جست‌وجوی استاد و پژوهشگر

Rolf Schwitterمشاهده پروفایل

مدرس ارشد

• Natural Language Processing
• Formal Language Processing
• Controlled Natural Languages
• +۴ مورد دیگر

Rolf Schwitter is a Senior Lecturer at the School of Computing, Macquarie University. His research focuses on natural and formal language processing, including controlled natural languages, answer extraction, knowledge representation, probabilistic logic programming, and Semantic Web technologies. He holds an h-index of 13 with over 944 citations. His work emphasizes bridging human-readable and machine-processable systems, particularly in legal and technical domains. Key research contributions include developing frameworks like PENG ASP for declarative programming in natural language, smart contract systems, and hybrid explainability tools like HESIP. He leads projects such as Policy Automation: Reconstructing Policy Documents for Objective Decision Making (2018–present) and has collaborated on initiatives like TwitterNews+ for real-time event detection. Research Themes: Controlled Natural Languages, Smart Contracts, Explainable AI, Legal Informatics Notable Projects: User-guided legal document processing, error-free smart contracts, hybrid prediction explanations Received the 2023 Faculty of Science and Engineering Award for Inter-School Collaboration. Active in academic publishing with over 117 research outputs spanning conferences, journals, and book chapters.

• Machine Learning
• Autonomous Systems
• Cyber Security
• +۱ مورد دیگر

Dr. Hong Gunn Chew is a Lecturer at the University of Adelaide, affiliated with the School of Electrical and Mechanical Engineering within the Faculty of Sciences, Engineering and Technology. His research focuses on Machine Learning, Autonomous Systems, Cyber Security, and Energy Management. He holds roles as the electronics practical coordinator and final year projects coordinator in the School of Electrical and Electronic Engineering. Dr. Chew’s academic contributions span teaching and research supervision across multiple disciplines, including Computer Architecture, Digital Electronics, and Project Management. He has coordinated undergraduate and postgraduate research projects, fostering practical skills in students through hands-on learning environments. His research publications reflect expertise in adversarial machine learning, network security, and energy systems optimization. Notable work includes developing explainability models for AI systems and frameworks for detecting cyber threats in networked devices. He has secured grants related to defense applications, such as eavesdropping detection and swarm intelligence coordination in urban environments. Dr. Chew’s teaching portfolio includes courses on circuit design, control systems, and distributed generation technology. His interdisciplinary approach bridges theoretical concepts with real-world applications, particularly in addressing challenges in autonomous systems and sustainable energy solutions.

Yue Xuمشاهده پروفایل

دانشیار

• Data Analytics
• Machine Learning
• Knowledge Discovery
• +۶ مورد دیگر

Associate Professor Yue Xu is affiliated with the School of Computer Science at Queensland University of Technology (QUT). She obtained her PhD in 2000 from the University of New England and has held academic positions at Tasmania University (2000–2002) and QUT since 2002, where she was promoted to Associate Professor in 2011. Her research focuses on data analytics, machine learning, and knowledge discovery. Key areas include pattern mining in large datasets, anomaly detection, vulnerability analysis, topic modeling for text summarization, and social media analytics for business and security improvements. She has developed methods to enhance recommendation systems through multi-dimensional user profiling, context-aware recommendations, and semantic-based approaches. Expertise: Text mining, social engineering attack detection, distributed algorithms for big data Research Themes: Cybersecurity policy frameworks, healthcare prediction models, and interpretable machine learning techniques Prof. Xu has received prestigious awards including the Best Paper Award at WEBIST 2014 and iiWAS2012. She leads research projects such as Web Services Reputation Management (funded by Australian Competitive Grant LP0776400, 2007). Her teaching responsibilities include courses like CAB430 and IFN645, and she coordinates the Master of Data Analytics program. Her current PhD supervisions address challenges in industrial control systems vulnerability detection, hospital readmission prediction, senior frailty assessment, and semantic topic modeling. Completed supervisions include impactful works on healthcare e-coaching systems, spammer detection on Twitter, and reputation models for recommender systems.

