جست‌وجوی استاد و پژوهشگر

Bisan Alsalibiمشاهده پروفایل

مدرس

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۴ مورد دیگر

Dr. Bisan Alsalibi is a Lecturer at the School of Information Technology, Monash University (Malaysia campus). She holds a PhD (2017) and MSc (2013) in computer science from Universiti Sains Malaysia, specializing in Artificial Intelligence. Previously, she served as Senior Lecturer at Taylor's University (2022–2023) and Teaching Fellow at Universiti Sains Malaysia (2018–2020). Education: PhD in Computer Vision and Optimization (2014–2017), Universiti Sains Malaysia MSc in Artificial Intelligence (2011–2013), Universiti Sains Malaysia Research focuses on AI-driven solutions in feature selection, bio-inspired optimization techniques, and computer vision applications. Her work bridges membrane computing and real-world problem-solving, including privacy-preserving recommender systems for social networks. She currently supervises PhD students exploring bio-inspired algorithms for complex challenges. Advising & Grants: Acknowledged PhD project areas: Bio-inspired optimization techniques and evolutionary machine learning

Michael Milfordمشاهده پروفایل

استاد

• Robotics
• Neuroscience
• Computer Vision
• +۳ مورد دیگر

Professor Michael Milford is a robotics and computer vision expert at Queensland University of Technology (QUT), serving as Joint Director of QUT's Centre for Robotics. His research bridges robotics, neuroscience, and computer vision, focusing on biologically inspired navigation systems for autonomous vehicles and drones. He has pioneered projects like SeqSLAM and RatSLAM, emphasizing the synergy between biological intelligence and robotic systems. Research Interests: Milford explores navigation algorithms inspired by animal behavior, energy-efficient neural networks, and autonomous systems. His work aims to create robots capable of operating in dynamic environments through interdisciplinary collaboration with institutions like MIT, Harvard, and NASA's Jet Propulsion Laboratory. Awards & Recognition: Awarded the 2019 Batterham Medal and a $2.7M Australian Laureate Fellowship for his project on GPS-independent positioning systems. His work has produced highly cited papers in robotics and computer vision, including breakthroughs in visual SLAM and place recognition under varying conditions. Teaching & Collaboration: Milford mentors students in robotics and AI, launching initiatives like the STEM Storybook to inspire youth. He collaborates globally, emphasizing cross-disciplinary research to bridge gaps between fundamental and applied sciences. Labs & Projects: Leads QUT's Centre for Robotics, advancing technologies for autonomous systems. His projects explore neuromorphic computing, SLAM systems, and bio-inspired navigation, with applications in defense, transport, and environmental monitoring.

Judy Hartمشاهده پروفایل

دانشیار

• Renewable Energy Materials
• Photocatalysis
• Solar Cells
• +۵ مورد دیگر

Associate Professor Judy Hart is a materials scientist at the School of Materials Science & Engineering, UNSW Sydney , specializing in the development of semiconducting materials for renewable energy applications. Her work integrates computational (DFT) and experimental approaches to understand composition-property relationships in systems like solid solutions , heterostructures , and doped materials for photocatalysis and solar cells . She leads projects funded by ARC Discovery and Linkage grants , including work on photo-electro-catalysis systems and stabilizing ceramic materials . Education: PhD in Materials Engineering (Monash University, 2007), BEng (Materials) (Monash, 2002) Professional Experience: Senior Lecturer (UNSW, 2017–), Lecturer (UNSW, 2013–2017), University of Bristol (2007–2012) Research Interests Her research focuses on designing materials for renewable energy , particularly photoelectrochemical water splitting and organic oxidation reactions . Key areas include Density Functional Theory (DFT) , defect engineering , band gap tuning , and nanostructured materials . She investigates ferroelectric polarization effects , metal oxide heterostructures , and stability of battery components , with applications in hydrogen production , CO2 conversion , and advanced battery materials . Scientific Awards Ramsay Memorial Fellowship (University of Bristol, 2007–2009) Teaching Contributions She is co-author of the 1st Australian & New Zealand edition of "Materials Science and Engineering: An Introduction" , and teaches courses on computational materials science , corrosion-resistant surfaces , mechanical behavior of metals , and materials design .

Fangbao Tianمشاهده پروفایل

دانشیار

• Computational Fluid Dynamics
• Fluid-Structure Interaction
• Biomechanics
• +۵ مورد دیگر

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.

