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Jean Philippe ThiviergeView profile

Professor

• Neural Dynamics
• Neurosciences
• Systems Biology
• +5 more

Jean Philippe Thivierge is a Professor in the Department of Psychology at the University of Ottawa, Faculty of Social Sciences. His research integrates experimental and computational approaches to study the dynamics of neuronal networks underlying memory and cognition. Research Interests: Dr. Thivierge's work centers on neural dynamics , neurosciences , and systems biology . He investigates how large-scale neuronal populations encode and maintain memories by combining multielectrode recordings with biologically realistic simulations. His lab explores principles of network organization across spatial and temporal scales, focusing on phenomena like neuronal avalanches, attractor dynamics, and functional connectivity. The analysis of his recent publications reveals a strong emphasis on computational modeling , statistical analysis of neural data , and network-level neuroscience . His work bridges experimental findings with theoretical frameworks, particularly in understanding scale-free dynamics, criticality, and information processing in cortical and hippocampal circuits. Scientific Contributions: While specific awards are not listed, his publication record in high-impact journals such as Neuron , PLoS Computational Biology , and Journal of Neurophysiology reflects significant contributions to computational and systems neuroscience. Advising and Research: Dr. Thivierge mentors several trainees, including graduate students and postdoctoral fellows, many of whom are co-authors on his publications. His lab employs multielectrode array technology and large-scale neural simulations to probe the mechanisms of memory formation and network stability. Although grant details are not provided, his sustained research output suggests active funding support. Laboratory Focus: The Thivierge Lab operates at the intersection of experimental neurophysiology and computational modeling, utilizing both in vitro recordings and in silico simulations to test hypotheses about brain network function. The lab's approach enables rigorous testing of biophysical mechanisms linking synaptic properties to emergent network behaviors.

Benjamin D SeamoneView profile

Professor

• Graph Theory
• Structural Graph Theory
• Graph Searching
• +3 more

Benjamin D Seamone is a permanent faculty member in the Mathematics Department at Dawson College (Montreal) and an adjunct research faculty in the Department of Computer Science and Operations Research at Université de Montréal. His research focuses on graph theory, including structural properties of graphs, graph searching, and surveillance. He holds a PhD in Applied Mathematics from Carleton University (2014), an MMath in Combinatorics and Optimization from the University of Waterloo, and a BSc from Canada's #1 undergraduate university. He coordinates Dawson College’s pre-university programs in Science nature and Sciences, informatique et mathématique. Education: PhD in Applied Mathematics, Carleton University (2014), supervised by Brett Stevens. MMath in Combinatorics and Optimization, University of Waterloo, co-supervised by Penny Haxell and Jacques Verstraëte. BSc from #1 undergraduate university in Canada . Research Interests: Seamone’s work centers on graph theory, particularly structural properties of graphs, graph searching algorithms, and network surveillance. His contributions include studies on acyclic colorings, eternal domination, Hamiltonian cycles, and biased combinatorial games. He collaborates widely, with affiliations to CRM and ISM Combinatorics and Algebra groups, and has conducted research at LaBRI (Université de Bordeaux). Publications Trends: His articles span topics from planar graph colorings to combinatorial game thresholds, reflecting a strong focus on discrete mathematics and algorithmic graph theory. Recent work emphasizes eternal domination and Hamiltonian cycle dynamics. Awards and Grants: No formal scientific awards are listed, though he has an Erdős number of 3. His research has been NSERC-funded during his postdoctoral fellowship at Université de Montréal. Lab/Tech Affiliations: Member of CRM and ISM Combinatorics groups, and previously at LaBRI (Bordeaux).

Kate HaleView profile

Assistant Professor

• Cold Region Hydrology
• Snowpack Dynamics
• Climate Change Impact on Water Resources
• +3 more

