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Professor Jiyuan Tu is a Professor in the Department of Mechanical and Automotive Engineering at RMIT University's School of Engineering. He specializes in computational fluid dynamics (CFD), multiphase flows, and their applications in renewable/nuclear energy, biomedical engineering, and built environment systems. His research has led to over 500 peer-reviewed articles, 9 books, and $10M+ in ARC grants. He has supervised over 50 postgraduate students and received prestigious awards such as the RMIT Research Excellence Award (2012) and Fulbright Senior Scholar Award (2008). Research interests include CFD modelling of bioaerosol transport, drug delivery systems, and thermal energy storage. He pioneered numerical models for multiphase flows, contributing to software implementations in industries. Notable works include books on CFD and multiphase flow analysis, and leadership in international conferences like COBEE 2018. He holds honorary professorships at Tsinghua University and is Editor-in-Chief of the Experimental and Computational of Multiphase Flow journal. Industry experience includes roles at ANSTO (1996-2001). Awards span fellowships from JSPS, KOSEF, and Fulbright programs. Grants include ARC Discovery, Linkage, and LIEF projects. His work ranks him among the world’s top researchers in pebble bed reactors and airborne infection studies (SciVal 2016-2025).

• Computational Fluid Dynamics (CFD)
• Multiphase Flows
• Thermal Sciences
• +4 more

Associate Professor Fangbao Tian is a distinguished researcher and academic at UNSW Canberra's School of Engineering and Technology, where he also serves as Deputy Head of School for Research since July 2023. Previously, he held positions as Senior Lecturer (2017-2021) and Lecturer (2014-2017) at the same institution after completing postdoctoral research at Vanderbilt University. His academic journey began with a BSc (2006) and PhD (2011) in Theoretical and Applied Mechanics and Engineering Mechanics from the University of Science and Technology of China. Dr. Tian's research focuses on Computational Fluid Dynamics (CFD) tools for complex flows and fluid-structure interaction, with particular emphasis on bio-inspired applications. His work spans modeling laryngeal aerodynamics and vocal-fold vibration, fluid-structure interaction of plates in viscous fluid, fish swimming and insect flight, blood flow dynamics, and non-Newtonian flow phenomena. Recent work has expanded into Martian atmosphere aerodynamics, showing his research's growing interdisciplinary nature. His extensive publication record demonstrates consistent contributions across fluid dynamics, with recent trends showing increasing focus on compressible flows, bio-inspired flight systems, heat transfer applications, and computational methods like Lattice Boltzmann approaches. The research shows strong connections between fundamental fluid mechanics and practical applications in aerospace, biomedical engineering, and environmental systems. UNSW Canberra Goldstar Award 2022 IEEE Outstanding SMCS Chapter Award 2021 Outstanding Volunteer Award 2021 UNSW Canberra Silverstar Award 2018 UNSW Canberra Silverstar Award 2017 Journal of Fluids and Structures Highly Cited Research 2017 ARC DECRA 2016 Dr. Tian actively supervises PhD students across diverse topics including bushfire-enhanced wind loads, bio-inspired flight on Mars, flow control optimization, and fluid-structure interactions in compressible flows. He has secured over $5 million in external funding as Chief Investigator, including significant Australian Research Council projects examining Martian atmosphere aerodynamics, bio-inspired flapping wings, and cardiovascular flow modeling. His editorial roles include Associate Editor for Journal of Fluids and Structures and Scientific Reports, reflecting his standing in the fluid dynamics research community.

