جستجوی استاد راهنمای دانشگاهی

• Quantum Computation
• Quantum Programming
• Formal Methods
• +۶ مورد دیگر

Professor Mingsheng Ying (University of Technology Sydney) is a Distinguished Professor specializing in quantum programming , quantum verification , and the foundations of artificial intelligence . He leads the Centre for Quantum Software and Information and co-founded the Quantum Lab . His work bridges quantum computation with formal methods and reasoning under uncertainty. Education : Mathematics, Fuzhou Teachers College (1981) Research Interests His research spans: Quantum programming languages and verification techniques Model checking quantum systems and cryptographic protocols Quantum machine learning robustness Entanglement theory and distributed quantum computation Recent Publications Key contributions include: Quantum error correction verification frameworks Quantum register machine architecture Hamiltonian simulation parallelization Symbolic execution for quantum debugging Robustness tools like VeriQR Awards & Editorial Roles NSF China Distinguished Young Scholar Award (1997) China National Science Award (2008) Co-Editor-in-Chief, ACM Transactions on Quantum Computing Vice President, International Fuzzy Systems Association (2005) Leadership & Grants He oversees 14 active grants (2010–2029) from: Australian Research Council (ARC Discovery Projects) National Natural Science Foundation of China Sydney Quantum Academy Baidu Contract Research His grants fund research in quantum program verification, entanglement classification, and distributed quantum protocols.

Kefeng Zhangمشاهده پروفایل

مدرس ارشد

• Green technologies for urban stormwater management
• Stormwater quality monitoring and risk assessment
• Water recycling
• +۵ مورد دیگر

Dr. Kefeng Zhang is a Senior Lecturer at the Water Research Centre , UNSW Sydney, specializing in nature-based solutions (NBS) for urban water treatment. His work focuses on stormwater management , greywater recycling , and Water Sensitive Urban Design (WSUD) to address pollution and climate resilience. He serves as Associate Editor for Water Research and Managing Editor for Blue-Green Systems . PhD (2015, Monash University) Master of Science in Engineering (2011, Southeast University) Bachelor of Science in Engineering (2008, Southeast University) His research integrates bioretention systems , green walls , and real-time control technologies to enhance water quality and mitigate urban flood risks. Key subfields include pollutant removal mechanisms , emerging contaminants , and interdisciplinary urban water planning . Recent publications analyze microplastics transport in green infrastructure, machine learning for water treatment , and climate-resilient stormwater frameworks , reflecting his focus on environmental engineering and hydrological modeling . Discovery Early Career Researcher Award (DECRA) Eric Laurenson Medal for urban water research Outstanding reviewing contributions to Water Research and Science of The Total Environment Postgraduate Publication Award (Monash University) Dr. Zhang supervises PhD and MPhil students in projects like Nitrogen removal in biofiltration and Green wall technology for microplastics removal . His grants include ARC Discovery Projects and Qatar National Research Fund collaborations.

• Vision Science
• Ocular Imaging
• Glaucoma Research
• +۷ مورد دیگر

Mojtaba Golzan is an Associate Professor of Vision Science and currently serves as Deputy Head of School (Research) at the Graduate School of Health, University of Technology Sydney. His academic journey includes a PhD from Macquarie University, postdoctoral training as an Alzheimer's Australia Fellow at Macquarie University, and an Endeavour Research Fellowship at the University of California, San Diego. Dr. Golzan's research focuses on developing new biomarkers for early identification of ocular and neurological diseases, with specific expertise in glaucoma, UV-related eye damage, and abnormal brain pressure. His interdisciplinary approach integrates image analysis, machine learning, artificial intelligence, photonics, and laboratory-based in-vitro assays to create innovative diagnostic solutions. He leads a research group that has been continuously supported by competitive funding from the National Health and Medical Research Council, Australian Research Council, and Google. His most notable innovation is A-Eye, an AI-powered technology package that enables non-invasive assessment of intracranial pressure through retinal imaging, which won first prize in the UTS Research Translation Competition. His publication record shows a strong focus on applying AI to ocular imaging, with recent work spanning Alzheimer's disease detection using retinal biomarkers, spontaneous retinal venous pulsations analysis, and non-invasive intracranial pressure measurement. First prize in the UTS Research Translation Competition for A-Eye NHMRC-ARC dementia fellowship (2016) Postdoctoral Fellowship (2013) Dr. Golzan actively supervises research students and coordinates Research Project subjects in the Orthoptics discipline. His research program has secured significant funding including grants from NHMRC Ideas Grants, Digital Health CRC, Australia's Economic Accelerator Ignite Grant, and Health Research Council of New Zealand. His work bridges vision science, digital health technology, and clinical applications, positioning him as a leading translational researcher at the intersection of these fields.

