جست‌وجوی استاد و پژوهشگر

Mamoun Alazabمشاهده پروفایل

استاد

• Cyber Security
• Data Analytics
• Digital Forensics
• +۷ مورد دیگر

Professor Mamoun Alazab is a full Professor and Inaugural Director of the NT Academic Centre for Cyber Security and Innovation (ACCI) at Charles Darwin University. His expertise spans cyber security, data analytics, and digital forensics with a focus on AI-driven solutions for cybercrime detection and privacy preservation. Research Interests: Malware authorship attribution, adversarial AI, access control systems in CPS/IoT, cyber criminology, and privacy-preserving machine learning. He has secured ~A$16.7M in research funding and published over 300 top-tier papers (90% in top 10% journals), 11 books, and holds 3 patents. Editorial Roles: IEEE Transactions on Computational Social Systems, ACM Digital Threats: Research and Practice Professional Activities: Founding Chair of IEEE NT Subsection, convened 200+ conferences Awards: Clarivate Highly Cited Researcher (2022), Top 2% Global Scientists (2020–2022), and multiple IEEE leadership awards. Labs/Teams: Leads ACCI, collaborates on projects like Cyber Territory Skills Hub and CVE: Countering Violent Extremism Research.

Jamal El-Denمشاهده پروفایل

مدرس ارشد

• Knowledge Management
• Positive Psychology
• Group Support Systems
• +۶ مورد دیگر

Dr. Jamal El-Den is a Senior Lecturer in Information Systems at Charles Darwin University's Faculty of Science and Technology. He holds a PhD in Information Systems from the University of Technology Sydney. His research focuses on Knowledge Management, Positive Psychology, Group Support Systems, Organizational Productivity, and the transformative role of Social Media in Education. He has successfully graduated three PhD students and currently supervises two more. His work bridges theoretical frameworks with practical applications in areas like AI-driven education, sustainable digital learning, and healthcare informatics. Dr. El-Den is actively engaged in interdisciplinary research, exploring topics such as energy-efficient 6G networks and smart urban systems. His publications span over 20 years, demonstrating a commitment to advancing Information Systems across diverse domains. Education: PhD in Information Systems (UTS Sydney). Key research interests include AI-enabled reskilling, sustainable digital learning, and the intersection of technology with organizational well-being. He has contributed to frameworks for social media adoption in educational and enterprise contexts, emphasizing cooperative learning and knowledge sharing. Notable research contributions include studies on diabetic retinopathy diagnosis via deep learning, stochastic models for technology adoption, and security compliance through positive psychology interventions. His work often addresses real-world challenges in education, healthcare, and urban planning, reflecting a dedication to socially impactful research.

Paul Duuringمشاهده پروفایل

پژوهشگر ارشد

• Economic Geology
• Mineral Exploration
• Ore Deposits
• +۴ مورد دیگر

Paul Duuring is an Adjunct Senior Research Fellow at the School of Earth and Oceans, The University of Western Australia (UWA), and a Senior Geologist at the Geological Survey of Western Australia. He holds a PhD in Economic Geology from UWA (2002) and has held postdoctoral positions at Monash University, University of British Columbia, Pukyong National University, and UWA. His research focuses on mineral systems, including orogenic and intrusion-related gold systems, komatiite-hosted nickel, porphyry Cu-Au, epithermal Au-Ag, hypogene/supergene Fe ore, and volcanic-hosted massive sulfide deposits. He has authored over 18 first-author articles in international journals. Recent publications emphasize geochemical data analysis, machine learning applications in geology, and rare earth element exploration. He has contributed to grant projects on predictive mineral exploration targeting in Western Australia, including studies on banded iron formations and laterite systems. Paul serves as an Associate Editor for Ore Geology Reviews and holds volunteer roles in the Geological Society of Australia (WA Chapter). His work aligns with UN Sustainable Development Goals related to sustainable industry and resource management. Key grants include geotechnical assessment using data mining (Fortescue Metals Group, 2014–2016) and predictive exploration for BIF-hosted Fe deposits (WA Department of Mines, 2012–2014). His research integrates computational methods with field-based mineralogy, reflecting interdisciplinary expertise in geology and data science.

