جستجوی استاد راهنمای دانشگاهی

• Information Systems Methodologies
• Artificial Intelligence
• Agent Systems
• +۸ مورد دیگر

Prof Ghassan Beydoun is a Professor and Head of Discipline (Information Systems) at the School of Computer Science, University of Technology Sydney (UTS). He leads the Information Systems discipline and is affiliated with the Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS). His research focuses on AI-driven systems, agent-based modelling, ontologies, and disaster management, with notable contributions to knowledge graphs, enterprise architecture, and IoT applications. Beydoun actively supervises Masters and PhD students in these domains. His research interests span metamodelling, agent systems, and AI applications in disaster management (e.g., flood, landslide, and earthquake risk assessment), health systems, and smart infrastructure. He has pioneered frameworks for reproducible machine learning solutions, digital identity systems, and cloud migration strategies. Beydoun’s work integrates interdisciplinary methods, such as bibliometric analysis for journal evolution and XAI for spatial hazard prediction. Recent publications highlight his expertise in AI for climate-induced hazard modelling, agent-based knowledge transfer mechanisms, and metaverse applications in education. His funded projects include AI-powered circular economy initiatives, smart beach safety systems, and health data querying frameworks. Beydoun collaborates with industry partners like CSIRO, Capsicum Business Architects, and Data Zoo, translating research into practical solutions for enterprise architecture, cybersecurity, and public health.

Kok Sheik Wongمشاهده پروفایل

استاد

• Multimedia Signal Processing
• Cybersecurity
• Data Hiding
• +۹ مورد دیگر

Kok Sheik Wong is a Professor and Deputy Head (Research) at the School of Information Technology, Monash University Malaysia. He holds a Doctor of Engineering from Shinshu University, Japan, and Master’s and Bachelor’s degrees in Computer Science and Mathematics from Utah State University, USA. His academic leadership and research excellence are central to his role at Monash. B.S. Computational Mathematics, Utah State University (2002) M.S. Computer Science, Utah State University (2006) M.S. Mathematics, Utah State University (2004) Doctor of Engineering, Shinshu University, Japan (2009) His research focuses on multimedia signal processing and cybersecurity , particularly in data hiding , reversible data hiding , coverless steganography , and multimedia encryption . He is also expanding into digital health , applying AI to mental health in workplace environments. His work aligns with UN SDGs, particularly in health and education. The recent publication trends show a strong emphasis on reversible data hiding , image watermarking , and AI-driven health applications . His interdisciplinary work spans computer science, engineering, and public health, with increasing focus on real-world impact through EU and national grants. He has received several honors, including: Academic of Science Malaysia - Young Scientist Network (2020) Best Paper Award, IWDW 2019 ITEX 2021 Gold Medal for BAITRADAR School of IT Excellence in Research Award (2022) Dr. Wong actively supervises PhD students and leads major research projects, including the EU-funded WAge project. He has served as an associate editor for IEEE Signal Processing Letters and the Journal of Information Security and Applications, and is a member of IEEE IFS and APSIPA technical committees. His grants reflect strong external collaboration and funding in cybersecurity and digital health. He is involved in key research labs and teams through Monash University and international consortia, particularly in the areas of multimedia security and digital health innovation. His leadership in the WAge project connects him with European and Asia-Pacific research networks, enhancing global impact.

Siqi Maمشاهده پروفایل

مدرس ارشد

• Automated Vulnerability Detection and Repair
• Mobile Security
• IoT Security
• +۴ مورد دیگر

Dr. Siqi Ma is a Senior Lecturer at the UNSW Institute for Cyber Security (IFCYBER) within the School of Systems & Computing at the University of New South Wales (UNSW). He previously served as a Lecturer at the University of Queensland's School of Information Technology and Electrical Engineering (ITEE). He holds a Ph.D. in Information Systems from Singapore Management University (2018) and was a Postdoctoral Research Fellow at Data61, CSIRO. He also visited Carnegie Mellon University (CMU) in 2015. Current Role: Senior Lecturer, UNSW Institute for Cyber Security Former Role: Lecturer, University of Queensland Education: Ph.D. (Singapore Management University), Postdoc (Data61, CSIRO) His research spans automated vulnerability detection, mobile security, IoT security, network authentication, and graph-based adversarial robustness. Recent work focuses on drone configuration bugs, Android malware analysis via GNNs, federated learning privacy, and credential leakage in open-source projects. Key trends in his 2024-2025 publications include automated security analysis for embedded systems, deepfake detection in multimedia, and privacy-preserving mechanisms for distributed networks. He collaborates with institutions like Purdue University, Singapore Management University, and CSIRO Data61.