• Computational Fluid Dynamics
• Fluid-Structure Interaction
• Biomechanics
• +5 more

Craig O'Neill is an Associate Professor in Geophysics/Remote Sensing at the School of Earth & Atmospheric Sciences, Faculty of Science, Queensland University of Technology (QUT). His research spans geodynamics, planetary science, geophysics, and engineering geology, with a strong focus on understanding Earth and planetary evolution through computational modeling and geophysical data analysis. His research interests include Geophysics, Geodynamics, Remote Sensing, Planetary Science, Engineering Geology, Geochemistry, and Geology . He applies advanced numerical methods to model planetary interiors, tectonic processes, and geohazards, with recent work exploring early Earth crust formation, Venusian core dynamics, exoplanet thermal evolution, and applied geophysical techniques for engineering and environmental monitoring. The trend in his recent publications shows a strong interdisciplinary focus, combining computational geophysics with planetary science and Earth systems analysis. His work appears in leading journals such as Nature , Science Advances , and Geophysical Research Letters , covering topics from asteroid impacts and craton formation to ambient noise tomography and groundwater response to climate change. Professional Memberships: Australian Society of Exploration Geophysicists American Geophysical Union Australian Geomechanics Society Craig O'Neill supervises research students in areas such as lunar seismology and planetary geodynamics. While no specific grants are listed in the provided text, his extensive publication record and active research programs suggest ongoing funding support. He has developed open-source tools like Planet_LB for lattice-Boltzmann modeling of planetary systems. He is actively involved in the geophysics community, with scholarly profiles on ORCID, Google Scholar, and Scopus, and shares his research via X (formerly Twitter). His work bridges fundamental planetary science with practical geophysical applications.

• Geophysics
• Geodynamics
• Remote Sensing
• +4 more

Professor Tilak Chandratilleke is a faculty member in the School of Civil and Mechanical Engineering at Curtin University, part of the Faculty of Science and Engineering. He holds a PhD from the University of Cambridge and has extensive post-nominals including MIEAust, CPEng, and MASME. His research focuses on advanced thermal engineering, computational fluid dynamics (CFD), and heat transfer optimization. Key areas of interest include thermal energy storage systems, fluid flow in curved ducts, and thermal design for industrial applications. He also serves in the Office of the Provost, contributing to academic governance. Research Interests: - Computational Fluid Dynamics (CFD) modeling of complex thermal systems. - Heat and mass transfer in energy storage and manufacturing processes. - Design and analysis of heat exchangers and thermal recuperators. - Fluid dynamics in curved geometries and secondary vortex structures. - Applications in renewable energy systems and advanced manufacturing. Selected Publications (2022–2010): - Investigated high-temperature thermal energy storage using CaCO₃/Al₂O₃ reactors (2022). - Developed numerical models for metal hydride thermal storage systems (2021). - Analyzed boiling heat transfer in curved ducts and laser-assisted machining thermal effects (2020–2019). - Advanced CFD methodologies for convective boiling and turbulent flow modeling (2018–2016). - Pioneered studies on Dean vortices and microfluidic heat enhancement (2011–2010). Teaching: - Thermodynamics and Heat Transfer. - Fluid Mechanics and Engineering Applications. Labs/Teams: - Involved in Curtin’s thermal energy and advanced manufacturing research groups. - Collaborates with industry partners on renewable energy and thermal system optimization projects.

• Computational Fluid Dynamics
• Heat and Mass Transfer
• Thermal Design
• +3 more

Associate Professor Pierre Le Clech is a leading expert in membrane science and chemical engineering at the University of New South Wales , affiliated with the UNESCO Centre for Membrane Science & Technology. His work focuses on optimizing membrane processes for water and wastewater treatment, particularly addressing fouling mechanisms caused by biopolymeric materials and algal blooms. Current research explores fouling characterization, energy-efficient desalination, and membrane regeneration strategies. He contributes to Desalination and Water Treatment as Associate Editor, and serves on the editorial boards of Membrane Water Treatment and Process Safety and Environmental Protection . Research Trends : Recent publications highlight advancements in algal fouling analysis, graphene oxide membrane applications, and computational modeling of fouling dynamics. His work bridges chemical engineering with environmental technology , emphasizing sustainable solutions for global water challenges. Scientific Awards : Associate Editor, Desalination and Water Treatment Editorial Board Member, Membrane Water Treatment and Process Safety and Environmental Protection Supervision & Collaboration : He actively supervises projects in municipal wastewater treatment, potable water systems, and membrane fouling mitigation. His team collaborates with industry partners on innovations like solar-integrated desalination and biofouling prevention.