Leigh Schmidtkeمشاهده پروفایل

استاد

• Wine Chemistry
• Chemometrics
• Metabolomics
• +۶ مورد دیگر

Leigh Schmidtke is a Professor of Oenology at Charles Sturt University (Gulbali Institute), leading research in wine chemistry, chemometrics, and agricultural innovation. He previously directed the National Wine and Grape Industry Centre and the Graham Centre for Agricultural Innovation. His work focuses on grapevine physiology, metabolomics, and rapid analytical methods for assessing abiotic/biotic impacts on vine performance. Research spans wine microbiology, environmental stewardship, and biosecurity, with a strong emphasis on data-driven approaches like IR and mass spectrometry. Education & Affiliations: Affiliated with Agricultural, Environmental, and Veterinary Sciences school. Key collaborations include Wine Australia and industry partners in viticulture and food systems. Research Interests: Grape/wine composition, flavor-matching, rapid analysis techniques (mass spectrometry), chemometric data modeling, and environmental factors influencing vineyards. Specializes in metabolomics for disease detection (e.g., Botrytis cinerea) and terroir studies in premium wines like Barossa Shiraz. Publications: Recent work includes soil carbon estimation via satellite data, copper's role in wine spoilage, and volatile analysis for fungal infection detection. His research bridges analytical chemistry with agricultural sustainability and food authenticity verification (e.g., beef production systems). Awards & Grants: While specific awards aren't listed, his leadership roles and high-impact research indicate significant industry and academic recognition. Active in securing grants for projects like terroir analysis and biosecurity solutions. Labs & Teams: Leads interdisciplinary teams at the Gulbali Institute, focusing on wine science, sustainable agriculture, and biosecurity. Collaborates with industry stakeholders to translate research into practical solutions for viticulture challenges.

• Autonomous Systems
• Robotics
• Computer Vision
• +۵ مورد دیگر

Asanka Perera is a Lecturer in Mechatronic Engineering at the University of Southern Queensland. His research focuses on robotics, autonomous systems, computer vision, and adversarial learning. He is affiliated with the Centre for Agricultural Engineering and the Centre for Future Materials, and holds an ORCID ID: https://orcid.org/0000-0003-4021-3943. Education: BScEEEng, University of Peradeniya (2008) MScience Industrial Automation, Moratuwa University (2015) PhD, University of South Australia (2020) Professional Memberships: Engineers Australia, Australian Computer Society (ACS), IEEE, Australian Association of Uncrewed Systems (AAUS) His research interests span autonomous vehicles, field robotics, intelligent robotics, and computer vision applications. He has supervised doctoral and master's students on topics like swarm robot localization, adversarial machine learning, and biomedical robotics. His work includes developing algorithms for robust perception in autonomous systems and non-invasive medical monitoring using drones and thermal imaging. Key contributions include reviews on UAV-UGV collaboration, adversarial robustness in LiDAR systems, and biomimetic navigation techniques inspired by celestial orientation. His research bridges robotics, computer vision, and healthcare technologies, emphasizing real-world applications in autonomous systems and medical diagnostics.

Hao Xiongمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Health Informatics
• Medical Imaging
• +۳ مورد دیگر

Hao Xiong is a Research Fellow at the Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University. He specializes in applying machine learning and artificial intelligence to healthcare challenges, including medical imaging, signal processing, and clinical diagnostics. His work bridges computer science and health informatics, focusing on applications like cough classification, medical prognosis modeling, and automated analysis of clinical interactions. Key research areas include neural networks, acoustic signal analysis, and deep learning for healthcare applications. His systematic reviews and models address issues such as wet/dry cough differentiation, esophageal fistula prognosis, and delirium-dementia correlations. He has contributed to advancements in brain extraction algorithms, logo detection frameworks, and multimodal clinical data analysis. Dr. Xiong has been recognized with prestigious awards, including the IBM Rational Prize in Software Engineering (2010) and Best Student Paper Award (2016). His work emphasizes interdisciplinary collaboration, evidenced by projects involving robotics, epidemiology, and wearable technology for health monitoring. Awards: IBM Rational Prize (2010), Best Student Paper (2016), First Place in Algorithms (2012), Mentoring in Visual Computing (2017/2018) Grants/Projects: Visual Computing and Big Data Analytics (2017-2018), multiple collaborations in healthcare AI His research portfolio includes over 40 peer-reviewed publications, showcasing his impact in health informatics, medical imaging, and machine learning applications.