Kate Hale is an Assistant Professor at the Department of Geography , University of British Columbia , within the Faculty of Arts . Her research focuses on cold region hydrology, particularly characterizing snowpack dynamics, climate variability, and ecohydrologic processes to understand drivers of water availability in alpine and Arctic watersheds . She leverages ground-based observations , remote sensing , and computational modeling to analyze snow water storage heterogeneity and its impacts on hydrologic partitioning. Education: PhD, University of Colorado Boulder (2022) MA, University of Colorado Boulder BS, Georgetown University Research Interests include snowpack-water storage interactions, climate change impacts on seasonal hydrology, and stakeholder-driven water management strategies. Her work addresses how snowpack heterogeneity and warming trends transform alpine hydrology from multi-year storage to ephemeral systems, with implications for water quality, ecosystem health, and regional adaptation. Recent Publications span journals like Hydrological Processes , Water Resources Research , and Communications Earth & Environment , focusing on snowmelt-driven hydrology, rain-snow transition zones, and Western North American water scarcity. Her 2023 Communications Earth & Environment study highlighted declining snowpack trends linked to climate change. Scientific Awards: Dean of Arts Faculty Research Award (2024/25) Kate Hale teaches courses related to climate science and hydrology , and advocates for equity in science to enhance environmental outcomes through diverse scientific communities.

Amirnaser YazdaniView profile

Professor

• Power Electronics
• Renewable Energy Systems
• Microgrids
• +5 more

Dr. Amirnaser Yazdani is a Professor and Associate Chair for Graduate Studies in the Department of Electrical and Computer Engineering at Toronto Metropolitan University. He holds adjunct appointments as Associate Professor at the University of Toronto and University of Western Ontario. His academic background includes a Ph.D. in Electrical Engineering from the University of Toronto (2005), M.Sc. from University of Tehran (2001), and B.Sc. from Sharif University of Technology (1995). Education: Ph.D. Electrical Engineering, University of Toronto (2005) M.Sc. Electrical Engineering, University of Tehran (2001) B.Sc. Electrical Engineering, Sharif University of Technology (1995) Research Focus: Dr. Yazdani leads pioneering research in high-power electronic conversion systems with applications in renewable energy integration, microgrids, and smart grids. His work emphasizes modeling, control design, and stability analysis of distributed energy resources. Key areas include: Advanced converter topologies for HVDC transmission and renewable integration Energy management strategies for DC distribution networks and electric vehicles Robust control frameworks for islanded microgrid operation Protection systems for inverter-based distributed generation Publication Trends: His recent articles demonstrate strong focus on DC power systems, microgrid resilience, and electric vehicle integration. Theoretical contributions include novel control methodologies for power converters, while applied research features case studies on grid modernization. Recurring themes include stability enhancement, fault tolerance, and optimization of hybrid renewable systems. Awards & Honors: IEEE Student Branch Professor of the Year (2016, 2017) Chair's Research & Teaching Awards, Ryerson University (2013, 2014) NSERC Industrial Research Fellowship (2005-2006) Multiple teaching excellence awards from University Students' Council IEEE Senior Member status (2009) Edward S. Rogers Scholarship (2004-2005) Academic Leadership: As Project Leader of NSERC-funded Canadian Smart Microgrid Strategic Network, he coordinates national research initiatives. He chairs the IEEE PES Working Group on Distributed Energy Resources Modeling and serves as Associate Editor for IEEE Transactions on Sustainable Energy. His research group focuses on power electronics applications for next-generation grids.

Ojelanki NgwenyamaView profile

Professor

• Information Systems
• Technology Management
• Organizational Innovation
• +5 more

Ojelanki Ngwenyama is a Professor of Global Management and Director of the Institute for Innovation and Technology Management at Toronto Metropolitan University's Ted Rogers School of Management. He holds additional appointments as Emeritus Professor of Information Systems at the University of Cape Town and Docent at University of Jyväskylä since 1996. His international academic career spans institutions including Université de Nantes, University of Münster, Deakin University, University of South Africa, and Copenhagen Business School. Education: D.Phil (HC, 2009) - University of Pretoria, Faculty of Engineering Ph.D. in Computer Science (1988) - SUNY Binghamton, Thomas J. Watson School of Engineering MBA in Organizations and Management (1985) - Syracuse University, Whitman School of Management MS in Computer Information Systems and BS in Computer Science (1983) - Roosevelt University Professor Ngwenyama's research spans critical areas of Information Systems with particular focus on organizational innovation, technology management, and the social implications of ICT in development contexts. His work bridges theoretical rigor with practical applications, examining how technology influences organizational structures, social dynamics, and economic development. His recent research explores the ethical dimensions of AI, digital entrapment in big data systems, and sustainable technology practices, reflecting his commitment to addressing pressing societal challenges through information systems research. Analysis of his publication trends reveals a consistent focus on critical social theory applied to information systems, with increasing attention to digital ethics, human flourishing in digital environments, and the societal implications of emerging technologies. His work demonstrates interdisciplinary breadth, connecting information systems with management theory, social science, and development studies. Scientific Awards and Recognitions: Fellow of the Association for Information Systems Member of the Academy of Science of South Africa Andrew Mellon Professor (2011) in South Africa Velux Visiting Professor (2012) at Copenhagen Business School As Director of the Institute for Innovation and Technology Management, Professor Ngwenyama leads the SSHRC-funded project 'Accelerating Digital Technology Adoption In Canadian Companies' and oversees several ongoing research initiatives including Organizational Innovation and Design, Decision modeling for Technology Management, Information Technology and Global Development, and Critical Social Science Research Methods. His research has secured significant funding and has been applied in both developed and developing country contexts. Professor Ngwenyama maintains active research collaborations across multiple continents, working with scholars from Europe, Africa, and North America. His research group focuses on critical examination of technology implementation, particularly examining power dynamics, social implications, and ethical considerations in digital transformation processes.

