جست‌وجوی استاد و پژوهشگر

Hoang Dinhمشاهده پروفایل

دانشیار

• Wireless Communications
• Networking Systems
• Machine Learning Applications
• +۵ مورد دیگر

Associate Professor Hoang Dinh is a faculty member at the School of Electrical and Data Engineering, University of Technology Sydney (UTS), Australia. He holds an ARC DECRA Fellowship and leads research in wireless communications, machine learning applications, and cybersecurity. His work includes over 200 publications, 20,000+ citations (h-index 53), and significant industry collaborations with Cisco and Apple Inc. He teaches IoT Security and Cyber Security for Mobile Platforms, achieving high student satisfaction scores. Key awards include the IEEE TCI Rising Star Award (2023), IEEE TCSC Excellence Award (2021), and multiple editorial recognitions from IEEE Transactions. His research focuses on 6G networks, metaverse technologies, federated learning, and blockchain security. Current projects involve secure edge computing, AI-driven communication systems, and digital twin integration. Education: PhD in Computer Science from Nanyang Technological University (2016). Research Funding: AUD 6M+ in external grants, including DECRA (2021). Editorial Roles: Editor for IEEE Transactions on Communications, Network Science and Engineering, Mobile Computing, and Wireless Communications. Industry Impact: Developed IoT security frameworks and contributed to disaster management digital transformation projects recognized in iAWARDS2024.

Yu Zhangمشاهده پروفایل

مدرس

• Mobile Computing
• Wireless Sensor Networks
• Embedded Systems
• +۵ مورد دیگر

Yu Zhang is a Lecturer in Computing (IoT/Networking) at the School of Computing, Macquarie University, Australia. He holds a PhD in Computer Science from RMIT University, an M.Eng in Distributed Computing from the University of Melbourne, and a B.Eng in Software Engineering from Southwest University for Nationalities. His research focuses on mobile computing, wireless sensor networks, embedded systems, on-device machine learning, and IoT, with emphasis on security, edge computing, and privacy preservation. He is affiliated with the Future Communications Research Centre and Smart Green Cities Research Centre. Dr. Zhang’s work integrates theoretical advancements with practical applications in IoT and edge computing. His research outputs span secure device communication, energy-efficient networking protocols, and anomaly detection frameworks. Collaborations include projects like the CSIRO Data61 PhD Scholarship. He actively contributes to IEEE and ACM, addressing challenges in privacy-aware systems and federated learning.

Shuo Liمشاهده پروفایل

مدرس

• Network Engineering
• Telecommunications
• Underwater networks
• +۴ مورد دیگر

Dr. Shuo Li is a Lecturer in the School of Engineering at RMIT University, Australia. She holds a B.Eng. (2009) and Ph.D. (2014) from City University of Hong Kong. Her research focuses on telecommunications, underwater optical networks, network design, and edge computing. She has held academic roles at RMIT since 2011 and Tianjin University (2014–2017). Education: Ph.D. and B.Eng. in Engineering from City University of Hong Kong. Research Interests: 6G cellular networks, underwater optical communication, network security, and edge computing architectures. Dr. Li leads projects on 6G mobile cellular design, underwater optical networks, and edge computing resource management. She has received awards including the Research Tuition Scholarship (2013) and CityU Mainland Scholarship (2005–2009). Her work emphasizes practical applications, such as developing web-based network design tools and security frameworks for edge computing. Recent Projects: 6G architecture development, underwater optical wireless systems, and zero-trust security in multi-access edge computing. Supervision: Active in guiding PhD/MEng students on topics like optical interconnects for data centers and edge computing security. She collaborates on industry-focused research and is available for consulting in Australia and internationally. Her work bridges theoretical advancements with real-world network challenges.

• Wound care and skin integrity
• Pressure-injury prevention
• Incontinence-associated dermatitis
• +۳ مورد دیگر