• Membrane and Separation Technologies
• Chemical Engineering
• Water Treatment Processes
• +3 more

Prof Adrian Sheppard is a Professor in the Department of Materials Physics at The Australian National University (ANU). He holds a B.Sc. (Hons) from the University of Adelaide and a Ph.D. from ANU. His research focuses on porous media analysis, X-ray tomography, and carbon sequestration, with expertise in fluid dynamics, geologic storage, and advanced imaging techniques. He leads projects on CO2 geostorage, multiphase flow modeling, and high-resolution tomographic imaging. His work bridges materials physics, environmental science, and engineering, addressing challenges in energy storage and climate mitigation. He has supervised numerous research students and collaborates on initiatives like the ARC Training Centre for Multiscale 3D Imaging. Key research interests include pore-scale fluid dynamics, supercritical CO2 behavior, and X-ray microtomography applications. Over 200 publications highlight his contributions to understanding fluid trapping mechanisms, beam hardening correction in tomography, and multiscale imaging techniques. He has pioneered methods for analyzing heterogeneous materials and improving tomographic image quality. His projects span geologic carbon storage, additive manufacturing inspection, and environmental fluid dynamics. Prof Sheppard has secured 26 research grants, including projects on CO2 sequestration, X-ray source optimization, and advanced manufacturing. He advises on imaging technologies and leads ANU's efforts in multiscale materials characterization. His lab focuses on applying cutting-edge imaging tools to solve real-world problems in energy and environmental science.

• Materials Physics
• Porous Media Analysis
• X-ray Tomography
• +3 more

Professor YuanTong Gu is the Pro Vice-Chancellor (Research Career Advancement) and Head of the School of Mechanical, Medical and Process Engineering at Queensland University of Technology (QUT). He holds an ARC Future Fellowship and leads the Laboratory for Advanced Modelling and Simulation in Engineering and Science. His research focuses on computational mechanics, biomechanics, and nanotechnology, with over $40M in secured research funding since 2000. He has supervised over 15 PhD students and collaborates with global institutions including Tsinghua University and the University of California. His awards include the International Computational Methods Award (2017) and ICACM Computational Mechanics Award (2017). Prof. Gu's work spans interdisciplinary projects in joint biomechanics, advanced materials, and AI-driven engineering solutions. Education: PhD (National University of Singapore), Graduate Certificate in Education (QUT). Research Groups: Leads a team of 3 academics, 2 ARC Future Fellows, and 15+ PhD students. Key projects include diamond nanothread composites, AI in biomedical devices, and fracture detection frameworks. His group collaborates with industry leaders and global universities to advance computational methods and materials science. Editorial Roles: Associate Editor of Engineering Analysis with Boundary Elements and Applied Mathematical Modelling , among others. Conference leadership includes chair roles in international computational mechanics conferences since 2012.

• Computational Mechanics
• Biomechanics
• Mechanical and Material Engineering
• +3 more

Dr. Sergio Galindo Torres is an Adjunct Associate Professor at the School of Civil Engineering, University of Queensland (UQ). His research focuses on geotechnical engineering, fluid dynamics, and computational modeling of granular and porous media. He specializes in discrete element methods (DEM), lattice Boltzmann methods (LBM), and their coupling for simulating particle-fluid interactions. His work addresses transient two-phase flow, hydraulic fracturing, dispersion in porous media, and erosion mechanisms. His publications (45 journal articles, 31 conference papers, and technical reports) highlight his expertise in micromechanical analysis and numerical simulation of complex geological systems. Recent studies examine Péclet-number-dependent dispersion and airblast hazards in block caving. The 15 most recent articles reflect trends across computational geomechanics, with emphasis on: Fluid flow in static/dynamic porous media DEM-LBM coupling for granular-fluid systems Two-phase displacement under varying boundary conditions Airblast hazard simulation in mining Liquefaction micromechanics Capillary pressure-saturation dynamics Dr. Galindo Torres collaborates with researchers like Alexander Scheuermann and Ling Li, and his work appears in journals such as Water Resources Research , Physical Review , and Computers and Geotechnics . He does not list specific awards or advisees in this dataset.

