Miroslav Grmela is a Researcher at the Department of Chemical Engineering in Polytechnique Montréal , and a member of the Research Center for High-Performance Polymer and Composite Systems (CREPEC) . His work spans thermodynamics, transfer processes, and multiscale modeling of complex fluids. Grmela’s research focuses on non-equilibrium thermodynamics , contact geometry in kinetic dynamics , and mesoscopic theories of polymer suspensions, superfluids, and nanocomposites. He has extensively explored the role of energy and entropy in multiscale systems, with recent publications addressing geometric formulations of thermodynamics and neural network applications to non-symplectic mechanics. Analysis of his 15 most recent articles reveals trends in multiscale thermodynamics , non-Fourier heat conduction , GENERIC formalism , and quantum hydrodynamics . His work often bridges geometric mechanics with thermodynamic consistency. Grmela has supervised 10 graduate students (7 PhD, 3 Master’s) in projects involving nanocomposite thermal conductivity , polymer rheology , and powder suspension simulations . He has no listed scientific awards. His research intersects with fluid dynamics , polymer science , and statistical mechanics , emphasizing mathematical structures like Poisson brackets and Hamiltonian formulations . The CREPEC laboratory provides institutional support for his studies on polymers and composites.
Steven Chamberland is a Full Professor at the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. He serves as Director of Academic Affairs and Student Life at the institution. With a Ph.D. from Polytechnique Montréal, an MBA from HEC Montréal, and an MIR from Queen's University, his expertise combines engineering rigor with strategic academic leadership. Ph.D. (Polytechnique Montréal) MBA (HEC Montréal) MIR (Queen's University) B.Eng. (Polytechnique Montréal) Dr. Chamberland specializes in network design and optimization , particularly for wireless and vehicular communication systems. His work addresses critical challenges in network reliability, congestion management, and resource allocation across emerging technologies like SDN, IoT, and 5G/6G systems. He actively explores machine learning applications for network optimization and quality-of-service improvements. His recent publications focus on heterogeneous vehicular networks , with contributions to congestion avoidance mechanisms using neural networks, routing protocols for intelligent transportation systems, and network slicing techniques with generative adversarial networks. These works align with his broader research in mobile computing and smart city infrastructure . Dr. Chamberland has supervised over 8 Ph.D. and 12 Master's students , including notable graduates like Falahatraftar, El Garoui, and Jaramillo Herrera. His leadership extends to the LARIM Laboratory , where he contributes to mobile computing research. Despite extensive publications (>110), no specific scientific awards were mentioned in the provided texts.
Dr. Jonathan Davies is an Associate Professor at the University of British Columbia's Faculty of Forestry, with dual affiliations in the Department of Botany and Department of Forest and Conservation Sciences. His research focuses on phylogenetic ecology, integrating evolutionary biology with ecological systems to address biodiversity conservation and climate change challenges. Academic Rank: Associate Professor Departments: Botany; Forest and Conservation Sciences Research Center: Biodiversity Research Center Email: j.davies@ubc.ca Research Interests : At the intersection of ecology and evolution, Davies' work explores phylogenetic approaches to conservation science, climate change biology, and disease ecology. His lab investigates: Climate change impacts on biodiversity and disease emergence Phylogenetic dilution effects in forest pest dynamics Evolutionary patterns in plant-herbivore interactions Statistical methods for phylogenetic analysis Global biodiversity patterns and diversification rates Eco-phylogenetics of protected area effectiveness
Michal Abrahamowicz, PhD is a Senior Scientist at the Research Institute of the McGill University Health Centre (RI-MUHC) and Professor in the Department of Epidemiology, Biostatistics and Occupational Health at McGill University's Faculty of Medicine and Health Sciences. He is affiliated with the Cardiovascular Health Across the Lifespan Program and the Centre for Outcomes Research and Evaluation (CORE) at RI-MUHC. His research focuses on developing innovative statistical methodologies for clinical and biomedical data analysis, particularly in survival analysis. Key areas include modeling time-varying and cumulative effects of risk factors and treatments, and addressing biases in observational studies. He co-founded and co-chairs the international STRATOS initiative (www.stratos-initiative.org), involving over 100 statisticians from 18 countries, aimed at improving analyses of observational studies. From 2011-2019, he served as Principal Investigator of the CAN-AIM network, funded by the Canadian Institutes for Health Research, which brought together over 45 faculty members from 12 Canadian universities for drug safety and effectiveness research. His recent publications demonstrate a strong focus on methodological advances in biostatistics, particularly in survival analysis, causal inference, and flexible modeling techniques. His work spans applications in cardiovascular diseases, cancer epidemiology, pharmacoepidemiology, and arthritis research, with an increasing emphasis on practical implementation of statistical methods in clinical research. Abrahamowicz leads major collaborative research initiatives including large clinical trials and longitudinal population-based studies. His research methodology work directly informs applications in real-world clinical and epidemiological studies, creating a strong bridge between theoretical statistics and practical healthcare research.
