr. Baillet's scientific recognition includes: Tier-1 Canada Research Chair of Neural Dynamics of Brain Systems (2018) French Academy of Sciences award for outstanding publication in Biology Election to the Academy of Science, Royal Society of Canada (2025) Open Science Leadership Award from the Tanenbaum Open Science Institute With over 11,700 citations and 4 articles in the Top 1% of most-cited publications in Neuroscience, Dr. Baillet has trained 130 students (74 graduates) and 13 post-doctoral fellows from diverse backgrounds, with 20 trainees securing faculty positions worldwide. His research is supported by a substantial funding portfolio exceeding $36 million from agencies including NSERC, CIHR, SSHRC, CFI, Compute Canada, Brain Canada, FRQS, FRQNT, NIH, and private donors, currently managing 14 active grants with 8 as PI or co-PI. Dr. Baillet founded the McConnell Brain Imaging Centre (Canada's largest), recruiting 6 PI leaders and 9 highly qualified personnel while raising $6.4 million in infrastructure grants. His lab hosts the Brainstorm software integration (27,600 user accounts), with training workshops attended by over 2,000 students/faculty worldwide. He co-founded the Open MEG Archives (OMEGA), now with Release 3 containing over 150 hours of MEG recordings from 644 participants, demonstrating his commitment to open science and collaborative neuroscience.
Florian Meyer is a Full Professor in Educational Technology Integration at the University of Sherbrooke's Faculty of Education since 2011, specializing in digital pedagogy and teacher training. His work bridges educational research with practical implementation of technology-enhanced learning systems. Education Background: Ph.D. in Educational Sciences (2010) - University of Montreal D.E.S.S. in Audiovisual and Computer Technologies for Education (1999) - University of Poitiers Master's Equivalent in Mathematical and Computer Engineering (1998) - University of Franche-Comté His research focuses on distance education methodologies, collaborative video analysis of teaching practices, digital innovation in pedagogy, and professional development for educators. Meyer has pioneered approaches to video-based teacher training and hybrid learning environments, with particular attention to synchronous technologies like telepresence systems. His recent publications reveal a strong trend toward AI integration in education, pandemic-responsive teaching strategies, and cross-cultural digital pedagogy, particularly in African and Quebec educational contexts. Meyer's work consistently bridges theoretical frameworks with practical implementation tools for educators. Scientific Recognition: Excellence Award in Diversity and Inclusion from ARUCC Prestigious University Teaching Distinction Award from University of Sherbrooke Meyer has secured over $3.5 million in research funding from agencies including FRQSC, FRQNT, MITACS, and international partners. His collaborative projects span Canada, France, Switzerland, Morocco, Colombia, and Mexico, focusing on digital transformation in teacher education. He leads the Technopedagogical Innovation Pole (Pôle d'Innovation Technopédagogique) and co-directs the GRIIPTIC research group focused on educational technology integration.