• Geotechnical Engineering
• Fluid Dynamics
• Computational Modeling
• +5 more

Associate Professor Saiied Aminossadati is a faculty member at the University of Queensland's School of Mechanical and Mining Engineering, with affiliate positions at the Future Autonomous Systems and Technologies (FAST) and Centre for Multiscale Energy Systems. He holds a BEng (1989), MEng (1994), and PhD (1999) in Mechanical Engineering, along with a Graduate Certificate in Higher Education. His research focuses on thermofluids, mine ventilation systems, computational fluid dynamics applications in mining, fibre-optic sensing technologies, and gas management systems. Specific interests include porous media flow, underground mine ventilation optimization, energy systems modeling, and industrial fluid dynamics. With 180+ publications spanning mining ventilation, energy systems, and fluid mechanics, recent work demonstrates strong emphasis on computational modeling of industrial processes. Research trends show increasing focus on renewable energy applications (solar collectors, nanofluids), mining safety (methane dispersion, aerosol transmission), and sustainable resource recovery (plastic depolymerization, hydraulic fracturing). He has secured 16 research grants totaling $2.65M and serves as academic advisor for 26 research higher degree students (18 graduated, 8 current). Keynote speaker at international conferences including Mine Ventilation Symposium (2009) and Fibre Optic Sensing Conference (2015). Reviewer for 30+ international journals in mechanical and mining engineering disciplines.

• Thermofluids
• Mine Ventilation
• Computational Fluid Dynamics
• +4 more

Yeoh Chin Vern is a Lecturer at the Malaysia School of Engineering, Monash University. He holds a PhD in Mechanical Engineering (2022) focusing on Direct Numerical Simulation, Study, and Quantification of Fractal Grid-Generated Turbulent Flows . His research expertise spans Computational Fluid Dynamics (CFD), Lattice Boltzmann methods, turbulent flows, and multiphysical modeling. He has contributed to projects on graphene-enhanced electronics cooling and ion-exchange membrane dynamics. His research interests include turbulence modeling, nonlinear dynamics, and applications in microfluidics and heat transfer. Notable work involves fractal grid-generated turbulence optimization, pressure wave dynamics in CFD, and surface roughness effects in microchannel flows. Recent publications (2020–2025) highlight advancements in lattice Boltzmann simulations, Reynolds stress modeling, and fractal grid configurations. He collaborates on interdisciplinary projects addressing sustainable cooling solutions and ion partitioning mechanisms. Yeoh has been a Chief Investigator (CI) on two research projects: Graphene Enhanced Devices for Electronics Cooling (2024–2026) and Decoding the Role of Valency in Multi-valent Ion Partitioning through Ion-Exchange Membranes (2023–2026).

• Computational Fluid Dynamics
• Turbulent Flows
• Lattice Boltzmann Method
• +5 more

Dr. Lin Tian is a Senior Lecturer in the School of Engineering at RMIT University, Melbourne, Australia. She holds expertise in multi-scale modeling of fluid dynamics and micro/nano particles, with a focus on aerosol transport, inhalation toxicity, and drug delivery in respiratory systems. Her research integrates computational methods like Lattice Boltzmann simulations to solve multiphase flow problems. Current projects include developing risk assessment platforms for inhaled carbon nanotubes and hydrodynamic modeling for underwater vehicle systems. Her academic journey includes roles as a Research Fellow at RMIT (2015–2018) and Assistant Professor at SUNY Canton, USA (2008–2014). She leads funded projects such as the DECRA-supported multi-scale risk assessment platform and DSTG-funded underwater vehicle hydrodynamics research. Teaching interests span advanced thermo-fluids, mechanics of solids, and computational fluid dynamics. Research highlights include nasal airflow modeling, fiber transport dynamics, and HVAC system optimization for pathogen control. Awards include the DECRA grant (2018), and her work addresses critical areas like occupational exposure, drug delivery efficacy, and sustainable building systems. Dr. Tian is open to supervising Masters and PhD students in computational fluid dynamics and multiphase flow applications.