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.
Dr. Kalikinkar Mandal is an Associate Professor in the Faculty of Computer Science at the University of New Brunswick (UNB), Fredericton, Canada. He holds the prestigious NB Power Cybersecurity Research Chair for smart grid security and privacy, a position supported by $500,000 in funding from NB Power for a five-year term. Dr. Mandal is also a member of the Canadian Institute for Cybersecurity (CIC), an ACM member, and a member of the International Association for Cryptologic Research (IACR). Education: PhD in Electrical and Computer Engineering from the University of Waterloo (2013) MTech in Computer Science from the Indian Statistical Institute, Kolkata (2009) Additional Master's degree in Mathematics Dr. Mandal's research broadly focuses on cryptography, cybersecurity, and privacy, with specific expertise in lightweight cryptography, privacy-preserving computation, security and privacy in smart grids and Internet of Things (IoT), trusted computing, and high-speed cryptography. His work addresses critical challenges in securing emerging technologies, particularly in energy infrastructure where cybersecurity threats can have severe consequences for essential services. His research bridges theoretical cryptography with practical applications in real-world systems. Analysis of Dr. Mandal's recent publications reveals a consistent focus on cryptographic techniques for resource-constrained environments, particularly for smart grid and IoT applications. His work spans theoretical foundations of cryptographic primitives, practical implementations of lightweight ciphers, and innovative privacy-preserving protocols for emerging technologies. A notable trend in his research is the development of efficient cryptographic solutions that balance security requirements with performance constraints in critical infrastructure systems. Scientific Awards: NB Power Cybersecurity Research Chair ($500,000 funding) Contributor to multiple cryptographic algorithms (ACE, SPIX, SpoC, WAGE) that reached Round 2 of NIST Lightweight Cryptography standardization Dr. Mandal actively mentors graduate students in cybersecurity research, currently supervising three students working on cryptographic protocols for cyber-physical systems, cybersecurity in advanced metering infrastructure, and privacy for electric vehicles. His NB Power Cybersecurity Research Chair supports research that provides training opportunities for both graduate and undergraduate students, preparing them as future cybersecurity leaders. Through direct applied research, knowledge dissemination, and student training, his work addresses critical challenges in power and security infrastructure. Dr. Mandal is actively involved in several research initiatives related to lightweight cryptography. He is part of the development teams for ACE, SPIX, SpoC, and WAGE - all of which were Round 2 candidates in the NIST Lightweight Cryptography standardization project. His GitHub repository (comsec-lwc) contains reference and optimized implementations of these cryptographic algorithms. He also contributes to the Canadian Institute for Cybersecurity at UNB, focusing on practical applications of cryptographic techniques in critical infrastructure security.
Yasser Mohamed is a Professor in the Civil and Environmental Engineering Department at the University of Alberta . His academic and professional focus revolves around construction engineering, discrete-event simulation, and process optimization for industrial and tunneling operations. He has also explored knowledge engineering techniques and the application of TRIZ (Theory of Inventive Problem Solving) to construction processes. Email: yaly@ualberta.ca Location: 7-269 Donadeo Innovation Centre For Engineering, Edmonton, AB Courses Taught: CIV E 603 (Construction Informatics), CIV E 606 (Design and Analysis of Construction Operations) His research emphasizes modeling construction processes using discrete-event simulation to optimize performance and develop synthetic environments for construction operations. Recent publications, however, indicate a shift toward power systems, focusing on DC microgrids , grid-forming converters , and renewable energy integration . Scientific Awards: None explicitly mentioned in the provided data. Advising and Grants: No formal advisees listed. A co-applicant on a CRD grant (2007–present) for synthetic environments in construction simulation.