• Software Engineering
• Data Engineering and Data Science
• Artificial Intelligence
• +۴ مورد دیگر

Assoc Prof Caslon Chua is an Associate Professor and Department Chair of Computing Technologies at the School of Science, Computing and Emerging Technologies, Swinburne University. He specializes in software engineering, data science, artificial intelligence, and human-centered computing. His research focuses on federated learning, cybersecurity, medical imaging, education technology, and sustainable energy systems. Prof Chua has led numerous grants, including projects on CTF-based cybersecurity platforms, smart energy systems, and AI-driven healthcare solutions. He actively supervises doctoral and master’s students in areas like AI ethics, medical diagnostics, and smart energy. His grants span collaborations with organizations like the Australian Council of Deans of ICT, Victorian Chamber of Commerce, and Commonwealth Scientific and Industrial Research Organisation (CSIRO). Recent grants include developing cybersecurity platforms for education and improving evacuation modeling in the Philippines. Prof Chua’s work emphasizes ethical AI integration in education and healthcare, addressing challenges like data imbalance and model drift in federated learning systems. He has published over 80 papers in top journals and conferences, focusing on edge-assisted learning systems, colorectal polyp detection, and AI-driven insurance predictions. His teaching activities include courses on AI ethics, cybersecurity, and data analytics. Prof Chua’s contributions bridge academia and industry, addressing real-world challenges in computing and emerging technologies.

• Data Analysis
• Recommendation System
• Responsible AI
• +۶ مورد دیگر

Dr. Angela Huo is an Associate Professor at the School of Computer Science within the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS). She holds multiple leadership roles including Deputy Director of Transnational Education for the Faculty of Engineering and IT, Responsible Academic Officer for Teaching and Learning of the School of Computer Science, Course Director for the Bachelor of Computing Science (Honours) program, and site coordinator for the South Pacific Programming Contests region of the International Collegiate Programming Contest (ICPC). Dr. Huo's research spans several key areas in computer science, with a primary focus on Data Analysis, Recommendation Systems, and Responsible AI. She specializes in utilizing AI and data analysis techniques to improve the efficiency and security of modern software systems. Her recent research interests include recommendation systems, anomaly detection, and privacy-preserving through data mining and deep learning. She has made significant contributions across multiple domains including multimodal learning, federated learning, causal inference, and human behavior recognition. Dr. Huo's publication record demonstrates a strong trajectory in cutting-edge AI research, with recent work focusing on conditional diffusion models for trajectory prediction, hybrid recommendation systems, causal learning to mitigate echo chambers, and adaptive waste detection. Her research shows a consistent pattern of addressing real-world challenges through innovative AI approaches, often combining multiple techniques to achieve superior results. Dr. Huo has secured research funding for projects including "Churn prediction scoping study" and "Army sovereign Software-Defined Battlefield Network." She has been actively involved in teaching and curriculum development, having created Industrial sub-majors for Google, AWS and iOS, Information Security sub-major, Data Analytics for Cybersecurity Microcredentials, and Cybersecurity and Privacy major since 2019. She has taught programming and cybersecurity management courses at the undergraduate level and served as HDR Coordinator of the School of Computer Science during 2021-2022.

• Cybersecurity
• Blockchain
• Artificial Intelligence
• +۳ مورد دیگر

Yang Xiang is a Full Professor and Dean of the Digital Research & Innovation Capability Platform at Swinburne University of Technology. He holds a PhD in Computer Science from Deakin University and has over 20 years of experience in cybersecurity research, focusing on network security, blockchain, and AI. As an IEEE Fellow, he serves as Editor-in-Chief for SpringerBriefs on Cyber Security Systems and Networks and Associate Editor for multiple IEEE journals including Transactions on Dependable and Secure Computing. His research integrates AI with cybersecurity to address vulnerabilities in distributed systems and IoT. Key areas include federated learning privacy, blockchain bridge security, and intrusion detection using graph neural networks. He leads Swinburne's blockchain initiatives and has published over 300 papers. Professor Xiang has received the IEEE Fellowship for contributions to cybersecurity. He actively supervises doctoral students in areas like fuzzing tools, 6G security, and automated software testing. His grants include projects on AI-driven manufacturing cybersecurity and distributed energy optimization.