• Multi-scale modeling
• Aerosol transport
• Fluid dynamics
• +6 more

Dr. Morteza Namvar is a Senior Lecturer at The University of Queensland Business School and an Affiliate of both the Centre for the Business and Economics of Health and Centre for Enterprise AI. His work bridges business contexts with advanced computational techniques, focusing on practical applications of artificial intelligence in organizational and healthcare settings. Faculty of Business, Economics and Law - School of Business Centre for the Business and Economics of Health Centre for Enterprise AI - Faculty of Engineering, Architecture and Information Technology Dr. Namvar specializes in Machine Learning (ML), Natural Language Processing (NLP), and Large Language Models (LLMs), with research concentrated in three primary areas: leveraging NLP and LLMs for enhanced theory building in Information Systems research, text feature engineering using advanced language models, and personalization/user experience enhancement through contextual understanding. His work systematically analyzes unstructured text data to develop robust theoretical constructs and improve machine learning model capabilities. His recent publications reveal strong trends in healthcare applications of LLMs, hate speech detection, and cryptocurrency market analysis through social media. The research consistently applies NLP techniques to solve real-world problems across healthcare, finance, and e-commerce domains, with particular emphasis on sociotechnical aspects of technology implementation. Dr. Namvar has successfully secured competitive funding including the prestigious UQ Knowledge Exchange & Translation Fund grant for developing social media monitoring tools for small businesses, and multiple grants from Medical Protection Society Limited for machine learning applications in healthcare systems. 2021-2022: Developing a context-specific social media monitoring tool to empower Australian small business (UQKx&T Fund) 2021: Enhancing Education Development: Analysing Members' Feedback Using Machine Learning Techniques (Medical Protection Society) 2021: Investigating the effective use of data and analytics in Medical Protection Systems (Medical Protection Society) He currently supervises five PhD students working on NLP and LLM applications in healthcare, data privacy regulation, and patient outcomes. His research impacts include leading machine learning projects with industry partners like Medical Protection Society and PA Hospital, where his NLP techniques have helped improve organizational strategies through text data analysis.

• Machine Learning
• Natural Language Processing
• Large Language Models
• +7 more

Professor Peyman Mostaghimi is a Professor of Minerals and Energy Resources at the University of New South Wales (UNSW) Sydney within the Faculty of Engineering, School of Civil and Environmental Engineering. He joined UNSW in 2014 after completing postdoctoral research at Imperial College London, where he focused on multiphase flow and transport in porous media. Professor Mostaghimi earned his PhD from Imperial College London and holds an MSc in Mechanical Engineering with specialization in Fluid Mechanics along with dual BSc degrees in Mechanical and Chemical (Reservoir) Engineering from Sharif University of Technology. His educational background has provided a strong foundation for his interdisciplinary research at the intersection of engineering, geoscience, and computational methods. His research spans computational fluid dynamics, natural gas extraction, subsurface reservoir simulation, pore-scale modeling of displacement processes, and flow and transport in porous media with applications to energy extraction, mineral recovery, subsurface hydrology, and environmental studies. Mostaghimi's work integrates advanced computational techniques with experimental validation to address complex challenges in subsurface resource management. He has pioneered approaches combining machine learning with traditional numerical methods to enhance the accuracy and efficiency of digital rock physics simulations. His recent publications (2024-2025) demonstrate a strong focus on multi-scale modeling approaches, bridging pore-scale phenomena to continuum-scale applications. His research group has made significant contributions to understanding multiphase flow in porous media, hydrogen storage, CO2 sequestration, and mineral characterization using cutting-edge imaging and computational techniques. The trend shows increasing integration of machine learning and deep learning techniques with traditional physics-based modeling to solve complex subsurface engineering problems. Professor Mostaghimi has received international recognition including being ranked among the world's top 2% scientists in Energy by Stanford University (2020). He serves as a Council Member for the International Society for Porous Media and as an Associate Editor for the Journal of Petroleum Science and Engineering. His professional affiliations include active membership in SPE (Society of Petroleum Engineers), InterPore, AGU (American Geophysical Union), and IAMG (International Association for Mathematical Geosciences). As director of the MUTRIS research group (http://mutris.unsw.edu.au), Professor Mostaghimi leads a team investigating multiphase flow and transport in porous media. His research has significant implications for energy transition technologies including carbon capture and storage, hydrogen storage, and sustainable mineral extraction. The group's work combines experimental techniques like X-ray micro-CT imaging with advanced computational methods to develop predictive models of subsurface processes.

