Find Academic Supervisors

• Computer Architecture
• Microelectronics
• Nanoscale Technology
• +9 more

Dr. Paul Beckett is an Honorary Associate Professor in the School of Engineering at RMIT University. His research focuses on cutting-edge areas such as computer architecture, nanoscale microelectronics, digital logic design, and photonics. He specializes in low-power circuit design, FPGA-based systems, and sensor technologies with applications in healthcare and environmental monitoring. Beckett's teaching interests include embedded systems, VLSI design, and hardware description languages (VHDL). His research spans disciplines such as electronics, communications engineering, and distributed computing, with notable contributions to null convention logic (NCL) circuits, plasmonic sensors, and spectral imaging systems. He has collaborated on innovative projects like the TIARA apnea monitoring system and wearable health technologies. His recent work emphasizes interdisciplinary applications, including healthcare technology and biomimetic optical systems. Notable publications include advancements in gas sensing (H2S detection), THz spectrum analysis, and machine learning optimization for embedded systems. Beckett actively supervises research projects in asynchronous computing architectures and nanotechnology.

• System Identification
• Stochastic Signal Processing
• Dynamic System Modelling
• +4 more

Professor Brett Ninness is a faculty member at the University of Newcastle, Australia, holding the position of Professor in the School of Electrical Engineering and Computing. He has served in various administrative roles, including Assistant Dean (Research Training), Deputy Head of Faculty, and Acting Pro Vice Chancellor. His research focuses on dynamic system modeling, system identification, stochastic signal processing, and wireless communications. He has authored over 100 papers and held editorial roles in journals like Automatica and IEEE Transactions on Automatic Control. Education: Brett Ninness earned his BE, ME, and PhD in Electrical Engineering from the University of Newcastle. His teaching spans systems theory, signal processing, digital systems, and communications. Research Interests: He specializes in system identification, noise-robust signal processing, and applications in wireless communications. His work includes developing algorithms for state estimation, Kalman filtering, and nonlinear model identification. Recent projects involve collaborations with industry partners like Bell Labs and Agere Systems. Publications: His most recent works address smoothed state estimation, nonlinear system identification, and distributed Kalman filtering. Articles highlight advancements in stochastic processes, control systems, and Bayesian methods. Awards: Recipient of the 2001 Tall Poppy Award for outstanding scientific contribution. He is a member of editorial boards and international committees, including the IEEE Technical Committee on System Identification and IFAC. Grants & Supervision: Extensive grants in system identification and control theory. Supervised numerous PhD/Master’s students, though specific names are not listed here. Collaborations: Partnerships with institutions like Royal Institute of Technology (Sweden), Linköping University, and Vrije Universiteit Brussel. Active in global research networks through IEEE and IFAC committees.

• Industrial Internet of Things
• Digital Manufacturing
• Industry 4.0
• +3 more

Prem Prakash Jayaraman is Professor and Director of the Factory of the Future and Digital Innovation Lab at Swinburne University, leading digital transformation initiatives for manufacturing and smart cities. His research develops IoT architectures for industrial applications with over $7.5M in external funding. Key projects include the Advanced Manufacturing Industry 4.0 Hub providing SME digital readiness assessments, 5G-enabled smart city solutions for road maintenance, and industrial IoT systems for quality control. His research spans edge computing, digital twins, and cyber-physical systems with applications in food processing, logistics, and healthcare. Professor Jayaraman has published extensively on IoT middleware, sensor sharing marketplaces, and quality-aware autonomous systems. He leads Swinburne's strategic partnerships in Industry 4.0 and contributes to national initiatives through ARC-funded research hubs on digital manufacturing.