Barbara BordalejoView profile

Professor

• Digital Humanities
• Textual Scholarship
• Scholarly Editing
• +4 more

Barbara Bordalejo is a Professor at the University of Lethbridge with dual appointments in Digital Humanities and English . She serves as President of the Canadian Society for Digital Humanities/Société canadienne des humanités numériques and has held leadership roles in Global Outlook:: Digital Humanities and the European Association of Digital Humanities . Her work focuses on: Digital Editions : Leading the CantApp project (2020) for mobile access to Chaucer’s Canterbury Tales , co-developing the Textual Communities platform with Peter Robinson, and editing Darwin’s Origin of Species . Textual Scholarship : Exploring phylogenetic methods for manuscript analysis, collation techniques, and the intersection of bioinformatics with textual criticism. Equity in Digital Humanities : Investigating gender and minority representation through publications like Minority Report (2018) and co-organizing ADHO diversity workshops (2017–2022). AI and Academic Integrity : Analyzing false positives in AI detection software (2025) and advocating for responsible AI policies in education. Her research projects include collaborations with Richard North and Peter Robinson on digital tools, work with Roopika Risam on intersectional DH, and contributions to global DH initiatives across disciplines and regions.

• Mechanical Engineering
• Vibration Analysis
• Structural Optimization
• +4 more

Jean-Marc Drouet is a Full Professor at Université de Sherbrooke since 2017, specializing in Vibration Analysis , Mechanical Engineering , and Sports Engineering . His career at Université de Sherbrooke spans from Lecturer (1995-2003) to Assistant Professor (2003-2008), Associate Professor (2008-2017), and currently Full Professor. PhD in Mechanical Engineering (2003), Université de Sherbrooke Master's in Mechanical Engineering (1994), Université de Sherbrooke Bachelor's in Mechanical Engineering (1991), Université de Sherbrooke Drouet's research explores: Vibration Analysis in road cycling, including perceptual thresholds and shock transmission to cyclists' hands Sports Engineering innovations like suspension stems and instrumented brake hoods for comfort assessment Structural Optimization using genetic algorithms for steel supports and bicycle frames Human Perception studies in dynamic comfort and biomechanical loads Ergonomic Design of cycling equipment and pedagogical tools for engineering education Key research trends from his publications include: Application of genetic algorithms to structural optimization challenges Development of dynamic comfort metrics for cycling equipment Integration of biomechanical measurements with structural analysis Focus on hand-arm vibration exposure and mitigation strategies Interdisciplinary approach combining mechanical engineering , psychophysics , and biomedical engineering Continued exploration of steel material properties in bicycle design Scientific recognitions: Institutional Teaching Excellence Award (2009-2010) Best Paper Award at The Engineering of Sport 11 (2016) His work has attracted significant funding through: NSERC Collaborative Research and Development Grant ($590,686) FRQSC Research Support ($196,544) CREAS Internal Infrastructure Funding ($157,000) CRIJEST Chair Collaborations ($830,000 total funding)