Professor Michelle Barakat-Johnson is a full-time Professor of Wound Care and Skin Integrity at the University of Sydney’s Sydney Nursing School, Faculty of Medicine and Health, and concurrently serves as Skin Integrity Lead for Sydney Local Health District. Over two decades she has built an internationally recognised program that translates evidence into policy and practice, securing more than AUD 9 million in competitive grants since 2019 and leading multi-centre trials enrolling >2,000 patients. Education & qualifications: PhD research program: “Getting to the bottom of hospital-acquired pressure injuries in one local health district” – University of Sydney (implementation-science thesis spanning four hospitals, >1,000 nurses & 1,500 patients). Research focus: Her work integrates implementation science, health economics and digital innovation to drive measurable reductions in pressure injuries, incontinence-associated dermatitis (IAD) and chronic wounds. Key strands include: Large-scale translational trials (HAPI & IMBED programs) that achieved 51% drop in pressure-injury incidence and 36% reduction in IAD prevalence across health districts. AI-enabled wound tools: led validation of Tissue Analytics app and creation of the first Australian Nurse-led Wound Care Command Centre, cutting patient wait-times from 13 days to 2 hours and saving >$1.1 M in 14 months. State-wide policy impact: toolkit adopted by NSW Clinical Excellence Commission; chairs NSW Wound Care & Skin Integrity Working Group for the Single Digital Patient Record. Scientific awards & honours: Federal Minister’s Award for Nursing Trailblazer 2025 European Pressure Ulcer Advisory Panel Early Investigator Award 2024 NSW Premier’s Award – Highest Quality Healthcare 2024 (Wound Care Command Centre) University of Sydney Alumni Graduate Medal for Research Excellence 2020 Rita & John Cornforth Medal for Research Excellence NSW Health Nursing & Midwifery Excellence in Innovation Award 2019 Grants & funding leadership: Chief Investigator on six competitively funded Q1 grants since 2019; Lead CI on four. 2025 FMH Start-up Scheme; 2024 NHMRC Partnership Project “ENABLE” (digital wound model of care); 2023 MRFF “VATICAN”; 2022 MRFF Rapid Applied Research Translation; 2019 TRGS “IMBED”. Teaching & supervision: She currently supervises two HDR students investigating digital wound-care models and virtual care in aged settings, and leads coursework development for a flexible APAC wound-care program targeting undergraduate, postgraduate and professional-development sectors.

• Secure Software Systems
• Cyber Security
• Cloud Computing
• +۵ مورد دیگر

Professor Ali Babar is a faculty member in the School of Computer and Mathematical Sciences at the University of Adelaide, part of the Faculty of Sciences, Engineering and Technology. He holds the academic rank of Professor and leads research in secure software systems, cyber security, and emerging technologies like cloud computing and IoT. Research focuses include engineering secure software systems, applying AI/ML for security, and empirical methods in software engineering. His work has resulted in over 320 peer-reviewed publications (h-index 66) and contributions to high-impact projects like the Cyber Security Cooperative Research Centre (CSCRC), a A$140M initiative. Collaborations span industry/government partners such as DST Group, ActewAGL, and Cisco. Awards include the 2014 Most Influential Paper Award at the Australasian Software Engineering Conference. His research addresses critical areas like secure microservices, ML model decay mitigation, and privacy engineering practices. Current themes include cyber security as a service and platform architectures for distributed systems. Active in supervising PhD and Master's students and participates in interdisciplinary initiatives like the Oceania Cyber Security Centre and Australian Cyber Collaboration Centre.

Xuyun Zhangمشاهده پروفایل

دانشیار

• Scalable Machine Learning
• Big Data Privacy
• Cyber Security
• +۵ مورد دیگر

Dr. Xuyun Zhang is an Associate Professor at the School of Computing, Macquarie University, Australia. He holds a PhD from University of Technology Sydney (2014), and Master's/Bachelor's degrees from Nanjing University (China). His research focuses on scalable machine learning, big data privacy, cyber security, edge computing, and IoT. He has led 11 research projects including Next-Gen Banking (2024-2028) and Scalable Document Intelligence (2022-2027). His work spans secure AI, privacy-preserving techniques, and edge-cloud collaboration. He has received awards such as the Chancellor's Best PhD Thesis (2015) and Early-Career Research Excellence (2019). His recent publications address areas like metaverse service offloading, hypergraph trust prediction, and federated learning frameworks. He actively organizes conferences like the Australasian Information Security Conference (2017) and chairs industry-research initiatives in cloud computing and mobile networking. Education: PhD (UTS, 2014), MEng (Nanjing University, 2011), BSc (Nanjing University, 2008). Teaching includes Machine Learning in Cybersecurity, Data Science, and Software Engineering. Key research contributions include privacy-preserving publishing, edge computing offloading methods, and blockchain-based secure access management. His projects often integrate AI with cloud-edge systems to address real-world challenges in finance, healthcare, and smart manufacturing.