Dan Liمشاهده پروفایل

مدرس

• Bayesian Inference
• Financial Econometrics
• Climate Risk Modelling
• +۳ مورد دیگر

Dr. Dan Li is a Lecturer in Computational Statistics at the School of Mathematical Sciences, Queensland University of Technology (QUT). She serves as ECR Co-leader for the Business, Engineering & Social Systems Theme. Her research focuses on Bayesian inference, financial econometrics, and climate risk modeling, emphasizing statistical methodologies for climate change and financial risk mitigation. Dr. Li holds a PhD from QUT and has contributed to projects funded by the Centre for Data Science. Her research integrates advanced statistical and econometric approaches to address challenges in sustainable finance, climate adaptation, and environmental systems. Key projects include sediment transport modeling in estuaries, climate change impact analysis, and risk assessment frameworks for coastal ecosystems. She collaborates with interdisciplinary teams to apply data-driven solutions to real-world problems such as levee erosion countermeasures and catchment-to-reef dynamics. Dr. Li’s publications span environmental science, hydrology, and climate modeling, with recent work focusing on sediment dynamics in the Great Barrier Reef catchments and San Francisco Bay systems. Her studies highlight innovative monitoring techniques and probabilistic modeling to improve environmental decision-making. She actively participates in research initiatives at QUT’s Centre for Data Science, contributing to advancements in computational methods for complex systems analysis.

• Self-Organizing AI
• Machine Learning
• Text Analytics
• +۳ مورد دیگر

Damminda Alahakoon is Professor of Business Analytics and AI at La Trobe University, where he founded and directs the Research Centre for Data Analytics and Cognition (CDAC). With dual appointments at Luleå University (Sweden) and University of Moratuwa (Sri Lanka), he bridges international AI research. His 15+ year academic career follows 10 years in industry, including roles in finance and IT across Australia, Sri Lanka, and the Netherlands. Research Impact: Developed the Growing Self-Organizing Map (GSOM) algorithm for adaptive AI systems applied in healthcare, utilities, and smart cities. Current projects include generative AI for healthcare chatbots and quantum optimization for energy systems. Industry Collaboration: Secured $6M+ in research funding for projects like AI-driven stroke rehabilitation monitoring and mining workforce analytics. Recent industry partnerships focus on operationalizing ethical AI frameworks in Australia-India tech corridors. Teaching: Leads the Master of Business Analytics program, specializing in predictive analytics curriculum development.

Tatiana Dancyمشاهده پروفایل

دانشیار

• Artificial Intelligence in Law
• Algorithmic Justice
• Blockchain Regulation
• +۲ مورد دیگر

Associate Professor Tatiana Dancy researches law-tech intersections including algorithmic justice, cryptoassets, and private law theory. She authored 'Artificial Justice' (OUP 2023) analyzing fairness beyond inequality metrics, and received the Modern Law Review Wedderburn Prize for her work on value transactions. Directs Digital Law programs and advises UK Law Commission on digital assets. Key Responsibilities: Director of Studies for Digital Law and Technological Innovation (MLM) Convenor: Law and Automation (JD), Cryptoassets (MLM), AI and Justice (MLM) Inner Temple Academic Fellow and Financial Markets Law Committee member Research Focus: Critical examination of algorithmic fairness paradigms, blockchain regulatory frameworks, and restitution theory in digital economies.