Mehdi Pouragha is an Associate Professor in the Department of Civil and Environmental Engineering at Carleton University's Faculty of Engineering and Design in Ottawa, Canada. He holds a BSc and MSc from Sharif University of Technology in Iran and a PhD from the University of Calgary. His academic career focuses on advanced geomechanics research with applications in both theoretical and practical engineering contexts. Dr. Pouragha's research spans multiple interconnected areas within geomechanics, with particular emphasis on constitutive modeling of geomaterials, micromechanics of granular materials, thermo-hydro-mechanical behaviors, and computational geomechanics. His work integrates theoretical approaches with advanced numerical methods to address complex problems in soil mechanics, permafrost engineering, and unsaturated soil behavior. His research program bridges fundamental micromechanical understanding with practical engineering applications, particularly in cold regions and climate change adaptation contexts. Analysis of Dr. Pouragha's recent publications reveals a strong trend toward multiscale modeling approaches that integrate discrete element methods with continuum mechanics. His work increasingly incorporates machine learning techniques to enhance computational efficiency while maintaining physical accuracy. The research spans both fundamental theoretical developments in constitutive modeling and practical applications in permafrost engineering, tailings management, and soil-structure interaction problems. His publications consistently demonstrate a focus on connecting microscale mechanisms to macroscale material behavior. Dr. Pouragha teaches several core civil engineering courses including Geotechnical Engineering, Fundamentals of Geomechanics, Numerical Methods in Geotechnical Engineering, and Professional Practice. His teaching portfolio reflects his research expertise while providing students with both theoretical foundations and practical engineering skills.
Xin Liu is an Adjunct Professor in the Department of Civil Engineering at the Faculty of Engineering. His research focuses on cybersecurity, machine learning applications, and IoT security, with a particular emphasis on network intrusion detection, data compression, and risk-aware access control systems. He holds a Ph.D. from the University of Ottawa, Canada, and M.Sc. and B.Sc. degrees from Hebei University of Technology, China. Education: Ph.D., University of Ottawa, Canada M.Sc., Hebei University of Technology, China B.Sc., Hebei University of Technology, China Research Interests: Dr. Liu's work bridges machine learning and cybersecurity, addressing challenges in IoT security, adversarial attacks, and network traffic analysis. His contributions include developing AI-driven intrusion detection systems, optimizing data compression techniques for IoT devices, and formulating risk-aware access control frameworks. Recent efforts focus on advanced persistent threats (APTs) and privacy leakage mitigation in language models. Articles Trends: His publications emphasize practical applications of machine learning in cybersecurity, including network attack detection, privacy-preserving methods, and resilient IoT infrastructure. Recent work highlights innovations in transformer-based models for intrusion detection and realistic benchmarking for APT simulations. Awards: No scientific awards explicitly mentioned in the provided materials. Advising & Grants: No advising records or grant information available in the current data. Labs/Teams: No specific lab affiliations or collaborative teams noted in the profile.
Paria Shirani is an Assistant Professor and Tier 2 Canada Research Chair in Cybersecurity at the School of Electrical Engineering and Computer Science (EECS), University of Ottawa. She holds a PhD in Information Systems Engineering from Concordia University (FRQNT Doctoral Scholarship recipient) and completed an NSERC Postdoctoral Fellowship at Carnegie Mellon University (CMU). Her research focuses on cybersecurity, including IoT security, vulnerability detection, malware analysis, threat intelligence, and AI/ML applications. She leads funded projects across undergraduate, master’s, PhD, and postdoctoral levels, emphasizing equity, diversity, and inclusion (EDI). Research Highlights: Develops AI-driven solutions for IoT security and vulnerability detection. Pioneers binary code fingerprinting and firmware analysis techniques. Advances threat intelligence through machine learning and anomaly detection. Key awards include the NSERC Postdoctoral Fellowship, FRQNT Doctoral Scholarship, and the Tier 2 Canada Research Chair. Collaborations involve institutions like Concordia University, Carnegie Mellon University, and IBM’s Cyber Range. She actively serves on editorial boards (e.g., ACM Computing Surveys) and organizes conferences (e.g., SecureComm, PST).
Marco Baiesi is an Associate Professor in the Department of Physics and Astronomy at the University of Padua. His research focuses on nonequilibrium systems, polymers, biopolymers, topology, and machine learning applications in physics and biophysics. He has contributed to understanding the statistical mechanics of complex systems, including polymer dynamics, topological effects, and non-equilibrium thermodynamics. His work spans interdisciplinary areas such as biophysics, soft condensed matter, and machine learning for medical diagnostics. Notable contributions include studies on knotted polymer behavior, entropy production in non-equilibrium systems, and the application of AI to EEG-based dementia classification. Baiesi’s publications frequently explore topics like fluctuation theorems, stochastic processes, and the interplay between topology and material properties. His research has been published in high-impact journals such as Science , Physical Review Letters , and New Journal of Physics .