• Intelligent Transportation Systems
• Vehicular Cyber-Physical Systems
• Traffic Flow Modeling
• +۳ مورد دیگر

Dongyao Jia is a Senior Research Fellow at the School of Civil Engineering, The University of Queensland. His research focuses on intelligent transportation systems, vehicular cyber-physical systems, and traffic flow modeling, with applications in energy harvesting, car-following model calibration, and vehicle-to-everything communication. Research Themes: Traffic flow prediction, eco-driving optimization, vehicular networks, and cyber-physical system design Key Collaborations: Working with researchers in transportation engineering, computer science, and energy systems Recent publications highlight his work in integrating deep learning with traffic dynamics for acoustic energy harvesting and developing adaptive frameworks for car-following models. His studies on multi-agent reinforcement learning for C-V2X networks and heterogeneous platooning communication demonstrate technical depth across transportation and computer science disciplines. While no specific awards are mentioned in the text, his extensive publication record across high-impact journals like IEEE Transactions on Intelligent Transportation Systems and Transportation Research Part C indicates significant scholarly contributions. Technical Expertise: V2X communication protocols, traffic simulation platforms, machine learning integration for transportation Application Areas: Urban traffic management, sustainable mobility systems, vehicular safety networks

Peng Chengمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Internet of Things (IoT)
• Wireless Communications
• +۵ مورد دیگر

Dr. Peng Cheng is a Senior Lecturer and PhD advisor in the Department of Computer Science and Information Technology at La Trobe University, Australia. He is also an Honorary Senior Lecturer at the University of Sydney. His research focuses on AI-driven IoT, wireless communications, and edge computing. He leads the Cisco-LTU Research Centre for AI and IoT and has secured over $1.3M in ARC grants. Notable contributions include pioneering 'wireless AI' research and developing graph-based deep reinforcement learning algorithms for dynamic resource allocation in 6G networks. His work bridges IoT with AI, addressing challenges in edge computing, network optimization, and sensing technologies. Current projects involve WiFi sensing for healthcare, satellite communications, and energy-efficient 5G/6G systems. Education: PhD in Communication and Information Systems from Shanghai Jiao Tong University. Prior roles include Postdoctoral Research Scientist at CSIRO (2014–2017) and ARC DECRA Fellow at the University of Sydney (2017–2020). Awards: ARC DECRA Fellowship (2020–2022) Teaching: Machine Learning, Data Communications, and Satellite Communications Labs: Cisco-LTU AIoT Centre, US-Cisco Collaboration Network

• Diabetic Foot Care
• Clinical Research
• Rehabilitation Medicine
• +۳ مورد دیگر

Dr. Jaap van Netten is an Adjunct Professor at Queensland University of Technology (QUT), School of Public Health & Social Work. He holds dual roles as Senior Research Fellow at QUT and Scientific Director of Diabetic Foot Australia. Specializing in clinical research on foot problems, particularly in diabetes, he transitioned from the Netherlands to Australia in 2016 to strengthen research-to-clinical practice links. His research focuses on diabetic foot care, offloading treatments, patient adherence, and global epidemiology of foot ulcers and amputations. Education: PhD in rehabilitation medicine from University Medical Center Groningen. Professional roles include secretary of the International Working Group on the Diabetic Foot (IWGDF) Editorial Board and its Prevention Working Group, contributing to international consensus guidelines. He has supervised over 50 students in the Netherlands and taught courses on evidence-based medicine, clinical communication, and footwear development. Research interests span biomechanics, adherence to offloading therapies, cost-effectiveness of care, and innovative monitoring technologies like the MyFootCare app. His work addresses prevention, treatment, and global trends in diabetic foot disease. Active in interdisciplinary collaborations, he leads projects on risk assessment, motivational interviewing for healthcare practitioners, and telemedicine applications. Advising: Supervised projects in three research lines at ZGT Hospital Group’s diabetic foot team. Grants and funding support his work in clinical trials and population-level analyses. Labs/teams include ZGT’s Diabetic Foot team, QUT’s research groups, and international collaborations through IWGDF.

