جست‌وجوی استاد و پژوهشگر

Yuzhe Tianمشاهده پروفایل

مدرس پاره‌وقت

• Anomaly Detection
• Industrial Internet of Things (IIoT)
• Sleep Analysis
• +۵ مورد دیگر

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
• +۵ مورد دیگر

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.

Djamel Benrachouمشاهده پروفایل

پژوهشگر

• Intelligent Transportation Systems (ITS)
• Deep Learning
• Automation
• +۴ مورد دیگر

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 Jusakمشاهده پروفایل

مدرس ارشد

• Internet of Things (IoT)
• Telehealthcare
• Blockchain Technology
• +۳ مورد دیگر

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 Kerrisonمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Internet of Things (IoT)
• Public Key Infrastructure (PKI)
• +۴ مورد دیگر

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
• +۸ مورد دیگر

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-Brownمشاهده پروفایل

مدرس

• Autonomous Vehicles
• Robotics
• Control Systems
• +۳ مورد دیگر

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.

Erick Alfons Lisanganمشاهده پروفایل

مدرس

• Intelligent Transportation Systems
• Artificial Intelligence
• Deep Learning
• +۵ مورد دیگر

Erick Alfons Lisangan is a Computer Science lecturer at Atma Jaya University of Makassar and a Doctor of Philosophy student at the University of Western Australia's School of Physics, Mathematics and Computing. His research integrates artificial intelligence with transportation infrastructure to address urban mobility challenges. Education Master of Computer Science, Gadjah Mada University (2013-2015) Bachelor of Computer Science, Atma Jaya University of Makassar (2006-2010) Research Interests His core focus lies in Intelligent Transportation Systems , analyzing graph traffic networks and spatiotemporal data collection. He develops algorithms for real-time traffic condition inference using embedded systems and AI-driven simulation. Specialized work includes deep learning architectures (LSTM/BiLSTM) for passenger flow prediction, fuzzy logic systems for dynamic route optimization, and wireless sensor networks for smart city applications like flood detection. His research bridges theoretical AI with practical urban infrastructure solutions. Research Output Trends Publications (2018-2025) reveal a trajectory from foundational smart city sensor networks toward advanced AI-driven transportation modeling. Recent work emphasizes hybrid deep learning for Transjakarta bus system prediction, while earlier contributions established fuzzy ant colony systems for traffic-responsive routing and image-based fake news detection frameworks. Advising and Grants Lisangan serves as a casual tutor for Data Structures & Algorithms and Computational Thinking with Python at UWA during his PhD studies. No formal advisees or research grant details are documented in the provided materials. Labs and Teams His doctoral research operates under supervision of Professor Rachel Cardell-Oliver and Professor Amitava Datta at UWA, contributing to intelligent transportation systems research groups with cross-institutional collaborations in Indonesia and Australia.

Hanna Suominenمشاهده پروفایل

استاد

• Machine Learning
• Health Informatics
• Natural Language Processing
• +۴ مورد دیگر

Prof Hanna Suominen is a Professor of Computer Science and Associate Director (Neuroinformatics) at the Australian National University (ANU), and Co-Chair of the ANU Our Health in Our Hands strategic initiative. She holds a PhD and Adjunct Professorship from the University of Turku (Finland), and a Master of Leadership in Curriculum and Pedagogy from Monash University. Her research focuses on applying machine learning and data analytics to healthcare, particularly in neuroinformatics, precision medicine, and medical technology. She leads projects in AI-assisted workflows, chronic disease management, and medical imaging analysis. Notable contributions include developing tools for Parkinson's disease diagnosis via EEG, diabetes glucose prediction systems, and NLP-based medical information extraction. She has received the Senior Fellow of the Higher Education Academy (SFHEA) and has led teams at CSIRO/Data61. Her work bridges technology, education, and health to enhance Australia's healthcare innovation. Education: PhD in Computer Science (University of Turku, 2009) Adjunct Professorship (University of Turku, 2013) MSc in Applied Mathematics (University of Turku, 2005) MEdL in Curriculum & Pedagogy (Monash University, 2020) Research Interests: Machine learning applications in healthcare, neuroinformatics, medical imaging analytics, personalized medicine, natural language processing for health data, and AI ethics in medical technology. Her work emphasizes interdisciplinary collaboration with industry partners like Lightcast and Konan Medical. Grants & Projects: Leads ANU initiatives like the John Eccles Institute and OHIOH, with current projects including closed-loop brain stimulation for depression, AI-driven diabetes management systems, and biomarker discovery for multiple sclerosis. Active in securing funding for AI in advanced materials and healthcare informatics. Awards: Senior Fellow of the Higher Education Academy (ANU, 2019) Labs/Teams: Former leader of the TAMPA (Multimodal Pattern Analysis) and NLP teams at CSIRO/Data61. Currently oversees neuroinformatics research at ANU's John Eccles Institute.