Lianhua Chiمشاهده پروفایل

مدرس

• Big Data Analytics
• Artificial Intelligence in Healthcare
• Machine Learning
• +۷ مورد دیگر

Lianhua Chi is a Lecturer in the Department of Computer Science and Information Technology at La Trobe University, Melbourne, Australia, since February 2018. He holds a dual PhD in Machine Learning and Data Mining from the University of Technology Sydney (Australia) and Huazhong University of Science and Technology (China). Before joining academia, he worked as a Postdoctoral Researcher at IBM Research Australia on Watson Education and Health, and as a Data Specialist at the University of New South Wales (UNSW). His research focuses on big data analytics, particularly in healthcare applications, AI-driven Autism Screening, and hashing techniques for real-time data processing. Chi has received notable awards including the 'Young Global Changer' title from G20/T20 Germany, 'Top 200 Young Researchers Globally' by the Heidelberg Laureate Forum, and the IBM External Honors award. Education: PhD in Machine Learning and Data Mining (2015), University of Technology Sydney & Huazhong University of Science and Technology Previous roles: Postdoc at IBM Research Australia, Visiting Researcher at UTS Research Interests: Chi’s work emphasizes adaptive hashing algorithms, graph stream classification, geolocation prediction in social media, and time series analysis. He applies these techniques to healthcare challenges such as AI-based Autism Screening and medical imaging diagnostics. His methodologies prioritize scalability and real-time adaptability. Awards & Grants: Best Paper Award (PAKDD13) Romberg Grant (Heidelberg Laureate Forum, 2016) Innovation Connection Grant (NostraData, 2022–2023) Advising & Collaborations: Chi has collaborated with Harvard Medical School’s Gehlenborg Lab and led projects on healthcare AI and cybersecurity. His work integrates advanced hashing techniques with clinical data to improve diagnostic accuracy and patient care efficiency. Labs/Teams: Active in interdisciplinary teams focusing on AI ethics, healthcare analytics, and big data security at La Trobe University.

Luis Mejias Alvarezمشاهده پروفایل

دانشیار

• Unmanned Aerial Systems (UAS)
• Computer Vision
• Collision Avoidance
• +۵ مورد دیگر

Luis Mejias Alvarez is an Associate Professor and Researcher in the School of Electrical Engineering & Robotics at Queensland University of Technology (QUT). He specializes in Unmanned Aerial Systems (UAS), focusing on vision-based guidance, collision avoidance, and autonomous navigation technologies. His work integrates computer vision, sensor fusion, and control systems to advance UAV applications in aerospace and robotics. Education: Electronic Engineer (UNEXPO, Venezuela, 1999) MSc in Networks and Telecommunication Systems (Universidad Politécnica de Madrid, 2001) PhD in Robotics and Automation (Universidad Politécnica de Madrid) Research Interests: His research spans Unmanned Aerial Systems (UAS), including autonomous helicopters, vision-based navigation, collision avoidance, and forced landing technologies. He develops algorithms for computer vision, sensor fusion, and control systems, with applications in aerospace engineering and artificial intelligence. His work aims to enhance UAV safety and autonomy in complex environments. Awards & Fellowships: 2017 Endeavour Executive Fellowship Visiting Professorships at Université de Bretagne Occidentale (2017) and UTIS (2017) Editor of Springer Tracts in Advanced Robotics (2016) Keynote Speaker at CIIMA 2014 Program Chair for UAS Conferences (2013) DECRA Fellowship (2012–2015) IRSES Grant (2009) Advising & Grants: Supervised PhD/Masters students in areas like vision-based collision avoidance and UAV navigation. Key grants include ARC DECRA and international IRSES collaboration with European institutions. Labs & Collaborations: Active in QUT’s Centre for Robotics and the Australian Research Centre for Aerospace Automation. Collaborates globally on projects like drone ship landing under adverse conditions and beyond-line-of-sight navigation.

Somayeh Hussainiمشاهده پروفایل

پژوهشگر ارشد

• Robotics
• Computer Vision
• Neuromorphic Computing
• +۴ مورد دیگر

Dr. Somayeh Hussaini is a Research Fellow at the QUT Centre for Robotics, Queensland University of Technology (QUT). She holds a Bachelor of Engineering (Honours) in Mechatronics from QUT (First Class Honours, 2020). Her research focuses on robotics, computer vision, and neuromorphic computing, particularly in developing biologically-inspired spiking neural networks for scalable visual place recognition. She has published at leading conferences like ICRA and IEEE Robotics and Automation Letters (RAL), and her Honours work earned the IEEE Best Thesis Award (2020). Her current projects involve adaptive robot localization, neuromorphic computing applications, and spike-based visual systems using Intel’s Loihi chip. Key contributions include sequence-matching algorithms for place recognition and hyperdimensional descriptors for scalable navigation systems. Her work bridges biological neural principles with robotic autonomy. Education : BEng (Honours) Mechatronics, QUT (2020) Awards : IEEE Best Final Year Thesis Award (2020) Advising : Supervised by Dr. Tobias Fischer and Prof. Michael Milford during her PhD. Lab Affiliation : QUT Centre for Robotics research group.