Pablo LemosView profile

Research Fellow

• Cosmology
• Machine Learning
• Astrophysics
• +3 more

Pablo Lemos is a postdoctoral Research Fellow at the Montrel Institute for Learning Algorithms (MILA) and the CIELA institute at the University of Montreal, where he is affiliated with the Department of Physics. He co-leads the accelerated forward modelling group at the Simons Collaboration in Learning the Universe and is a member of the Dark Energy Survey (DES) collaboration. Research Focus Lemos specializes in applying machine learning techniques to astrophysics and cosmology problems. His core research areas include: Graph neural networks for cosmological simulations Symbolic regression methods for data analysis Simulation-based inference techniques Bayesian inverse problem solving Large-scale structure analysis Publication Analysis Lemos's recent publications (2024-2025) demonstrate strong interdisciplinary work combining cosmology, astrophysics, and machine learning. Major themes include cosmological constraints from galaxy clustering and weak lensing, advanced Bayesian inference methods using diffusion models, and applications of neural networks to astrophysical data. Approximately 60% of recent publications focus on machine learning applications in cosmology, while 25% address astrophysical inverse problems, and 15% explore cometary science and planetary physics. Collaborations and Groups Co-leader of accelerated forward modelling group at Simons Collaboration in Learning the Universe Active member of Dark Energy Survey (DES) collaboration

Melike Erol KantarciView profile

Associate Professor

• 5G and 6G Networks
• Artificial Intelligence (AI)
• Tactile Internet
• +9 more

Dr. Melike Erol-Kantarci is an Associate Professor at the School of Electrical Engineering and Computer Science, University of Ottawa, and a Canada Research Chair in AI-enabled Next-Generation Wireless Networks. She founded the Networked Systems and Communications Research (NETCORE) Laboratory and holds a courtesy appointment as Assistant Professor at Clarkson University's Electrical and Computer Engineering Department. With over 6,000 citations and an h-index of 40, she contributes to IEEE as a Senior Member, chairs the Green Smart Grid Communications special interest group, and serves as Editor for IEEE Communications Letters and IEEE Access . Research Focus: 5G/6G wireless networks AI/ML-driven network optimization Smart grid communications Cyber-physical system security Edge computing and IoT Reconfigurable Intelligent Surfaces (RIS) Scientific Contributions: Her recent publications highlight generative AI integration in 6G, intent-driven network management using hierarchical reinforcement learning, physical layer security for connected vehicles, and explainable AI frameworks in communications. The 15 most recent works (2024-2025) span topics like beamforming optimization, federated learning security, UAV-assisted networks, and semantic communication systems. Leadership: As director of the NETCORE Laboratory, she leads cutting-edge research in networked systems, bridging wireless communication paradigms with energy sustainability and security requirements for next-generation networks.

• Quantum Computing
• Quantum Cryptography
• Classical Cryptography
• +6 more

Gilles Brassard is a Full Professor in the Department of Computer Science and Operations Research at the Université de Montréal's Faculty of Arts and Sciences. He holds the Canada Research Chair in Quantum Computing and serves as Scientific Director of INTRIQ (Institut transdisciplinaire d'information quantique). His affiliations include membership in the Centre de recherches mathématiques (CRM), Institut Courtois, LITQ (Laboratoire d’informatique théorique et quantique), and talents (Laboratoire d'Intelligence Artificielle pour la Cybersécurité). Brassard's research spans quantum computing, quantum and classical cryptography, foundations of quantum mechanics, and privacy protection. He pioneered quantum teleportation and quantum cryptography, demonstrating how quantum mechanics enables unconditionally secure communication. His work explores quantum advantages in computation, including algorithms that could break classical cryptography while quantum cryptography provides countermeasures. Key concepts he developed include quantum teleportation (inspiring Star Trek-like applications) and quantum pseudo-telepathy games. His recent publications reveal strong focus on quantum key distribution security proofs, relativistic cryptography for secure positioning, and privacy protection against data brokers. Trends show increasing emphasis on practical quantum cryptography implementations, noise resilience in quantum communication, and intersections with machine learning. The 2023-2025 articles particularly address real-world quantum security challenges and foundational quantum information questions. Gerhard-Herzberg Canada Gold Medal for Science and Engineering Killam Prize in Natural Sciences Officer of the Order of Canada Fellow of the Royal Society Brassard has supervised over 40 graduate students across quantum information topics, including quantum algorithms, entanglement simulation, and privacy-preserving systems. His current research is funded by major Canadian grants including NSERC Discovery Program ($20965), FRQNT Strategic Regroupments, and CIFAR. Recent projects include QUORUM (Québec Ontario Consortium on Quantum Protocols) and quantum machine learning initiatives. He leads the theoretical quantum information group within LITQ, focusing on quantum communication complexity and cryptographic applications of quantum phenomena.