• Learning and Teaching
• Computer Education
• Serious Games
• +۷ مورد دیگر

Dr. Julian Dermoudy is an Associate Professor and Associate Head (Learning and Teaching) in the School of Information and Communication Technology at the University of Tasmania. With over 25 years of teaching experience, he has received national and institutional recognition for his pedagogical contributions. His roles have included Head of School, Associate Dean, and Course Coordinator, reflecting his leadership in academic administration. His teaching spans the Bachelor of ICT and Master of ITS programs. Research Interests: Learning and Teaching Innovations Computing Education and Curriculum Design Serious Games and Gamification for Behavior Change Multimodal Analysis and Verification Parallelism and Software Engineering Funded Projects: UTAS Internal Funding: Embedding Indigenous Knowledge in Curriculum (2021-2021) Advising: Supervised 11 doctoral candidates across domains like biometric authentication, ICT curriculum design, and mobile technology impact. Recent students include Simon Stanton (Cooperative Intent) and Shahan Chowdhury (Collaborative In-Store Shopping). Labs/Teams: Active in curriculum redesign initiatives and educational technology innovation, particularly in VR and gamification applications.

Nasser Asgariمشاهده پروفایل

مدرس ارشد

• Robotics
• Embedded Systems
• Computer Vision
• +۳ مورد دیگر

Nasser Asgari is a Senior Lecturer in the College of Science and Engineering at Flinders University, Australia. He holds adjunct roles in the Medical Device Research Institute and serves as Teaching Program Director (TPD) for Engineering and Design. His key responsibilities include coordinating Electrical & Electronic Engineering and Robotics Engineering programs. Dr. Asgari's academic background includes a PhD in Computer Engineering from the University of Adelaide, an MSc in Communication Systems Engineering, and a BSc in Electronic Engineering. His research focuses on robotics, embedded systems, and computer vision applications in assistive technologies and disaster response. Specific interests include interprocessor communication, mobile robot navigation, and people detection using thermal/color cameras. His work spans multidisciplinary projects such as designing rescue robots with real-time vision systems and developing algorithms for thermal image analysis in disaster zones. He has published in journals like the International Journal of Mechanical Engineering and Robotics Research, and authored books on robotics applications. Teaching responsibilities include coordinating topics like ENGR2712 (Automation & Industrial Control), ENGR7851 (Advanced Electronic Design), and ENGR3771 (Robotic Systems). He actively contributes to curriculum development in cyber-physical systems, sensors/actuators, and advanced robotic systems.

Helia Farhoodمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Machine Learning
• Image Processing
• +۳ مورد دیگر

Dr. Helia Farhood is an Honorary Senior Research Fellow at the School of Computing, Macquarie University, specializing in Artificial Intelligence, Machine Learning, and Image Processing with applications in educational technology and object recognition. Her academic qualifications include a PhD in Computer Systems and Artificial Intelligence from the University of Technology Sydney (awarded November 2021) and a Master's degree in Computer-AI from Amirkabir University of Technology (Tehran Polytechnic, awarded September 2013). Dr. Farhood's research spans interdisciplinary AI applications, with significant contributions in student outcome prediction using generative adversarial networks, explainable AI through LIME heatmaps, and image-based storytelling systems. Her work integrates machine learning with educational data mining to enhance creativity assessment and learning analytics, while maintaining strong technical focus on 3D reconstruction and object recognition. Analysis of her 16 publications (2020-2025) reveals three dominant research trajectories: (1) AI-driven educational analytics for student performance prediction, (2) advanced image processing techniques for object recognition and 3D reconstruction, and (3) systematic reviews establishing methodological foundations in presentation attack detection and image-based storytelling. Her recent work increasingly emphasizes explainability and ethical considerations in AI deployment. Dr. Farhood has participated in externally funded research projects, including the 2022 project "Estimating the Number of Tyres in Stockpiles" (October-December 2022). No information is available regarding students she has advised. No information is available about specific research laboratories or teams led by Dr. Farhood.