Felipe Trevizanمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Operations Research
• Machine Learning
• +۳ مورد دیگر

Dr. Felipe Trevizan is a Senior Lecturer in the School of Computing at the Australian National University (ANU), specializing in Artificial Intelligence, Operations Research, and Machine Learning. His research focuses on automated planning, scheduling, and heuristic search, particularly in uncertain environments. Previously, he was a Senior Research Scientist at NICTA/Data61 and earned his Ph.D. in Machine Learning from Carnegie Mellon University under Prof. Manuela Veloso. Education: Ph.D. in Machine Learning, Carnegie Mellon University (2013) M.Sc. in Machine Learning, Carnegie Mellon University (2010) M.Sc. in Computer Science, University of São Paulo (2006) B.Sc. in Computer Science, University of São Paulo (2004) Research Interests: Felipe’s work bridges AI and Operations Research, emphasizing automated planning under uncertainty , heuristic search algorithms , and integration of machine learning with planning systems . His contributions include novel methods like short-sighted planning and occupation measure heuristics, as well as advancements in multi-objective stochastic planning and constraint generation techniques. Awards: 2016 Kikuchi-Karlaftis Best Paper Award (Transport Research Board) Best Paper Awards at ICAPS 2016 and 2017 Advising & Grants: Felipe has mentored over 20 students, including Ph.D. candidates Mingyu Hao and Johannes Schmalz, and Honours students Ryan Wang and Dillon Chen. His research is supported by grants focusing on planning under uncertainty, optimization in transportation, and machine learning integration with classical planning. Key Contributions: Recent work includes partial-space search for learned heuristics, CG-iLAO* for stochastic shortest paths, and GOOSE , a domain-independent heuristic learning framework. These innovations aim to enhance planning efficiency and adaptability in complex domains.

Hudyjaya Siswoyo Joمشاهده پروفایل

دانشیار

• Robotics
• Mechatronics
• Industrial Automation
• +۵ مورد دیگر

Associate Professor Hudyjaya Siswoyo Jo is a faculty member at the Faculty of Engineering, Computing and Science at Swinburne University of Technology Sarawak Campus. He holds a BEng (Hons) and PhD from Swinburne University of Technology and is a Chartered Engineer (Engineering Council UK) with professional memberships in the Institution of Mechanical Engineers and the Institute of Electrical and Electronic Engineers. His research expertise spans multiple domains of robotics and automation, with particular focus on: Mechatronics System Design Industrial & Building Automation Industrial Internet of Things Human Machine Interaction Agriculture Mechanisation Professor Siswoyo Jo has successfully completed numerous manufacturing and automation projects focusing on Industry 4.0 implementation for Small-Medium Enterprises in Sarawak. He has served as a technical consultant for significant projects including the Borneo Cultures Museum, the second largest museum in Southeast Asia. His research has resulted in multiple patents, including "Vehicle for Collecting and Transporting System and Method Thereof" (Australia, 2020) and "Autonomous Harvester" (Malaysia, 2021). His scientific achievements include: Gold Award and IET Best Automation and Control Concept Special Award (2020) Swinburne Vice-Chancellor Community Engagement Award (2019) Swinburne Vice-Chancellor Industry Engagement Award (2018) Best Paper Award at the International Conference on Robotics and Mechanical Engineering (2016) Professor Siswoyo Jo has secured multiple research grants including SDEC TRG Grants as both Principle Investigator and Co-Investigator for projects related to UAV-based parking enforcement, AGV-based IoT solutions, and smart waste collection systems. He actively supervises postgraduate students and welcomes research higher degree candidates in his areas of expertise. His laboratory work focuses on practical applications of robotics and automation technologies in industrial and community settings, with strong industry partnerships that provide students with real-world project experience.