• Computational Fluid Dynamics
• Pore-Scale Modeling
• Multiphase Flow in Porous Media
• +7 more

Ean Hin Ooi is an Associate Professor in the School of Engineering at Monash University Malaysia, where he leads the Computational Modelling team. He holds a PhD in Mechanical Engineering from Nanyang Technological University, Singapore, and a Bachelor's degree in Mechanical Engineering from the University of Technology, Malaysia. His research spans biomedical engineering, computational modeling, and numerical methods, with applications in cancer therapy and medical diagnostics. Doctor of Philosophy, Mechanical Engineering, Nanyang Technological University (NTU), 2009 Bachelor's Degree, Mechanical Engineering, University of Technology, Malaysia Dr. Ooi’s research focuses on the application of mathematical and computational modeling to understand biophysical phenomena in healthcare. His work targets improving cancer treatments such as thermal ablation (radiofrequency, cryoablation, photothermal), developing diagnostic tools like shear wave elastography for kidney disease, and advancing numerical techniques including meshless and boundary element methods. He is a pioneer in the radial basis integral equation method, contributing significantly to computational mechanics. The recent publications reflect a strong trend in interdisciplinary research combining engineering, medicine, and materials science. Key themes include thermal therapy optimization, nanomedicine (gold nanorods, graphene), microfluidics, and machine learning integration in sensor systems. His modeling expertise extends from organ-level simulations (liver, kidney) to nanoscale heat transfer, demonstrating versatility across scales and applications. Dr. Ooi serves as an Associate Editor for Computer Methods and Programs in Biomedicine and Journal of Mechanics in Medicine and Biology , highlighting his scholarly impact. He has received research funding for projects such as photothermal therapy for liver cancer and thermochemical ablation, indicating sustained grant support. He mentors students and is currently accepting PhD candidates in areas related to wound healing mechanics and computational prediction tools for thermal therapy. He is actively involved in professional service, including participation in the Asia-Pacific Society for Artificial Organs and visiting researcher roles at institutions like the University of Nottingham Malaysia. His lab, the Computational Modelling team, focuses on developing predictive frameworks for medical interventions, aiming to bridge computational science with clinical applications.

• Biomedical Engineering
• Computational Modeling
• Thermal Ablation Therapy
• +12 more

Dr. Travis Mitchell is a Lecturer at the School of Mechanical and Mining Engineering , The University of Queensland , and an affiliate of the Centre for Multiscale Energy Systems . He holds a PhD in Multiphase Computational Fluid Dynamics and dual degrees in Mechanical Engineering (BE Hons) and Mathematics (BSc). Education: PhD in Multiphase Computational Fluid Dynamics, The University of Queensland BE (Hons) in Mechanical Engineering, The University of Queensland BSc in Mathematics, The University of Queensland Research Interests focus on numerical modeling of multiphase fluid dynamics in porous media , with applications spanning CO2 electrolysis , hydrogen production via methane pyrolysis , biomedical fluid-structure interaction , and geomechanical fracture analysis . His methodological expertise includes Lattice Boltzmann techniques and high-performance computing . Recent Work Trends encompass multiphase transport in fractured media , gas diffusion electrode optimization , fiber-based air filter design , and thermocapillary flow modeling , reflecting his interdisciplinary impact in energy, health, and resource engineering. Scientific Recognition includes the ICMMES-CSRC Award for multiphase lattice Boltzmann research and an EAIT Citation for Excellence in Student Learning (2023) . Teaching Portfolio includes coordination of MECH2700: Computational Engineering and Data Analysis and lectures in MECH3780: Computational Mechanics and MECH6480: Computational Fluid Dynamics .

• Computational fluid dynamics
• Lattice Boltzmann methods
• Multiphase fluid dynamics
• +3 more