Joseph Liuمشاهده پروفایل

استاد

• Cyber Security
• Blockchain Technology
• Applied Cryptography
• +۵ مورد دیگر

Joseph Liu is a Full Professor at Monash University's Faculty of Information Technology, leading the Monash Cybersecurity Discipline Group and founding director of the Monash Blockchain Technology Centre. He holds a PhD from the Chinese University of Hong Kong (2004) and has pioneered research in blockchain security, linkable ring signatures (underpinning Monero cryptocurrency), and applied cryptography. His work spans cloud security, healthcare privacy, and lightweight cryptographic algorithms. He has received over 10,000 citations and 200+ publications in top venues like CRYPTO and ACM CCS. Awards include the 2018 ICT Researcher of the Year (ACS) and 2021 IEEE Technical Achievement Award. Education: PhD Information Engineering, Chinese University of Hong Kong (2004) MPhil Information Engineering, Chinese University of Hong Kong (2001) BEng Information Engineering, Chinese University of Hong Kong (1999) Research focuses on bridging cryptographic theory with real-world applications, emphasizing privacy-preserving technologies and post-quantum security. Recent projects include the Algorand Centre of Excellence for Sustainability Informatics and ethical frameworks for blockchain-based digital credentials. He has led 22+ research projects and contributed to ISO/IEC blockchain standards. Awards: ACS ICT Researcher of the Year 2018 IEEE Technical Achievement Award 2021 Best Paper Awards (2021–2022) Teaching includes courses like FIT2034 and FIT5043. He co-chairs the IEEE Blockchain Australia Chapter and has organized major conferences (e.g., ProvSec, Pairing). Current initiatives include privacy-preserving AI in materials discovery and scalable blockchain systems.

• Cybersecurity
• Smart Grids
• Cyber-Physical Systems
• +۳ مورد دیگر

Thusitha Dayaratne is a Research Fellow in the Department of Software Systems & Cybersecurity at Monash University. His work primarily focuses on cybersecurity challenges in smart grids, cyber-physical systems, and distributed identity frameworks. He specializes in addressing vulnerabilities such as false data injection attacks, resilient device scheduling, and enhancing situational awareness in energy systems. His research integrates applied machine learning and self-sovereign identity (SSI) solutions to improve security in IoT-enabled energy infrastructure, including smart inverters and virtual power plants. He has contributed to frameworks for firmware update management and tracking in VPP contexts, as well as cybersecurity measures for 6G networks and federated learning systems. Key areas of exploration include securing decentralized energy systems, mitigating adversarial attacks in demand response mechanisms, and ensuring privacy in IoT ecosystems. His work aligns with UN Sustainable Development Goals, particularly in advancing resilient infrastructure and sustainable energy solutions. Dayaratne has published extensively in top-tier conferences such as IEEE SmartGridComm and journals like Springer's Power Systems series. His articles consistently address cutting-edge threats in smart grid cybersecurity and propose innovative mitigation strategies.

• Fluvial geomorphology
• Hydrology
• Environmental management
• +۷ مورد دیگر

Dr. Scott Rayburg is a Senior Lecturer in the School of Engineering at Swinburne University of Technology, specializing in fluvial geomorphology and hydrology. His research focuses on catchment management, environmental flows, and sustainable infrastructure. He holds a PhD from SUNY Buffalo and has authored over 90 publications. Awards include the 2024 Vice-Chancellor’s Teaching Excellence Award (Highly Commended) and the 2023 School of Engineering Faculty Teaching Award. Education: PhD, SUNY Buffalo, United States MSc, University of Wisconsin, Madison, United States Bachelor of Arts/Bachelor of Science, SUNY Buffalo Research Interests: Urban heat islands, sustainable construction materials, floodplain soil dynamics, and GIS applications in environmental management. His recent publications address climate change impacts on rainfall patterns, mass timber sustainability, and urban microclimate analysis. He supervises PhD students in areas like urban heat islands and closed landfill management. Grants include projects on tram journey greenhouse gas footprints and stormwater quality protocols. Professional memberships include Friends of Maribyrnong Creek and the Victorian Plant Society. He actively contributes to teaching excellence initiatives, emphasizing humanitarian engineering education and employability skills integration.