Sami Azamمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Artificial Intelligence
• Deep Learning
• +۵ مورد دیگر

Dr. Sami Azam is a Senior Lecturer and Undergraduate Course Coordinator at Charles Darwin University's Faculty of Science and Technology. He holds a PhD in Biomedical Engineering, focusing on binaural processing in the human brain. His research spans machine learning, artificial intelligence, deep learning, advanced signal processing, and medical image analysis, with applications in biosignal classification (e.g., EEG, ECG) and cybersecurity for IoT devices. Dr. Azam is a key member of the Biomedical Engineering and Health Informatics research group and actively engages in grant writing, conference presentations, and professional organizations such as IEEE and ACS. His work emphasizes interdisciplinary projects, including automated disease diagnosis (e.g., skin cancer, retinal diseases), smart grid security, and privacy-preserving data analysis. He has secured numerous grants and developed frameworks like PBDINEHR for secure electronic health records. Dr. Azam’s contributions bridge biomedical engineering and computational methods, addressing global health challenges through innovative AI applications.

• Additive Manufacturing
• Composite Materials
• Materials Engineering
• +۷ مورد دیگر

Assoc. Prof. Mostafa Nikzad is an Associate Professor at Swinburne University of Technology’s School of Engineering, specializing in mechanical and product design engineering. His research focuses on composite materials, additive manufacturing, and sustainable materials science, with industry collaborations including Tesla, Ford, and CSIRO. He holds a PhD in additive manufacturing of metal/polymer composites and an MSc in electro-physical deposition processes. Education: PhD: Additive Manufacturing of Metal/Polymer Composites MSc: Electro-Physical Deposition Processes Research Interests: Additive Manufacturing of Composites Recycling and Sustainable Materials Structural Health Monitoring Biobased Polymers and Vitrimers Advanced Manufacturing Techniques Grants & Industry Projects: Recycled Plastic ROBOVOID Construction Solution (Federal Grant) Automating Shower Base Manufacturing using Cobots (Industry Contract) Composite Spacers from Recycled Plastics (Sustainability Victoria) Awards: ANTEC 2021 Awards Excellence in Teaching Award (2019) TESLA Excellence in Research Award (2018) Advising & Labs: Supervised over 20 PhD/Master’s projects on topics like 3D-printed composites, bio-based materials, and structural health monitoring. Collaborates with labs focused on advanced manufacturing, composites processing, and sustainable materials innovation.

Andrew Caseyمشاهده پروفایل

دانشیار

• Astrophysics
• Stellar Astrophysics
• Data Analysis
• +۳ مورد دیگر

Associate Professor Andrew Casey is a computational astrophysicist at Monash University's School of Physics and Astronomy, specializing in data-driven methods applied to astrophysical problems. He holds a PhD from Australian National University (ANU), with postdoctoral research at the University of Cambridge as a King's College Senior Member. His work bridges astrophysics, statistics, and machine learning, focusing on stellar astrophysics, Bayesian inference, and large-scale surveys like Gaia and GALAH. He leads projects on stellar interiors, galactic evolution, and unresolved binary systems. Casey has received awards including the Young Tall Poppy Award and the Australian Prime Minister's Endeavour Award. He actively mentors PhD students in data analysis and computational methods. Education: PhD in Astronomy & Astrophysics (ANU), Visiting Graduate Student at MIT (via Endeavour Award). Research interests include: computational data analysis, stellar astrophysics, Bayesian statistics, machine learning applications in astronomy, and algorithm optimization. Notable projects include GaiaUnlimited (studying Milky Way disc structure) and GALAH surveys (chemical tagging of stars). Recent articles focus on topics like Gaia data analysis, exoplanet detection via astrometry, and models for M dwarfs. His work often emphasizes interdisciplinary approaches, combining physics-based models with AI-driven techniques. Awards: Young Tall Poppy Award (2018), Fresh Science (2018), Senior Member (2015), Australian Prime Minister's Endeavour Award (2011), and InnovationACT Prize (2011). Advising and grants: Accepting PhD students; leads ARC-funded projects such as the Discovery Early Career Researcher Award. Projects include Gaia survey analysis, star formation studies, and binary star detection. Labs/Teams: Involved with the Monash Astrophysics Group and collaborates internationally on surveys like Gaia and SDSS-V.