• Plasma Physics
• Fluid Dynamics
• Turbulence
• +۴ مورد دیگر

Dr Mahdi Davoodianidalik is a researcher in the Department of Nuclear Physics & Accelerator Applications at the Australian National University (ANU). He is affiliated with the Space plasma power and propulsion group and the Physics of fluids group, focusing on interdisciplinary research at the intersection of plasma physics, fluid dynamics, and space propulsion technologies. His research interests include Turbulence and wave-driven flows Plasma thrusters and electrothermal propulsion Fluctuation-induced forces and interactions Fluid-structure dynamics Thermal engineering of micro-thrusters Nonlinear phenomena in fluids Recent publications highlight his work on analogs of the Casimir effect in turbulent flows, passive propulsion mechanisms, and advanced propulsion systems using solid hydrocarbon propellants. He has contributed to understanding turbulence in both fundamental and applied contexts, with a focus on energy transfer and chaotic flow phenomena. His collaborations span ANU colleagues including Nicolas Francois and Michael Shats, with a strong emphasis on experimental and computational fluid dynamics.

Dikai Liuمشاهده پروفایل

استاد

• Robotics
• Field Robotics
• Human-Robot Collaboration
• +۵ مورد دیگر

Dikai Liu is a Distinguished Professor and Strategic Research Director at the University of Technology Sydney (UTS), Australia, within the School of Mechanical and Mechatronic Engineering . His work spans field robotics and human-robot collaboration (HRC) , focusing on autonomous systems for infrastructure maintenance, construction automation, and underwater operations. Key research areas: Robotics, Human-Robot Interaction, Bio-Inspired Design, Infrastructure Maintenance Recent publications highlight innovations in trust modeling for HRC, stiffness control in continuum robots, and sociotechnical frameworks for AI-driven robotic systems. His 15 most recent articles emphasize applications in bridge maintenance, construction automation, and ethical AI integration. Awards include the 2019 UTS Medal for Research Impact, ASME DED Leonardo da Vinci Award (USA), and multiple engineering excellence recognitions. His research has generated over $22M in external funding, including 13 ARC grants and industry partnerships.

• Composite Materials
• Structural Engineering
• Machine Learning Applications
• +۳ مورد دیگر

Dr. Thuc Vo is an Associate Professor in Civil Engineering at La Trobe University, Australia. His expertise lies in structural engineering, composite materials, and machine learning applications. He previously held roles at Northumbria University (UK) and Airbus’ Advanced Composite Training and Development Centre. His research focuses on shear deformation theories for composite structures and machine learning for structural engineering. He has authored over 120 publications in prestigious journals and conferences. Education & Experience: Associate Professor, La Trobe University (2019–present) Senior Lecturer & Program Leader in Civil Engineering, Northumbria University (2013–2019) Lecturer at Airbus’ Advanced Composite Training and Development Centre/Wrexham Glyndwr University (2011–2013) Research Associate, University of Liverpool (2010–2011) Research Interests: Composite material analysis (FGMs, nanoporous materials) Machine learning for structural prediction Vibration and buckling analysis Advanced beam and plate theories Collaboration & Supervision: Offers supervision for masters/PhD students and collaborates on industry projects. His work bridges theoretical mechanics with data-driven approaches, addressing challenges in smart materials and structural optimization.

Charles Hokeمشاهده پروفایل

مدرس ارشد

• Aerodynamics
• Computational Fluid Dynamics
• Flapping Foil Power Generation
• +۳ مورد دیگر

Dr. Charles Hoke serves as a Senior Lecturer in the School of Engineering and Technology at UNSW Canberra, specializing in computational aerodynamics and energy harvesting systems. His academic foundation includes a Bachelor's in Engineering Mechanics from UC San Diego (2000) and a Master's in Aeronautics and Astronautics from Stanford University (2001), with ongoing PhD studies at UNSW Canberra. His educational background comprises: Bachelor of Science in Engineering Mechanics, University of California, San Diego (2000) Master of Science in Aeronautics and Astronautics, Stanford University (2001) PhD candidate in Engineering, University of New South Wales, Canberra (present) Dr. Hoke's research centers on unsteady fluid-structure interactions, with primary focus areas: Computational investigation of flapping foil power generation systems Active flexibility mechanisms and near-wall flow effects Hypersonic shock-structure interaction phenomena Energy harvesting applications from oscillating foils Analysis of his publication history (2004-2024) reveals a progressive research trajectory from missile aerodynamics (2004) to advanced computational studies of bio-inspired propulsion systems. Recent works (2023-2024) demonstrate significant innovations in active morphing techniques for power extraction efficiency and high-fidelity modeling of hypersonic fluid-thermal-structural interactions, reflecting his dual expertise in defense applications and renewable energy solutions. His professional experience includes eight years as a US Air Force officer (2000-2008), serving as Aeronautical Engineer at the Air Force Research Laboratory and Assistant Professor at the Air Force Academy where he directed courses in aerodynamics and computational fluid dynamics, followed by four years as Lead Aerodynamicist at Raytheon Missile Systems (2008-2012).