Neda Aboutorabمشاهده پروفایل

دانشیار

• Network Coding
• Wireless Communications
• Physical-Layer Security
• +۸ مورد دیگر

Associate Professor Neda Aboutorab is affiliated with the University of New South Wales (UNSW) Canberra, where she holds the position of Deputy Head of School at the School of Engineering and Technology. She completed her PhD in Electrical Engineering at the University of Sydney in 2012 and served as a Postdoctoral Research Fellow at the Australian National University from 2012 to 2015 before joining UNSW. Her research focuses on network coding, wireless communications, physical-layer security, industrial IoT, fog computing, and machine learning applications in networking, with additional contributions to information theory and adaptive modulation. PhD: Electrical Engineering, University of Sydney (2012) Her research interests encompass a wide array of topics including secure network coding, distributed storage systems, and the integration of machine learning into communication networks. She explores theoretical foundations of coding schemes alongside practical applications such as energy-efficient offloading in fog radio access networks and intrusion detection in industrial IoT environments. Her work often bridges mathematical rigor with real-world system optimization, addressing challenges in wireless communication reliability and security. In publication trends, her recent work emphasizes physical-layer security enhancements through jamming techniques and explores the boundaries of linear/nonlinear coding in index coding problems. She also investigates fog computing architectures and cybersecurity solutions for industrial IoT, highlighting a shift toward practical machine learning-driven systems. While no scientific awards are explicitly listed, her contributions to network coding and wireless security are notable within her field. Her advising and grants narrative remains unspecified in the provided information, though her role as Deputy Head of School suggests active involvement in academic leadership and research coordination. No dedicated lab or team affiliations are mentioned beyond her institutional roles.

• Wireless Communications (5G/6G)
• AI/Machine Learning Applications
• Cyber Security and Privacy
• +۹ مورد دیگر

Dr. Diep N. Nguyen is an Associate Professor and Associate Dean (Teaching & Learning) at the University of Technology Sydney (UTS), leading the Agile Communications and Computing Group within the Faculty of Engineering and Information Technology. He holds adjunct positions at universities in the US, Vietnam, and Japan. His research focuses on wireless communications (5G/6G), AI-driven networking, cybersecurity, and edge computing, with over 200 publications and $7M in grants from NSF, ARC, and industry partners. He has supervised 15 PhD students, many now in senior academic and industry roles globally. Key roles include Director of Transnational Education, co-founder of Food Agility CRC, and leadership in international initiatives like APEC DARE. Education: Ph.D. and M.E. in Electrical and Computer Engineering from The University of Arizona and UC San Diego, respectively. Professional service includes editorial roles for IEEE Transactions and conference leadership (e.g., IEEE VTC, INFOCOM). Awards include UTS Research Excellence Awards (2021, 2024), DECRA (2015), and industry recognitions like the 2024 iAward and IoT Impact Award. Research emphasizes AI applications in communications, cybersecurity for Industry 4.0, and 6G security. Notable projects include Australia-Vietnam 5G/6G Centre ($2.1M) and DFAT-funded initiatives for disaster management. Books authored include Deep Reinforcement Learning for Wireless Communications and Generative AI for Communications Systems . Teaching focuses on integrating research into courses like Cloud Security and Industry 4.0 Technologies. His pedagogy emphasizes self-directed learning through authentic research tasks, supported by real-time feedback channels.

Sajib Mistryمشاهده پروفایل

مدرس ارشد

• Secure Machine Learning
• Cloud/Edge Computing
• IoT
• +۶ مورد دیگر

Dr. Sajib Mistry is a Senior Lecturer and Director of Research at Curtin University’s School of Electrical Engineering, Computing, and Mathematical Sciences (EECMS), part of the Faculty of Science and Engineering. He holds positions as Associate Director at Curtin’s High-Performance Intelligent Systems (HPIS) lab and Vice Chair of the IEEE WA Section. His research focuses on secure machine learning, edge/cloud computing, IoT, and distributed systems, with specialties in economic models for Infrastructure-as-a-Service (IaaS) composition and autonomous systems. Education: PhD in Computer Science (RMIT University), Postdoctoral Research Fellowship (University of Sydney). Research Interests : Service computing, cloud/edge computing, IoT, AR/VR, machine learning, distributed systems, software engineering, and big data analysis. His work emphasizes practical applications in defense, healthcare, and smart infrastructure. Grants (selected): Over $1.3M in funding from the Department of Defence, Australian Academy of Science, and WA government programs. Projects include combat system architectures, microservices management for legacy systems, and geo-spatial transfer learning for misinformation detection. 2023-2025: Combat System Architecture (RECSA), $1.5M 2022-2024: Micro-Services Management Platform, $418K Awards : Best Paper Award (ICSOC 2016), Distinguished Early Career Researcher nominee (2022). Labs/Teams : Leads research at Curtin HPIS, collaborating on edge analytics, WebAR platforms, and autonomous vehicle coordination. Active in IEEE and ACM committees, including roles as Publication Chair (ICSOC 2020) and Program Committee member for multiple conferences.