• Community Development
• Coastal Resource Management
• Fisheries Governance
• +۳ مورد دیگر

Dirk Steenbergen is an Associate Professor and Principal Fellow at the Australian National Centre for Ocean Resources and Security (ANCORS) within the University of Wollongong's Faculty of Business and Law. He holds an adjunct role as Research Fellow at Charles Darwin University. His academic journey includes a D.Phil. in Community Development, Governance and Conservation from Murdoch University (2013) and a Master’s in Social Science from Wageningen University (2006). His research focuses on community-based fisheries management (CBFM) in the Asia-Pacific, particularly scaling CBFM in Pacific Island nations like Kiribati, Solomon Islands, and Vanuatu. He leads the Pathways-2 Project, emphasizing participatory approaches, policy integration, and gender inclusion. Dirk’s work spans rural development, coastal livelihoods, and governance, with expertise in participatory methodologies across diverse cultural contexts. Recent projects leverage technology like AI and deep learning to enhance fisheries management. His teaching interests include environmental anthropology, coastal governance, and common-pool resource management. Current supervision includes a doctoral project on technology-driven coastal fisheries assessment in the Pacific. Dirk actively contributes to academic communities, serving on the Too Big To Ignore network and reviewing for journals like AMBIO . His research bridges policy, practice, and community needs, addressing challenges such as post-disaster resilience, social inclusion, and marine resource equity.

Fabio Zambettaمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Reinforcement Learning
• +۶ مورد دیگر

Professor Fabio Zambetta is Deputy Dean of Engagement at RMIT University's School of Computing Technologies. An internationally recognized research leader in AR/VR, games technology, and real-time simulation, he focuses on industry partnerships and cross-disciplinary practice. His research interests include artificial intelligence in games, reinforcement learning, mixed reality systems, and real-time simulation. He has led major projects with industry partners including Microsoft, GitHub, and Village Roadshow. Professor Zambetta's publications explore multimodal interfaces, cognitive load measurement in games, brain-computer integration, and assistive technologies. His recent work examines human-robot teaming, sports technology, and neuroadaptive systems. He has received the Best Paper Award at CHI 2024 for research on brain-to-brain interfaces.

Annie Liangمشاهده پروفایل

مدرس ارشد

• Air Traffic Management
• Trajectory-Based Operations
• Machine Learning
• +۷ مورد دیگر

Dr. Annie Liang is a Senior Lecturer in the School of Engineering at RMIT University, specializing in Air Traffic Management (ATM), Trajectory-Based Operations (TBO), machine learning, and big data analytics with a focus on autonomous systems and Advanced Air Mobility (AAM). Her work addresses challenges in urban air mobility, sustainable aviation, and airspace optimization. She holds licenses in air traffic control and is an active member of professional societies like the Royal Aeronautical Society and AIAA/IEEE. Research interests include intelligent air traffic systems, unmanned traffic management, and safety-centered AAM. Her UN Sustainable Development Goals alignment includes Industry, Innovation and Infrastructure; Sustainable Cities and Communities; and Climate Action. Teaching focuses on aviation law, avionics, and sustainable aviation practices. Key projects involve trajectory prediction, wind disturbance analysis for Urban Air Mobility, and drone fleet management for agriculture. She supervises Master’s and PhD students in topics like air traffic flow optimization and autonomous systems. Collaborates with labs such as Intelligent Automation & Autonomy for Aerospace and Information in Society.

• Construction Technology
• Sustainable Building
• Artificial Intelligence in Construction
• +۶ مورد دیگر

Dr. Lei Hou is an Associate Professor in the School of Engineering at RMIT University. His research focuses on integrating advanced technologies like Building Information Modelling (BIM), Augmented Reality (AR), Virtual Reality (VR), and Artificial Intelligence (AI) into construction and civil engineering. He leads projects on sustainable infrastructure, construction waste management, and worker safety through digital tools. His work emphasizes lifecycle sustainability analysis, smart asset management, and robotic automation in construction processes. Dr. Hou collaborates internationally, with a strong publication record in journals like Automation in Construction and Advanced Engineering Informatics. He actively supervises postgraduate students in topics such as BIM-based decision-making and AI-driven defect control. Teaching interests include Engineering Project Management, Virtual Reality applications, and Game Engineering. He has pioneered courses on BIM integration with emerging technologies. His research has led to innovations in UAV-based bridge inspection, eye-tracking for worker safety, and robotic waste sorting systems. Dr. Hou's contributions advance the use of digital twins for emergency management and sustainable urban development. Key Research Themes: Smart Construction, Sustainability, AI & Robotics Recent Projects: BIM for Green Retrofit, AR Safety Systems, UAV-Driven Infrastructure Monitoring Campus: City Campus, Australia