Preethi PreethichandraView profile

Professor

• Biomedical Engineering
• Sensor Development
• Nanotechnology
• +5 more

Preethi Preethichandra is Deputy Dean (Research) at CQUniversity's School of Engineering and Technology, specializing in Electrical Engineering. She holds a PhD and is a Senior Member of IEEE. Her roles include Discipline Leader for Electrical Engineering and Unit Coordinator for courses like Mechatronics Systems Design and Embedded Systems. She is actively involved in research supervision across Biomedical Engineering, Electrical Engineering, and Sensors. Education: BSc.Eng, MEng, MEBM, PhD Research Interests: Biomedical instrumentation, sensor development, nanotechnology, exoskeleton systems, structural health monitoring, and wireless sensor networks. Her work combines nanomaterials with biomedical applications and explores robotics for environmental monitoring. Publications: Over 60 peer-reviewed articles in journals like IEEE Sensors and Sensors (Basel), focusing on exoskeletons, smart sensors, and electrochemical biosensors. Recent work addresses agricultural exoskeletons and structural health monitoring using smart sensors. Labs/Teams: Leads research groups in mechatronics, biomedical engineering, and sensor networks. Involved in interdisciplinary projects on environmental robotics and asset management.

• Cyber-Physical Systems
• Internet of Things (IoT)
• Edge Computing
• +4 more

Prof Jiong Jin is a Full Professor and Academic Director (Research Training) at Swinburne University of Technology's School of Science, Computing and Engineering Technologies. He holds a B.Eng (First Class Honours, Nanyang Technological University) and a Ph.D. (University of Melbourne). His research focuses on networked systems, IoT, edge computing, and robotics automation, with applications in smart manufacturing, transportation, and cities. Research Interests: Control and optimization of networked/embedded systems Edge/fog computing architectures Cyber-physical systems and IoT applications Autonomous robotic systems Real-time distributed algorithms Recent Publications: Recent work includes groundbreaking contributions in edge-IoT frameworks (Farm-LightSeek), cloud-fog automation paradigms, and adversarial machine learning defenses. His research bridges theory and practice through collaborations with industry partners like KDDI Research and IMCRC. Awards & Recognition: 2020 School Research Excellence Award 2019 Faculty Mid-Career Researcher Award Commendation Top 2% global cited scientists (Stanford, 2019) AI 2000 Most Influential Scholars (2021/2022) Grants & Collaborations: Australian Research Council (ARC) Linkage Projects CSIRO Data61 collaborations Industry partnerships with YSTC Energy, IMCRC, and iMOVE Australia Lab & Teams: Leads a multidisciplinary team advancing industrial IoT and smart systems through projects like the Factory-in-a-Box platform and virtual manufacturing solutions. His lab emphasizes practical industry applications of theoretical advancements.

• Mechanical Engineering
• Materials Engineering
• Nanotechnology
• +4 more

Haifei Zhan is an Adjunct Associate Professor in the School of Mechanical, Medical & Process Engineering at Queensland University of Technology (QUT). His research focuses on nanomaterials, mechanical properties, numerical modelling, and thermal analysis. He holds a PhD from QUT and a Bachelor of Engineering. Research Interests: Zhan’s work spans nanotechnology, materials engineering, and mechanical engineering. Key areas include nanomaterials (e.g., diamond nanothreads, graphene), thermal transport in nanostructures, and computational mechanics. His research often integrates atomistic simulations and experimental validation. Awards & Grants: He has received awards such as the ICACM Young Investigator Award (2018) and the International Young Computational Award (2019). His grants include projects like 'A Novel Multilevel Modelling Framework to Design Diamond Nanothread Bundles' (DP200102546) and 'Breakdown of Hooke’s Law at the Nanoscale' (DP170102861). Publications & Supervision: Over 20+ peer-reviewed articles, including studies on ceramic coatings, graphene heterojunctions, and nanocomposite hydrogels. He has supervised PhD/Master’s projects on nanowire characterization, carbon-based nanosprings, and nanocomposite modelling.