• Music Psychology
• Music Cognition
• Auditory Memory
• +۴ مورد دیگر

Dr. Tim Byron is a Lecturer in the School of Psychology at the University of Wollongong, Faculty of the Arts, Social Sciences and Humanities, where he has held academic appointments since 2018. His research focuses on the intersection of music psychology and cognitive processes, particularly examining how musical structures interact with memory systems and expectation formation. His educational background includes a PhD from Western Sydney University (2004-2009), which provided the foundation for his specialized work in music cognition. This training is evident in his methodologically rigorous approach to studying auditory phenomena. Byron's research program centers on music cognition with particular emphasis on earworm phenomena, musical hooks, and the physiological responses to musical expectation violations. His work demonstrates how musical elements like vocals, compound hooks, and choruses enhance memorability through complex interactions between auditory processing and memory systems. Recent investigations have explored autonomic responses to rhythm changes using heart rate variability measurements, revealing the deep physiological embedding of musical processing. Analysis of his publication trends shows consistent output across multiple formats including high-impact journal articles, book chapters, and media contributions. His work spans fundamental cognitive processes in music perception to applied analyses of contemporary streaming habits and chart music evolution. The 2022 book "Hooks in Popular Music" represents a significant synthesis of his research on musical catchiness factors. Byron actively supervises doctoral research with five current students working on topics including cardiac responses during music listening, philosophical pitch analysis, and mental health in music performance students. His teaching portfolio includes coordinating the History and Philosophy of Psychology course while offering supervision in music psychology and cognition. His leadership roles include serving as Head of Students since February 2023 and regular media engagement through The Conversation, ABC broadcasts, and international conference presentations. This public scholarship demonstrates effective translation of complex cognitive concepts for broader audiences.

• Artificial Intelligence
• Machine Learning
• Probabilistic Inferencing
• +۵ مورد دیگر

Barry Drake serves as an Adjunct Professor in the School of Computer Science at the University of Technology Sydney (UTS), where he is also affiliated with the Faculty of Engineering and Information Technology and the Data Science Institute. Additionally, he holds the position of Co-Chief Scientist at the Digital Health Cooperative Research Centre and participates in government advisory committees. His career bridges academic research and industry application, with significant experience in translating research into practical technology solutions for business and government sectors. Drake earned his PhD in Computer Science from UNSW Australia (1998-2003) and a BSc with First Class Honors in Computer Science from UTS (1991-1996). His educational background is complemented by a Certificate of Proficiency for Radio Fitter/Mechanic Electronic Systems from the Royal Australian Navy. His research focuses on algorithms and software for practical smart systems, with particular expertise in applications of AI and machine learning, probabilistic inferencing and knowledge compilation, learning probabilistic models, and fast-efficient near-neighbor searching in ultra-high dimensional spaces. His work demonstrates a clear trajectory toward health informatics applications , especially in health systems and delivery of health services, where he has made significant contributions through projects like the Lumos statewide linkage programme. The analysis of his publication record reveals a consistent pattern of research bridging theoretical computer science with practical healthcare applications. His recent work shows increasing focus on health data integration, patient journey modeling, and privacy-preserving synthetic data generation for healthcare applications, while maintaining his foundational expertise in probabilistic models and efficient search algorithms. Inventor on 20 filed patents ORCID identifier: 0000-0003-0572-9936 Drake actively supervises Masters and PhD students according to his profile, and his funded research portfolio includes multiple grants from the Digital Health CRC and NSW Health. His industry experience, particularly his 13 years at Canon Information Systems Research Australia where he served as Senior Principal Engineer and lead researcher for machine learning, informs his approach to technology research methods from a commercial perspective. His current projects focus on the impact of integrated care in New South Wales, synthetic data generation, and patient journey modeling. As Co-Chief Scientist at the Digital Health CRC, Drake contributes to a major national initiative focused on digital health innovation. His work with the Lumos programme has created Australia's first statewide linked data asset across primary care and other health settings, providing unique insights about cross-setting healthcare utilization. This initiative represents a significant contribution to health data infrastructure in Australia.

Binghao Liمشاهده پروفایل

دانشیار

• Indoor Positioning
• Pedestrian Navigation
• Satellite Positioning
• +۳ مورد دیگر

Associate Professor Binghao Li leads the MIoT & IPIN Lab at the School of Minerals and Energy Resources Engineering, University of New South Wales, Sydney. He holds a PhD in Spatial Information Systems from UNSW and advanced degrees in Civil and Electrical/Mechanical Engineering from Tsinghua University and Beijing Jiaotong University. Expertise in indoor/outdoor positioning systems Pioneering mine IoT applications Leader in pedestrian navigation research His research spans indoor positioning technologies, satellite navigation, and mining IoT solutions. Key grant projects include: 2021 CRC-P grant ($2m) for underground mine LoRa networks 2020 ARC Research Hub ($5m) for connected sensors 2018 Digital Grid Seed Funding for indoor navigation 2015-2019 ARC Linkage grants for positioning systems Award highlights: 2019 Best Paper & Presentation Awards 2010 VC's Post-Doctoral Fellowship 2004-2005 student research awards He supervises research in indoor positioning and mine IoT, and teaches courses including ENGG1000 Engineering Design and MINE8710 Mine Slope Stability.