Abdul-Rahman Mawlood-Yunis is an Associate Professor in the Department of Physics and Computer Science at Wilfrid Laurier University. His research focuses on Artificial Intelligence, Android Mobile Application Development, Software Engineering, Distributed Systems, and P2P Networking with an emphasis on fault-tolerant systems and semantic web technologies. He has contributed to frameworks for live streaming apps and machine learning algorithms for feature selection. Research interests include: Chatbots and Natural Language Processing (NLP) Ontology engineering and knowledge representation Algorithm design for distributed systems Mobile agent performance analysis Fault-tolerant semantic P2P networks His recent work (2022-2024) emphasizes machine learning applications in feature selection and real estate price estimation, reflecting a shift towards data-driven solutions. Earlier contributions (2003-2013) explored foundational aspects of mobile agents and semantic interoperability in P2P networks. Teaching responsibilities include courses on Android development and Java programming, with associated open-source materials and courseware. His book Android for Java Programmers provides foundational resources for students and instructors. Languages spoken: English, Kurdish, Arabic, Farsi.
Dr. Christopher Bidinosti is a Professor in the Department of Physics at the University of Winnipeg. He holds a Ph.D. from the University of British Columbia (2000) and specializes in nuclear magnetic resonance (NMR), magnetic resonance imaging (MRI), and machine learning applications in agriculture. His research spans low-field NMR/MRI, hyperpolarized nuclei, and collaborations like the TerraByte project, aimed at advancing agricultural machine learning through open-access plant image datasets. His research interests include TRASE MRI, neutron electric dipole moment (EDM) searches, GPU computing, and magnetics (coil design, shielding). He teaches courses such as Electricity & Magnetism and Optics and Waves. His work bridges physics and applied technology, with a focus on interdisciplinary innovation. Bidinosti collaborates with institutions like UWinnipeg’s Computer Science department and has developed hardware solutions for NMR/MRI systems. His contributions span experimental physics, computational methods, and agricultural technology, leveraging both theoretical and applied approaches.
Jessica Olivares is an Assistant Professor of Supply Chain Management at the Shannon School of Business, Cape Breton University. Her expertise spans supply chain resilience, digital twins, and Industry 5.0, with a focus on mitigating disruptions in global networks. Dr. Olivares contributes to both academic research and practical solutions for sustainable supply chain management. Her academic credentials include: B.S. in Industrial Engineering, University of the Americas Puebla (UDLAP), Mexico M.S. in Industrial Engineering, University of the Americas Puebla (UDLAP), Mexico Ph.D. in Industrial and Manufacturing Systems Engineering, University of Windsor, Canada Dr. Olivares' research centers on supply chain management, with specific interests in disruption recovery, digital twin applications, and sustainable design. She explores how Industry 5.0 principles can humanize smart manufacturing while enhancing resilience. Her work addresses critical gaps in perishable food supply chains and resource distribution during crises, integrating risk assessment with technological innovation to build robust systems. Her recent publications (2021-2025) show a strong emphasis on digital twins for supply chain resilience, with increasing attention to sustainability and multi-objective optimization. She has pioneered frameworks for recovery from major disruptions, including pandemic impacts, and investigates energy-aware scheduling in manufacturing. Her scholarship bridges theoretical models with real-world applications in food systems and global networks. No scientific awards were documented in the available sources. Information on graduate student supervision and research funding was not provided, though her active publication record suggests engagement in scholarly mentorship and potential grant-supported projects. No details about laboratories or research teams were mentioned.
Nicolas Vermeys is a Full Professor at the Université de Montréal’s Faculty of Law, serving as Director of the Centre de recherche en droit public (CRDP) and Associate Director of the Cyberjustice Laboratory. He holds advanced degrees (LL.D. and LL.M.) from Université de Montréal and is a certified CISSP (Certified Information Systems Security Professional). His work focuses on intersections between technology and law, particularly cybersecurity, AI governance, and cyberjustice innovation. Education: LL.D. and LL.M. (Université de Montréal) Affiliations: Cyberjustice Laboratory, CRDP, Regroupement stratégique Research Interests: Cyberjustice systems, AI ethics in law, information security obligations, civil liability in digital contexts, and legal frameworks for emerging technologies. He frequently advises governments, legal professionals, and international organizations on these topics. Recent Article Trends: Explores cybersecurity challenges in judiciary systems, AI’s role in judicial processes, and privacy implications of smart technologies. Key themes include ODR systems, digital evidence reliability, and regulatory strategies for autonomous systems. Grants & Projects: Lead researcher on initiatives like Lex Electronica (digital law research) and Human-Centric Cybersecurity Partnership. Co-leads projects on judicial data processing, blockchain arbitration, and AI-driven legal tools. Labs & Teams: Directs CRDP (Canada’s largest legal research center) and co-manages the Cyberjustice Lab, which develops software solutions for justice system challenges. Collaborates internationally with institutions like William & Mary Law School and the University of Fortaleza.