Daniel Quevedoمشاهده پروفایل

استاد

• Networked Systems
• Cyberphysical systems
• Cyberphysical Security
• +۳ مورد دیگر

Prof. Daniel Quevedo is a Professor in Cyberphysical Systems at the School of Electrical Engineering and Robotics, Queensland University of Technology (QUT). He previously led the Chair in Automatic Control at Paderborn University, Germany. He holds a PhD from the University of Newcastle (Australia) and degrees from Universidad Técnica Federico Santa María (Chile). His research focuses on networked cyberphysical systems, cybersecurity, and model predictive control, with over 240 publications and three patents. He has attracted over $2M in research funding and is a Fellow of the IEEE. His work emphasizes cross-disciplinary collaboration in fields like power electronics, telecommunications, and behavioral economics. Educations: PhD in Automatic Control (2005), University of Newcastle, Australia M.Sc. and B.Eng. (2000), Universidad Técnica Federico Santa María, Chile Research Interests: Prof. Quevedo’s work bridges theoretical systems control with practical applications. Key areas include networked cyberphysical systems, cybersecurity (e.g., deception attacks, privacy preservation), and energy-efficient control strategies. His contributions span event-triggered control, encrypted cooperative systems, and power converter optimization. He collaborates globally with institutions like ABB, TU Berlin, and Indian Institute of Technology Bombay. Grants & Awards: Notable grants include DFG-funded projects on network-informed control and ARC grants on predictive control. His 2018 IEEE Axelby Award highlights his impact on systems control theory. He has also held visiting professorships and editorial roles for journals like IEEE Transactions on Automatic Control. Teaching & Supervision: At Paderborn University, he modernized control systems curricula, integrating blended learning and industry-relevant projects. He has supervised over 10 PhD/MSc theses and mentored postdoctoral researchers in areas like cyber-physical security and distributed control. Labs & Teams: He is affiliated with QUT’s Centre for Robotics, focusing on interdisciplinary robotics and cyberphysical systems research.

Anthony Vanderkopمشاهده پروفایل

پژوهشگر

• Robotics
• Mobile Robotics
• Robot Control
• +۳ مورد دیگر

Anthony Vanderkop is a Researcher and PhD candidate affiliated with the Queensland University of Technology (QUT) Centre for Robotics (QCR) and the CSIRO's Robotics and Autonomous Systems Group (RASG). His research focuses on advancing the capabilities of multi-legged robots in navigating natural outdoor environments, particularly challenging terrains such as sand and soil. His work bridges robotics control, perception, and the dynamics of robot-terrain interactions. Anthony’s research interests include robot control systems, mobile robotics, and the development of models to enhance robotic performance in deformable environments. His publications explore topics ranging from physics-based simulators to self-supervised learning techniques for video analysis. He is supervised through a joint PhD program between QUT and CSIRO, leveraging interdisciplinary collaboration to address real-world robotic challenges. While no awards or grants are explicitly noted, his research contributes to advancing autonomous systems in unstructured environments.

• Marine Science
• Coral Reef Ecology
• Hydrodynamics
• +۵ مورد دیگر

Peter V. Ridd is a Professor at James Cook University, specializing in marine science with a focus on coral reef ecosystems, hydrodynamics, and environmental policy. His research addresses challenges such as marine plastic pollution, sediment dynamics, and the resilience of coral reefs to climate change. He has contributed to significant projects like the Port of Mackay marine water quality monitoring and the analysis of hypersaline coastal systems. Ridd critiques environmental policy frameworks, emphasizing rigorous scientific validation. His work spans field studies in tropical regions and collaborations with international teams, bridging ecology, geophysics, and computer science. Key research interests include coral reef resilience, sediment transport mechanisms, and the integration of policy with scientific data. His publications highlight innovative methodologies, such as using ground-penetrating radar for archaeological studies and machine learning for weed classification. Ridd’s interdisciplinary approach addresses both natural processes (e.g., tidal dynamics) and anthropogenic impacts (e.g., dredging effects). While no formal awards are listed, his extensive contributions to marine environmental science are evident through his prolific publications and applied research projects. He collaborates with institutions like TropWATER and engages in policy discussions on environmental management strategies.