Matt Garrattمشاهده پروفایل

استاد

• Robotics
• Swarm Robotics
• Unmanned Aerial Vehicles
• +۵ مورد دیگر

Professor Matt Garratt is a faculty member at the University of New South Wales (UNSW Canberra), School of Engineering and IT, serving as AI theme lead for the Defence Trailblazer Universities initiative with over $200 million in funding. His primary research focuses on sensing, guidance, and control for autonomous systems within robotics and unmanned aerial vehicles. Garratt's research spans robotics, swarm intelligence, and autonomous systems with emphasis on bio-inspired navigation techniques and adaptive flight control. His work addresses critical challenges including terrain following using vision systems, landing UAVs on moving platforms, and developing self-organizing swarms. He integrates artificial intelligence, computer vision, and machine learning to advance unmanned systems capabilities in complex environments. Analysis of his recent publications reveals strong trends in bio-inspired UAV navigation (particularly honeybee behavior modeling) and swarm robotics applications. His work increasingly incorporates deep learning for perception tasks while addressing real-world challenges like gas plume detection and adversarial robustness in 3D vision systems. The research demonstrates consistent progression toward practical implementation of autonomous systems in dynamic environments. Professor Garratt has secured over $7.7 million in external research funding as Chief Investigator on 33 grants. He actively mentors graduate students with scholarships available for Masters and PhD research in robotics and AI, focusing on: UAV path planning and adaptive control systems Swarm robotics collective motion optimization Bio-inspired autonomous navigation techniques Computer vision for robotic perception He co-founded the UNSW Canberra AIR (AI and Robotics) Group (AIR Lab), which drives research in trusted autonomy, swarm intelligence, and AI integration for defense applications. The lab develops practical solutions for autonomous systems operating in complex, real-world environments while maintaining ethical AI frameworks.

• Computational Intelligence
• Cloud Computing
• Big Data Applications
• +۶ مورد دیگر

Jun Shen is a Professor at the School of Computing and Information Technology, University of Wollongong. He specializes in computational intelligence, cloud computing, and big data applications, with a focus on AI-driven solutions for real-world challenges in transport systems, healthcare, education, and environmental management. He has secured over 40 research grants totaling AU$4.5 million and supervised 26 completed PhD projects. His work spans interdisciplinary areas including bioinformatics, smart manufacturing, and digital health. Research interests include bio-inspired algorithmic optimization, AI in arts/media, and edge computing for IoT systems. He has pioneered research centers in applied computing since 2014 and holds editorial roles in top journals like IEEE Transactions. As an IEEE Distinguished Lecturer, he actively promotes AI ethics and interdisciplinary collaboration. Recent publications emphasize adversarial machine learning defenses, UAV systems, and multimodal data fusion. His supervision includes projects in intelligent transport systems, cloud computing, and e-learning. Grants include projects on resilient energy systems and UAV geolocation verification. Leadership roles include leading over 20 researchers and chairing conferences. He advocates for digital transformation in public services and has conducted fieldwork at MIT, UCI, and Georgia Tech.

• Visual Physiology
• Neurobotics
• Insect Visual Systems
• +۴ مورد دیگر

Associate Professor Steven Wiederman holds the position of Associate Dean Research in the Faculty of Health and Medical Sciences at the University of Adelaide. He leads the Visual Physiology & Neurobotics Laboratory within the School of Biomedicine. His research focuses on understanding visual processing in insects, particularly dragonflies, and translating these insights into applications for autonomous robotics and neuro-inspired systems. Key areas include target detection, optic flow processing, and selective attention mechanisms in biological systems. His interdisciplinary work combines electrophysiological techniques, computational modeling, and robotics engineering. Current projects explore how dragonfly neurons enable precise tracking of moving targets amidst clutter, with applications in developing advanced vision systems for drones and robots. He has secured significant funding through ARC fellowships and industry partnerships, including projects on neuro-inspired deep learning for defense applications. Academic achievements include an ARC DECRA Fellowship (2011–2015) and an ARC Future Fellowship (2016–2020). He is a member of the ARC College of Experts and actively supervises PhD and Master’s students in neuroscience, robotics, and computational biology. His lab collaborates with engineers and computer scientists to bridge biological insights with technological innovation. Publications highlight breakthroughs in understanding neuronal mechanisms underlying predictive vision, selective attention, and adaptive processing in dragonfly visual systems. Media coverage includes features in Wall Street Journal , New York Times , and Science Daily , emphasizing the potential of insect-inspired solutions for future technologies.