Haytham Fayekمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Dr. Haytham Fayek is a Senior Lecturer in the School of Computing Technologies at RMIT University, leading the Machine Learning and Intelligence Group. He holds roles in the Evolutionary Computing and Machine Learning (ECML) Group, AI Innovation Lab, and the Centre for Industrial AI Research & Innovation (CIARI). His academic journey includes a PhD from RMIT (2019), postdoctoral work at Meta (2018-2020), and industry experience as an electrical engineer. He teaches courses like Foundations of Artificial Intelligence and Programming Fundamentals for Scientists. Research focuses on AI systems that generalize from limited data, emphasizing continual learning, multimodal learning, and applications in satellite systems, structural engineering, and gaming. Key projects include SAR interference mitigation, graph neural networks for automotive design, and cognitive load measurement in video games. He has supervised over 15 PhD/MS students and authored 60+ peer-reviewed publications. Notable achievements include a 2025 Spotlight presentation at ICLR and 2023 Best Paper nominations. Awards include EACL 2024 publication and IEEE Transactions contributions. His work bridges theory (e.g., SWAP-NAS NAS framework) with applications like autonomous satellite systems and aircraft defect tracking through NLP.

Vincenzo Muscarelloمشاهده پروفایل

مدرس ارشد

• Aero-Servo-Elasticity
• Rotorcraft Dynamics
• Urban Air Mobility
• +۶ مورد دیگر

Dr. Vincenzo Muscarello is a Senior Lecturer in the Department of Aerospace Engineering and Aviation at RMIT University's School of Engineering. He has held academic positions including Assistant Professor at Politecnico di Milano (2018–2022) and a Postdoctoral Researcher there (2013–2018), as well as an Honorary Research Fellow at the University of Liverpool (2012). He obtained a Master's in Aeronautical Engineering (2009) and a PhD (2013) from the Polytechnic University of Milan. His research focuses on aero-servo-elasticity and rotorcraft dynamics, with particular emphasis on multidisciplinary modeling for aircraft and rotorcraft design, verification, and certification. Current research areas include advanced/urban air mobility, aeroservoelasticity of fixed- and rotary-wing aircraft, distributed electric propulsion systems, and development of digital twins for loads prediction and fatigue life assessments. He led the Clean Sky 2 'Formosa' project, which aimed to design innovative control surfaces for NextGen Civil Tiltrotors in collaboration with Leonardo Helicopters. Muscarello supervises research projects such as 'Exploring Aeroelastic Stability...' and 'SafeSky: Fusion...'. He is open to supervising Masters/PhD students and collaborating on industry projects. His work integrates computational fluid dynamics (CFD), multibody dynamics, and real-time simulations to address aeroelastic stability and vibration control challenges. Key collaborations and initiatives include the Formosa Clean Sky 2 project and partnerships with industry and academic institutions. His research contributes to the advancement of tiltrotor technology, urban air mobility, and rotorcraft safety and efficiency.

Brendan McGrathمشاهده پروفایل

استاد

• Power Electronics
• Renewable Energy
• Electrical Energy Conversion
• +۵ مورد دیگر

Professor Brendan McGrath is a faculty member at RMIT University's School of Electrical and Computer Engineering. He holds the rank of Professor and has been with RMIT since May 2010. His research focuses on modulation and control of power electronic systems, particularly multilevel converters, converter topologies, and grid integration of renewable energy systems. Education: Not explicitly detailed in the text. Awards: Recipient of the Douglas Lampard Research Medal from Monash University (2004). Research Interests: Modulation theory for power electronics, multilevel converters, high-performance control systems, and applications in motor drives and grid-connected inverters. His recent publications emphasize grid stability, renewable integration, and advanced control strategies for inverters. McGrath has supervised over a dozen research projects, including topics like dual active bridge converters and circular business models for EV batteries. Teaching Interests: Power electronics, renewable energy, electrical energy conversion, and smart energy systems. Collaborations: Associate Editor for IEEE Transactions on Industry Applications and Industrial Informatics.