Haohui LuView profile

Research Fellow

• Artificial Intelligence
• Graph Machine Learning
• Health Informatics
• +12 more

Haohui Lu is a Research Fellow at the Molly Wardaguga Research Centre within the Faculty of Health. He is registered to supervise postgraduate research and holds a PhD from The University of Sydney, awarded in March 2024. His work bridges artificial intelligence and public health, with a focus on ethical and explainable AI systems. Research Interests: Artificial Intelligence and Machine Learning Graph Machine Learning and Knowledge Graphs Health Informatics and Clinical Decision Support Bias Mitigation and Fairness in AI Large Language Models for Healthcare Statistical Modeling and Real-World Data Analysis His recent publications demonstrate a strong trend in applying machine learning—particularly graph-based and language models—to public health challenges such as disease progression, policy analysis, and undernutrition. He frequently publishes in high-impact journals like PLoS One , Scientific Reports , and Neurocomputing , and presents at top venues such as EMNLP. His work emphasizes fairness, interpretability, and practical impact for policymakers and communities. Scientific Contributions and Recognition: Active contributor to UN Sustainable Development Goals, particularly in health and well-being. Presented research at EMNLP 2024 on LLMs for disease prediction. Research disseminated through news outlets and widely shared on academic platforms like Mendeley. Advising and Leadership: Registered as a postgraduate research supervisor, indicating a role in mentoring future researchers. Provides technical leadership in AI tool development, research data platforms, and LLM applications, supporting multidisciplinary and international collaborations. Laboratories and Teams: Based at the Molly Wardaguga Research Centre, a hub for health research, where he contributes to projects integrating AI with real-world health data and policy.

Yuzhe TianView profile

Part-Time Lecturer

• Anomaly Detection
• Industrial Internet of Things (IIoT)
• Sleep Analysis
• +5 more

Yuzhe Tian is a Part-Time Lecturer at the School of Computing, Macquarie University, within the Faculty of Science and Engineering. His research focuses on interdisciplinary applications of machine learning, including anomaly detection in industrial IoT systems, sleep stage recognition via graph networks, and brain-computer interface (BCI) technologies. He holds a Doctor of Philosophy and has published extensively in top-tier conferences and journals since 2019. Research interests include real-time BCI systems using geometric learning, optimization of neural networks (e.g., model pruning and quantization), and healthcare applications like sleep analysis through graph attention networks. His work bridges computational methods with practical challenges in biomedical engineering and industrial automation. Yuzhe has collaborated on projects leveraging multi-view learning for anomaly detection and swarm intelligence algorithms (e.g., Krill Herd Algorithm). His publications span topics from lightweight BCI frameworks to cybersecurity in IIoT environments, demonstrating a strong focus on both theoretical advancements and real-world implementation.

• Machine Learning
• Hypergraph Models
• Social Network Analysis
• +5 more

Malik Khizar Hayat is a Researcher at Macquarie University's School of Computing within the Faculty of Science and Engineering. He holds a Doctor of Philosophy (PhD) and is associated with research in machine learning, hypergraph models, and dynamic network analysis. His work emphasizes supervised learning techniques applied to social networks, anomaly detection, and graph-level classification. Hayat has collaborated internationally on projects involving heterogeneous hypergraphs and self-supervised learning frameworks. His research outputs span computer science, data mining, and social systems analysis, with a focus on practical applications like recommendation systems and academic ranking methodologies. Education: Doctor of Philosophy (PhD), Macquarie University Research Interests: Development of hypergraph frameworks for session-based recommendations Self-supervised learning techniques in graph embedding Anomaly detection in dynamic networks using co-evolutionary patterns Supervised learning applications for identifying academic rising stars Bibliometric analysis of research collaboration impacts Key Research Trends: Recent work (2023-2025) focuses on advancing hypergraph models for complex network analysis, integrating time-aware mechanisms, and applying machine learning to real-world systems like social recommendations and academic ranking. His methodologies often combine deep learning with graph theory innovations. Grants & Collaborations: Research funded through institutional grants at Macquarie University, with collaboration networks extending to institutions in China (via co-authors like Yang, Jie and Xue, Shuqiang) and other international partners. No specific grant details are disclosed in the provided texts. Labs/Teams: Affiliated with Macquarie University's computational research groups focusing on machine learning and network analysis, though specific lab names aren't mentioned. Active participation in IEEE conferences and journal publications indicates strong ties to computational research communities.