• Granular Media
• Solid mechanics
• Constitutive and multiscale modeling
• +6 more

Émilien Azéma is a Professor at the University of Montpellier since 2023, affiliated with the Department of Mechanics in the Faculty of Sciences and the Mechanics and Civil Engineering Laboratory (LMGC). Since 2024, he also holds an Associate Professor position at Polytechnique Montréal in the Department of Civil, Geological and Mining Engineering. Primary Institution: University of Montpellier, France Secondary Appointment: Polytechnique Montréal, Canada Research Recognition: French University Institute (IUF) Research Chair (2020-2025) Dr. Azéma received his complete education at the University of Montpellier, earning degrees in Mathematics, Solid Mechanics, and completing his Doctorate and Habilitation (HDR) in Mechanics. His doctoral research focused on railway ballast behavior using Discrete Element Method (DEM) simulations, supported by a joint CNRS and SNCF grant. Licence/Maîtrise (Master 1) in Mathematics DEA (Master 2) in Solid Mechanics Doctorate in Mechanics Habilitation (HDR) in Mechanics His research program centers on the micromechanics of granular systems with realistic microstructure. Using innovative Discrete Element Method (DEM) approaches, he systematically investigates the nonlinear effects of particle shape characteristics (angularity, non-convexity, elongation) and size polydispersity on granular rheology across flow regimes from quasi-static to rapid. His work extends to evolving granular systems where particles can fragment or undergo large deformations, with applications to geomechanical materials, industrial powders, and extraterrestrial granular systems. An analysis of his recent publications (2023-2025) reveals a strong emphasis on particle shape effects, cohesive strength mechanisms, and polydisperse system behavior. His research bridges fundamental granular physics with practical applications in railway engineering, planetary science (particularly asteroid regolith modeling), and geomechanics, appearing in high-impact journals including Physical Review E, Granular Matter, and Icarus. Dr. Azéma's significant research contributions have been recognized through: A prestigious Research Chair from the French University Institute (IUF) as Junior Member (2020-2025) An extensive publication record with 81 publications across multiple high-impact journals He teaches core courses in solid mechanics, numerical computation, finite element method, discrete approaches, and rheology of granular media. His administrative responsibilities include: International affairs coordinator at the Faculty of Sciences (since 2018) Responsible for the first year curriculum of the Mechanical Engineering Master's program (since 2021) His primary research laboratory is the Mechanics and Civil Engineering Laboratory (LMGC) at the University of Montpellier, where he conducts his investigations into granular media and solid mechanics phenomena, with significant collaborations extending to Polytechnique Montréal and international institutions.

Wilson Q. WangView profile

Professor

• Signal Processing
• Artificial Intelligence
• Machine Learning
• +6 more

Wilson Q. Wang is a Professor at Lakehead University's Department of Mechanical and Mechatronics Engineering, where he serves as Lakehead Research Chair, Director of Mechatronics Engineering, and PhD Graduate Program Coordinator. He founded and directs both the Intelligent Mechatronics Systems Lab and Electric Vehicle Lab, supported by CFI/ORF grants. With cross-appointment in Electrical and Computer Engineering, he maintains an adjunct professorship at the University of Waterloo. PhD, Mechatronics Engineering, University of Waterloo MEng, Industrial Engineering, University of Toronto MSc, Mechanical Engineering, Northeastern University, China BASc, Electro-mechanical Engineering, SIT, China Dr. Wang's research focuses on the intersection of artificial intelligence and mechanical systems, specializing in signal processing techniques for condition monitoring, fault diagnosis, and prognostics. His work develops intelligent control systems that enhance machinery reliability through early fault detection and predictive maintenance strategies. The research spans both theoretical development of novel algorithms and practical implementation in industrial settings, with particular emphasis on mechatronic systems and electric vehicles. His publication record demonstrates consistent contributions to high-impact journals including IEEE Transactions on Fuzzy Systems, IEEE Transactions on Instrumentation and Measurement, and IEEE/ASME Transactions on Mechatronics. The work shows an evolving trajectory from fundamental signal processing techniques toward increasingly sophisticated AI-driven prognostic systems, with growing emphasis on real-time implementation and industrial applications. CFI John Evens Leaders Grant Award (2022) Excellent Teaching Award, Lakehead University (2018) Distinguished Researcher Award, Lakehead University (2017) NSERC DG Accelerator Grant Award (2016) Innovation Award, Lakehead University (2015) Dr. Wang has supervised an extensive research team including 9 postdoctoral fellows, 15 PhD students, and nearly 40 MSc students. His research has been supported by multiple NSERC grants (DG, AG, CRD, DAS, EG, IG), CFI (JELF, NOF), ORF, and industry partners including Bombardier Transportation, Siemens Mahon Electric, and Techform Group. He serves as Associate Editor for several prestigious journals including IEEE/ASME Transactions on Mechatronics and IEEE Transactions on Instrumentation and Measurement. He directs two specialized research facilities: the Lab for Intelligent Mechatronic Systems (LIMS) and the Lab for Electric Vehicles (LEV), which support his team's work on smart sensors, fault diagnosis systems, and intelligent control applications across various mechanical and electromechanical systems.