• Plant Phenotyping
• Precision Agriculture
• Machine Vision
• +۶ مورد دیگر

Dr. Huajian Liu is a Grant-Funded Researcher (B) at the University of Adelaide's School of Agriculture, Food and Wine, within the Faculty of Sciences, Engineering and Technology. He is affiliated with The Plant Accelerator, the Adelaide node of the Australian Plant Phenomics Facility. His research focuses on machine vision and machine learning for plant phenotyping and precision agriculture, particularly using hyperspectral imaging for plant nutrient estimation, disease detection, stress tolerance analysis, and pest monitoring. Dr. Liu holds a PhD in machine vision for invertebrate detection from the University of South Australia (2018) and has been a post-doctoral researcher at The Plant Accelerator since then. His expertise spans hyperspectral imaging, bio-inspired machine vision systems, 3D model reconstruction, and optical sensing system design. He is eligible to supervise Masters and PhD students in plant phenotyping and precision agriculture. Key research areas include crop stress detection (drought, salt, nutrient deficiencies), invertebrate pest identification, and automation in agricultural monitoring. Affiliations: The Plant Accelerator, School of Agriculture, Food and Wine Research Themes: Plant phenotyping, precision agriculture, machine learning applications Grants: Ongoing grant-funded research in plant phenomics and hyperspectral technologies Publications highlight innovations in hyperspectral imaging for crop yield prediction, disease diagnostics, and nitrogen content analysis. His work bridges computational methods with agricultural challenges, emphasizing sustainable farming solutions.

Joe Gattasمشاهده پروفایل

دانشیار

• origami-inspired engineering
• computational building design
• advanced manufacturing
• +۱۴ مورد دیگر

Associate Professor Joe Gattas is affiliated with the University of Queensland's School of Civil Engineering , where he leads the Folded Structures research group. His work bridges origami-inspired engineering , computational building design , and advanced manufacturing , with a focus on lightweight/modular structures and timber engineering . Education: BEng (2009) and PhD (2013) from the University of Queensland and University of Oxford, respectively. Research interests emphasize digital fabrication , hybrid materials , and structural innovation . His recent publications highlight trends in timber-CFRP composites , self-shaping structures , and value chain optimization for sustainable timber use. Scientific awards include the prestigious John Monash Scholarship . He actively supervises PhD and Master’s students in projects related to timber composites , structural optimization , and low-cost housing . Joe contributes to ARC Research Hub initiatives , co-leading Manufacturing Innovation and Value Chain Innovation nodes, and develops open-source tools like TimberTracker to visualize timber supply-demand dynamics.

• Biomedical Engineering
• Nanotechnology
• Microelectronics
• +۵ مورد دیگر

Professor Omid Kavehei is a Professor of Intelligent Microsystems in the Faculty of Engineering at the University of Sydney, serving as Deputy Head of the School of Biomedical Engineering. Previously, he held roles as a Research Fellow at the University of Melbourne and Lecturer at RMIT University. His research focuses on biomedical microsystems, nanotechnology, and brain-inspired hardware for healthcare applications, particularly epilepsy monitoring and seizure prediction. Education: PhD (specific institution not explicitly stated) His work bridges nanoelectronics and healthcare, aiming to develop low-power, brain-inspired devices for sensory perception and medical diagnostics. Key interests include neuromorphic engineering, wearable sensors, and AI-driven medical systems. Awards include the Ramaciotti Biomedical Research Award (2021), Microsoft AI for Accessibility Grant (2019), and multiple teaching/research excellence awards from the University of Sydney. His recent work explores neuromorphic cytometry for cell analysis, edge AI for ECG/EEG diagnostics, and closed-loop neurostimulation systems. Collaborations include the Sydney Nano Institute, Brain and Mind Centre, and industry partners like Microsoft. Current research students are advancing topics like bio-inspired algorithms for seizure detection, hardware-friendly machine learning models, and flexible sensor systems for aquatic environments. Grants include funding for neurophysiology platforms, quantum sensors, and semiconductor design. Labs/teams: Involved in the Centre for Drug Discovery Innovation and collaborations across engineering, neuroscience, and clinical domains.

• Artificial Intelligence
• Machine Learning
• Spatial Reasoning
• +۳ مورد دیگر

Dr. Paulo Santos is a Senior Lecturer at Flinders University's College of Science and Engineering, specializing in Artificial Intelligence with a focus on explainable AI systems. He holds a PhD from Imperial College London (2003) and has over 20 years of research experience in spatial reasoning, machine learning, and robotics. His work bridges knowledge representation with deep learning to enhance transparency in AI decision-making. Dr. Santos has led research groups in Brazil, collaborated internationally, and secured funding from organizations like the British Council and EU. His expertise spans robotics, computer vision, and cognitive science. Notable achievements include the British Computer Science Machine Intelligence Prize (2004) and the Santander Prize for Science and Innovation (2006). Research interests include reinforcement learning for autonomous underwater vehicles (AUVs), scene graph generation in computer vision, and spatial reasoning for multi-robot systems. Recent work emphasizes sim-to-real transfer learning and fault recovery in underwater robotics.