• Biomedical Engineering
• Electrical Engineering
• MEMS/NEMS Technology
• +5 more

Dr. Said Al-Sarawi is an Associate Professor in the School of Electrical and Mechanical Engineering at the University of Adelaide, affiliated with the Centre for Biomedical Engineering (CBME) and The Centre for High Performance Integrated Technologies and Systems (CHiPTec). He holds a PhD in Electrical and Electronic Engineering (2003) and a Graduate Certificate in Education (2006). His research focuses on biomedical engineering, MEMS/NEMS technologies, neuromorphic systems, and secure hardware/software co-design. Dr. Al-Sarawi leads multiple research initiatives including advanced integrated circuits using Gallium Nitride, fall detection systems for elderly care, and memristor-based neuromorphic applications. He has secured funding from the Premier’s Research and Industry Fund (PRIF), ARC Discovery grants, and international collaborations. Current projects involve 24 PhD students and postdoctoral researchers across biomedical sensors, cybersecurity in AI, and space-based sensor systems. He has been recognized with the University Medal (2003) for postgraduate academic excellence and actively contributes to education committees within the university. His work spans interdisciplinary domains, bridging biomedical innovations with cutting-edge electronics and cybersecurity solutions.

Djamel BenrachouView profile

Researcher

• Intelligent Transportation Systems (ITS)
• Deep Learning
• Automation
• +4 more

Dr. Djamel Benrachou is a Senior Research Officer at the Centre for Accident Research & Road Safety – Queensland (CARRS-Q) at Queensland University of Technology (QUT). He holds dual PhDs in Intelligent Transportation Systems (ITS) and Automatics and Signals, along with a Master in Electronics and a Bachelor of Engineering (Electrical). His research focuses on algorithm development, deep neural networks, and real-time robotic applications in Connected Automated Vehicles (CAVs), Generative AI, and Human-Machine Interaction (HMI) systems. Key projects include the Cooperative and Highly Automated Driving (CHAD) , DynaMix-FM (mixed reality for future mobility), and safety risk evaluation of remote operations in automated vehicles. His work integrates big data analytics, cloud computing, and embedded systems to address challenges in autonomous systems and intelligent transportation. Education: PhD in ITS (QUT), PhD in Automatics/Signals (QUT), Master of Electronics, Bachelor of Engineering (Electrical). Awards: QUT ARC Linkage Scholarship (2020), QUT Tuition Fee Scholarship (2020). His research aligns with CARRS-Q's mission to enhance road safety through advanced technologies, focusing on vehicle motion prediction, social interaction-aware systems, and AI-driven solutions for transportation systems.

Jusak JusakView profile

Senior Lecturer

• Internet of Things (IoT)
• Telehealthcare
• Blockchain Technology
• +3 more

Dr. Jusak Jusak is a Senior Lecturer in Internet of Things (IoT) at the School of Science and Technology, James Cook University Singapore. He holds a PhD in Electrical Engineering from RMIT University and a BEng in Electrical Engineering from Brawijaya University, Indonesia. His research focuses on IoT applications in telehealthcare, blockchain for healthcare IoT, and lightweight machine learning for constrained devices. Dr. Jusak has held academic positions at Dinamika University (Surabaya, Indonesia) and Massey University (New Zealand). He has secured grants including a Cross-Campus Collaboration Grant for blockchain development and a Teaching Innovation Grant for the VetheRBlocks project. He is a Guest Editor for the Electronics journal's special issue on wireless communication security. His research interests include IoT device development for medical signal analysis, secure cloud-based healthcare systems, and hybrid-channel communication for rural healthcare. He has published over 20 peer-reviewed articles and received awards such as the ICITAS 2018 Best Paper Award and a 2022 Futuristic Technology Award for IoT-based water quality monitoring. Dr. Jusak's work emphasizes practical IoT solutions for healthcare challenges, integrating machine learning and blockchain to enhance data security and accessibility in distributed networks.