• Geochemistry
• Volcanology
• Geophysics
• +۳ مورد دیگر

Associate Professor Rebecca Carey is affiliated with the University of Tasmania's School of Natural Sciences, specifically in the Earth Sciences department. Her academic rank is Associate Professor, focusing on volcanology, geochemistry, and geophysics. She is involved in supervising numerous doctoral and master's students, including James John Rochfort Brady, Hannah Clare Moore, and Joshua James Phillips. Her research interests span submarine volcanic processes, magma-water interactions, and the dynamics of deep-sea eruptions, with contributions to understanding hazards and mineral exploration. Dr. Carey has been awarded the Australian Research Council Future Fellowship and DECRA Fellowship. Education: Not explicitly stated in the text. Grants: Over 30 funded projects, including studies on submarine eruption dynamics, plume-ridge interactions, and mineral exploration strategies. Labs/Teams: Collaborations with institutions like CSIRO, ANSTO, and international teams, contributing to marine geology and volcanic hazard research. Her work emphasizes the interplay between volcanic processes and marine environments, with recent projects addressing the 2022 Hunga eruption and the 2012 Havre submarine eruption. Key findings include insights into submarine eruption fragmentation, tsunami generation, and the role of plumes in tectonic evolution. Awards: Australian Research Council Future Fellowship Australian Research Council DECRA Fellowship Teaching/Supervision: Current and past supervision spans topics like tephra geochemistry, submarine caldera formation, and mineral exploration in ancient volcanic terrains.

• Microelectromechanical Systems (MEMS)
• Porous Silicon
• Infrared Systems
• +۷ مورد دیگر

Adrian Keating is a Professor in the School of Mechanical Engineering at The University of Western Australia (UWA), specializing in Microelectromechanical Systems (MEMS), porous silicon, and infrared sensors. He holds roles such as Mechatronics Course Advisor and Laser Safety Officer. His career spans over 20 years, including industrial experience at Calient Networks as Fiber Optics Technology Manager, where he developed high-yield MEMS-based products. Dr. Keating earned a Bachelor of Engineering (Honors) from The University of Melbourne and a Ph.D. from Telecom Research Laboratories, focusing on photonic communication networks. His research emphasizes optical sensors, MEMS, and IoT technologies. Notable contributions include patents for fiber-collimator designs and work on MEMS-based infrared sensors. He actively supervises students and leads projects in areas like soil and grain parameter assessment via microspectrometers. Key research interests include porous silicon materials, thermal sensing, and MEMS fabrication. He has secured grants totaling millions, such as the 2004 ARC Discovery Project on MEMS/NEMS technologies. Teaching responsibilities include units like Mechatronic Systems and Engineering Dynamics. Current projects explore infrared thermal imagers, microfluidics, and IoT-enabled beehive monitoring systems. His work aligns with UN Sustainable Development Goals through innovations in agriculture and environmental monitoring. Dr. Keating collaborates internationally, with recent projects in Japan (NTT) and the U.S. (UC Santa Barbara). His lab focuses on developing low-cost, high-performance sensors and imaging systems. Patents and peer-reviewed publications reflect his expertise in optical systems, micromachining, and material science. Future research aims to advance infrared imaging and MEMS-based sensor technologies for industrial and environmental applications.

• Artificial Intelligence
• Machine Learning
• Knowledge Graphs
• +۲ مورد دیگر

Sirui Li is a research associate at the ARC Training Centre for Transforming Maintenance through Data Science, University of Western Australia, and serves as a part-time lecturer. She holds a PhD in Artificial Intelligence from Murdoch University and Master's/Bachelor's degrees in Computer Science from the Australian National University. Her educational background: PhD in Artificial Intelligence, Murdoch University Master of Computing, Australian National University Bachelor of Advanced Computing, Australian National University Dr. Li's research centers on Artificial Intelligence and Machine Learning, specializing in deep learning for knowledge graphs with applications in industrial decision-making systems. Her work bridges natural language processing, knowledge representation, and data science, contributing to UN Sustainable Development Goals through AI-driven innovation in maintenance and infrastructure. Recent publications (2023-2025) reveal a cohesive research trajectory leveraging large language models and temporal knowledge graphs for document annotation, question answering, and failure mode analysis. These studies demonstrate cross-disciplinary integration of machine learning with real-world industrial maintenance challenges. Her recognition includes: Best Demo Award (2024) Dr. Li actively contributes to the ARC Training Centre for Transforming Maintenance through Data Science, a national research hub focused on revolutionizing industrial maintenance via data science. Her collaborative work emphasizes translating AI research into practical industry solutions, particularly in predictive maintenance and knowledge-driven decision systems.