• Food Sciences
• Agricultural Biotechnology
• Chemical Engineering
• +۳ مورد دیگر

Neil McKenzie serves as a Research Fellow at Queensland University of Technology's Faculty of Engineering, specifically within the School of Mechanical, Medical & Process Engineering. With over 15 years of continuous service since July 2005 at QUT's Sugar Research and Innovation center, he brings extensive industry experience to his academic role. McKenzie holds a Bachelor of Technology in Industrial Instrumentation from Central Queensland University. His career progression demonstrates steady advancement from apprentice Instrument fitter (1981-1986), to Technician/Senior Technician (1986-1996), to Research Engineer (1996-2005), culminating in his current Research Fellow position. This trajectory reflects deep integration with the sugar industry's technical requirements. His research expertise centers on sugar mill engineering , with specialized knowledge in industrial instrumentation and process optimization . McKenzie's work spans Food Sciences, Agricultural Biotechnology, and Chemical Engineering domains, with practical applications implemented across Thailand, China, and South America. His publication record shows consistent scholarly output since 2001, with recent work expanding into sustainable processing technologies and biomaterials research. McKenzie manages the production of specialized sugar mill instrumentation products for global distribution, demonstrating his ability to bridge academic research with commercial applications. His work on automated control systems, cane property characterization, and sustainable processing technologies represents the evolving focus of his research toward efficiency and environmental sustainability in the sugar industry.

• STEM Education
• Sustainable Development
• Water Resources Management
• +۳ مورد دیگر

Professor Les Dawes is a distinguished academic in the School of Civil & Environmental Engineering at Queensland University of Technology (QUT). He holds a PhD and BAppSc in Geology from QUT. His research spans STEM education, sustainable development, water resource management, and environmental engineering. Notably, he led the Step Up project ($12M grant) to enhance science/mathematics teacher training in Queensland. He also contributed to the Temaiku sustainable urban development project in Kiribati, focusing on culturally appropriate infrastructure. His awards include Vice-Chancellor’s Excellence Awards (2014, 2011) for teamwork and academic engagement. Professor Dawes supervises numerous PhD projects, including studies on precast concrete optimization and Indigenous water equity. He collaborates with institutions like Brisbane Airport Corporation and the Kiribati Government. His work emphasizes real-world applications, integrating environmental sustainability with engineering practice. Education: PhD (QUT), BAppSc(Geology) (Queensland Institute of Technology). Research Interests: STEM pedagogy innovation, water quality protection, urban sustainability, and interdisciplinary solutions to environmental challenges. His publications address soil carbon analysis, sustainable logistics, and green infrastructure design. Awards: Highlighted are his Vice-Chancellor’s recognitions for fostering collaboration and educational impact. His supervision spans topics like precast concrete efficiency and Indigenous community resilience.

• Power Electronics
• Renewable Energy Systems
• Electromagnetic Compatibility
• +۳ مورد دیگر

Prof Firuz Zare is the Head of School of Electrical Engineering & Robotics at Queensland University of Technology (QUT). With over 20 years of experience in academia, industry, and international standardization committees, he specializes in power electronics, renewable energy systems, electromagnetic compatibility, and pulsed power. His research focuses on grid-connected renewable energy, harmonics mitigation, and standardization of future grids. He has published over 320 peer-reviewed papers, secured AU$10M+ in research funds, and leads international projects. Awards include the Star Associate Editor Award (2020) and the 2015 Innovation and Excellence Award. Education: PhD in Electrical Engineering from QUT. Research areas include advanced power converter topology, electromagnetic interferences, grid standardization, and pulsed power applications. He has supervised 35 PhD/M.Eng students and 14 post-docs. Notable contributions include establishing IEEE Power Electronics Societies in Queensland and leading IEC standardization efforts for solar inverters and wind turbines. His teaching innovations include Power Electronics Education E-Books and entrepreneurship-focused pedagogy.