Steve KerrisonView profile

Senior Lecturer

• Cybersecurity
• Internet of Things (IoT)
• Public Key Infrastructure (PKI)
• +4 more

Dr. Steve Kerrison is a Senior Lecturer in Cybersecurity at James Cook University (Singapore Campus). He holds a PhD and MEng in Computer Science from the University of Bristol, and certifications including CISSP and CCSP. His expertise spans IoT cybersecurity, embedded systems, and energy-efficient computing. Education: PhD in Computer Science, University of Bristol (2010-2015) MEng in Computer Systems Engineering, University of Bristol (2005-2009) CISSP and CCSP certifications (ISC)² Research Interests: Focuses on IoT cybersecurity, PKI for IoT, energy-efficient computing, and Industry 4.0. Collaborations include EU-funded projects (ENTRA, ICT-Energy) and Singapore’s National Cybersecurity R&D Program. Teaching: Specializes in open-source tools and community-driven cybersecurity education. Formerly a Senior Research Associate at Bristol and CTO at MICROSEC, a Singapore-based IoT security startup.

• Cosmology
• Extragalactic Astrophysics
• Physics and Astronomy Education
• +8 more

Dr Michael Cowley is a Senior Lecturer in the School of Chemistry & Physics at Queensland University of Technology (QUT), Faculty of Science. He leads the QUT Astrophysics Research Group and serves as the Academic Lead of Learning and Teaching. His research spans extragalactic astrophysics, galaxy evolution, and physics education, with strong involvement in major surveys such as ZFOURGE, ZFIRE, TAIPAN, and ASKAP-EMU. Research Interests: Dr Cowley's work focuses on the co-evolution of galaxies and supermassive black holes, using multi-wavelength data to study star formation, AGN activity, and quenching mechanisms across cosmic time. He also investigates physics and astronomy education, with a commitment to embedding Indigenous knowledges in science curricula. Publication Trends: His recent publications (2020–2025) reflect a strong focus on high-redshift galaxy populations, radio surveys (EMU), source detection algorithms (Hydra), and the integration of observational data with simulations. There is a clear trajectory toward large-scale data analysis, collaborative survey science, and methodological innovation in source finding and galaxy characterisation. Scientific Awards: Vice-Chancellor's Award for Excellence (2022) Faculty of Science's Educator of the Year (2021) Research Centre for Astronomy, Astrophysics and Astrophotonics Observing Funding Award (2015) Member of the International Astronomical Union (2019) Member of the Astronomical Society of Australia (2014) Member of the Australian Institute of Physics (2010) Member of the Institute of Physics (2010) Supervision and Grants: Dr Cowley supervises Honours, Masters, and PhD students in areas such as star formation rate estimation, galaxy evolution, and radio survey analysis. He is actively involved in education leadership and curriculum development. While specific grants are not listed, his leadership in major surveys implies significant research funding and collaboration. Labs and Teams: He leads the QUT Astrophysics Research Group and is a key member of international collaborations including the ZFOURGE, ZFIRE, TAIPAN, and EMU surveys, contributing to large-scale data analysis and scientific interpretation.

Kieran Quirke-BrownView profile

Lecturer

• Autonomous Vehicles
• Robotics
• Control Systems
• +3 more

Kieran Quirke-Brown serves as an Associate Lecturer in the Department of Electrical, Electronic and Computer Engineering within the School of Engineering at the University of Western Australia. He concurrently holds the position of Student Manager for the Renewable Energy Vehicles Project (REV) under Professor Thomas Bräunl's direction. His academic credentials include a Master of Professional Engineering and ongoing PhD studies at the University of Western Australia, complemented by a Master of Information Technology from the University of Queensland. Prior industry experience encompasses Smart Services Engineering at Schneider Electric, specializing in Building Management Systems (BMS) deployment and retrofits. Research centers on practical implementations of autonomous driving and robotics, with emphasis on autonomous shuttle development, modular system design, and real-time control solutions. Recent work demonstrates integration of open-source software frameworks and algorithm selection for optimal performance in transportation systems. Teaching responsibilities include Mobile Robots and Digital and Embedded Systems courses, reflecting his applied technical expertise. Through the REV initiative, he contributes to sustainable vehicle technology development while bridging academic research with industrial automation practices. Current projects focus on campus-wide autonomous shuttle deployment and risk management in modular transportation architectures.