Adrian IlincaView profile

Professor

• Renewable Energy
• Wind Energy
• Solar Energy
• +6 more

Adrian Ilinca is a Professor at the Department of Mechanical Engineering within École de Technologie Supérieure (ÉTS), Université du Québec . His research focuses on Renewable Energy systems, particularly Wind Energy and Solar Energy , with specialization in Cold Climate Technology Adaptation , Energy Storage , and CO2 Capture solutions. Director: ÉDÉ – ÉTS Sustainable Energy Laboratory Research Axes: Sensors & Connectivity, Circular Economy, Intelligent Systems Key Expertise: Thermal Systems, Hybrid Energy, Wind Turbine Aerodynamics His academic contributions span Computational Fluid Dynamics , Machine Learning for energy systems, and Hybrid Renewable Technologies . Recent publications emphasize Hydrogen Liquefaction , Battery Storage Integration , and Wind Energy Optimization in extreme environments. As principal supervisor, he mentors over 20 graduate students in projects ranging from Wind Turbine Icing to Microgrid Decarbonization . His work frequently addresses Arctic Energy Challenges and Industrial Sustainability through innovative system design.

Simon DayView profile

Adjunct Professor

• Reactor Physics
• Safety Analysis
• Criticality Safety
• +4 more

Simon Day is an Adjunct Professor in the Department of Engineering Physics at McMaster University. Since 1998, he has led the Reactor Analysis group at the McMaster Nuclear Reactor, focusing on experimental and computational nuclear reactor analysis. His research interests include: Reactor physics and safety analysis methodologies Code benchmarking against experimental data Positron beam-line design and optimization Criticality safety and reactor operations Computational simulations of nuclear systems His publications (2010-2024) demonstrate strong focus on reactor physics validation through experimental measurements and simulations. Recent work emphasizes computational fluid dynamics (CFD), gamma heating analysis, fuel depletion calculations, and code benchmarking. The research consistently integrates experimental data with simulation tools like Serpent-2, OSCAR-4, and PARET-ANL for reactor safety and optimization. He leads the Reactor Analysis group at McMaster Nuclear Reactor, conducting research in nuclear instrumentation, safety validation, and reactor operations. No awards, grants, or student advising details are mentioned in available sources.

• Nuclear Engineering
• Thermal-Hydraulics
• Heat Transfer
• +3 more

Laurence Leung is an Adjunct Professor in the Department of Engineering Physics at McMaster University, specializing in nuclear engineering and thermal-hydraulics. His research focuses on heat transfer and critical heat flux (CHF) in supercritical fluids, particularly for Canadian SCWR (Supercritical Water-Cooled Reactor) designs. Key research areas: Nuclear Engineering, Thermal-Hydraulics, Heat Transfer, Fluid Dynamics, Reactor Design His scholarly activity highlights trends in SCWR development, CHF prediction models, and thermal-hydraulics safety analysis. Recent work includes collaborations with the IAEA, contributions to the Ninth International Symposium on SCWRs, and experimental studies on supercritical water and carbon dioxide flow behavior. Academic contributions include advanced modeling of reactor fuel geometries, validation of computational tools for heat transfer analysis, and international benchmarking of CFD simulations for tube and channel systems.