Mahbuba Afrinمشاهده پروفایل

مدرس

• Machine Learning
• Edge Intelligence
• Networked Robotics
• +۲ مورد دیگر

Dr. Mahbuba Afrin is a Lecturer at Curtin University's School of Elec Eng, Comp and Math Sci (EECMS), with affiliations to the Faculty of Science and Engineering. She holds a Ph.D. from Swinburne University of Technology, an M.S. and B.S. in Computer Science and Engineering from University of Dhaka. Her research specializes in Internet of Things-enabled Cyber-Physical Systems, Networked Robotics, and development of efficient learning models for intelligent systems. Research focuses include resource allocation optimization, autonomous network management, and edge intelligence applications in agricultural technology, fraud detection, and livestock management. Current projects explore UAV-based solutions for bushfire detection and real-time robotic task allocation using deep reinforcement learning. Afrin has secured multiple grants including the Strong and Resilient Communities Grant (AUD $360,000), Innovation Challenge for Generative AI (AUD $50,000), and three Pawsey Supercomputing grants. Her 15 most recent publications (2018-2025) demonstrate consistent focus on machine learning applications in networked systems, spanning UAV coordination, blockchain security, cloud robotics, and agricultural technology. Awards include the 2024 WiTWA Tech Rising Star Award in STEM Academia, People's Choice Award at Pawsey Supercomputing Project Showcase (2022-23), and Vice-Chancellor's Postdoctoral Fellowship (2021). She teaches courses including Data Structures and Algorithms, Fundamentals of Programming, and Computer Science projects.

• Computer Networks
• Wireless Sensor Networks
• Network Protocols
• +۴ مورد دیگر

Terry Koziniec is a Lecturer in the School of Information Technology within the College of Science, Technology, Engineering and Mathematics at Murdoch University. His research focuses on computer networking, particularly wireless sensor networks, network protocols, and high-speed network interface design. Research Areas: Includes performance analysis of LoRaWAN and HF wireless networks; reliability measurement of enterprise WiFi; design of scalable network interfaces for 100Gbps networking; and traffic characterization in modern enterprise environments. His work bridges theoretical networking concepts with practical implementation challenges. Educational Research: Investigates student perceptions of flipped learning models, contributing to pedagogical innovation in IT education. His extensive publication record demonstrates expertise across networking hardware, wireless technologies, and performance optimization. Publications: Cover a wide spectrum from fundamental network protocols (TCP/UDP at 100Gbps) to specialized applications (ionospheric propagation for HF sensors) and educational methods, reflecting a versatile research profile focused on advancing network reliability, speed, and efficiency.

Frank den Hartogمشاهده پروفایل

استاد

• Complex Wireless Networked Systems
• Internet of Things (IoT)
• Cyber-Physical Systems
• +۴ مورد دیگر

Frank den Hartog is a Professor at the University of Canberra, holding the Cisco Research Chair in Critical Infrastructure, and an Adjunct Fellow at UNSW Canberra's School of Systems & Computing. His research focuses on complex wireless networked systems, IoT, and Cyber-Physical Systems. Previously, he served as Senior Scientist at TNO (2003–2016) and worked at KPN, pioneering home networking research. He holds a PhD in Physics from Leiden University and an MSc from Eindhoven University of Technology. Dr. den Hartog has led numerous industry-academic projects, including European Horizon 2020 initiatives, and contributed to 73 patents and 67 standardization papers. He actively participates in IEEE and has supervised 7 Master’s/Honours and 2 PhD students. His work has been recognized with academic and industry awards, and he co-authored over 90 peer-reviewed articles. Key affiliations: University of Canberra (Professor), UNSW Canberra (Adjunct Fellow) Education: PhD in Physics (Leiden University), MSc in Engineering (Eindhoven University of Technology) Research Interests: His work spans IoT security, 6G networking, blockchain in IoT, and smart home systems. He emphasizes standardization and interdisciplinary collaboration, addressing challenges in heterogeneous networks and cyber-physical integration. Publications: His recent work explores AI-driven smart home traffic analysis, 6G spectrum sharing, and IoT trust models. These contributions highlight advancements in network security, edge computing, and decentralized systems. Awards: Multiple unspecified academic and industry accolades for innovations in home networking and IoT. Grants/Leadership: Led EU-funded projects, chaired the HGI Technical Working Group (2012–2016), and reviewed journals and conferences. He contributes to the Home Gateway Initiative and collaborates with industry partners, fostering practical applications of theoretical research in telecommunications and cybersecurity.