• Computational Biology
• Single-Cell RNA Sequencing
• Virology
• +۴ مورد دیگر

Fabio Zanini is an Associate Professor at the University of New South Wales (UNSW) , leading a research group focused on computational biology , single-cell approaches , and transcriptomic analysis across diseases like severe dengue , neonatal lung disease , cancer , and marine biology . He previously conducted postdoctoral research at Stanford University (2016-2019) and earned a PhD in Bioinformatics from the Max Planck Institute for Developmental Biology and the University of Tuebingen (2015). Current Affiliation: Group leader, UNSW Previous Training: Postdoc (Stanford), PhD (Max Planck/University of Tuebingen) His research spans single-cell RNA sequencing , computational virology , developmental cell biology , and bioinformatics tool development , with recent work on: Severe dengue progression (viral-host interactions, immune signatures) Lung development (endothelial cell diversity, hyperoxia-induced injury) Cancer genomics (mutant HSC clones, AZA therapy response) Marine biology (plankton transcriptomics, evolutionary analysis) Bioinformatics (HTSeq 2.0, northstar algorithm) Recent scientific awards include grants from the Chan Zuckerberg Initiative ($270,000), NIH R01 (multiple), ARC Discovery Grant , and NHMRC Ideas Grant . Notable contributions include: Northstar - Cell classification algorithm SpectralSeq - Hyperspectral-transcriptomic integration Tabula Muris - Mouse aging atlas He has supervised research into hematopoietic stem cell regulation , lung vascular development , and autophagy in viral infections , with collaborations across Stanford , University of Sydney , and Harvard .

• Spatio-temporal Statistics
• Computational Statistics
• Environmental Informatics
• +۳ مورد دیگر

Andrew Zammit Mangion is an Associate Professor at the University of Wollongong , affiliated with the School of Mathematics and Applied Statistics . His research focuses on spatio-temporal statistics, computational methods, and environmental informatics, with applications in climate science and geospatial data analysis. Education : PhD in Statistics (University of Sheffield, 2012), B.Eng. (University of Malta, 2007) Research Themes : Spatio-temporal modeling, Bayesian inversion frameworks (e.g., WOMBAT v2.S), deep learning integration, and statistical software development (e.g., FRK package) Grants & Projects : ARC DECRA Fellow (2018), Chief Investigator on ARC Discovery Project (greenhouse gases), ARC Special Research Initiative (Securing Antarctica's Environmental Future), and ARC Industrial Transformation Hub (TIDE). Collaborations : University of Bristol, University of Edinburgh, ESA CCI, NASA OCO-2 data projects Scientific Awards include the prestigious Australian Research Council Discovery Early Career Researcher Award (DECRA). His work spans Antarctic ice sheet analysis, CO2 flux inversion, and scalable spatial statistical models for environmental monitoring.

• Graph Analytics
• Graph Mining
• Graph Algorithms
• +۳ مورد دیگر

Dr. Lijun Chang is an Associate Professor in the School of Computer Science at the University of Sydney. He holds an ARC Future Fellowship (2019–2022) and an ARC DECRA Fellowship (2015–2017). Previously, he was at the University of New South Wales. His research focuses on graph analytics, mining, algorithms, and network science. He teaches courses like INFO5011 (Competitive Programming), COMP5313 (Large Scale Networks), and COMP9120 (Database Management Systems), and coaches the USYD Programming Competition Teams. Education: B.Eng. in Computer Science & Technology from Renmin University of China; PhD from the Chinese University of Hong Kong. Research highlights include scalable graph processing systems (e.g., ScaleG), densest subgraph detection, and graph similarity search. He leads projects funded by ARC grants such as 'Advanced Search of Cohesive Subgraphs in Big Graphs' (2018) and 'Directionality-Aware Cohesive Subgraph Search' (2022). His work emphasizes efficient algorithms for large-scale networks and graph databases. Awards : ARC Future Fellow, ARC DECRA Fellow Students : Yu KONG, Rashmika MATHTHAKA GAMAGE, Mouyi XU Labs/Teams : Focuses on graph algorithms and systems research, contributing to open-source tools and large-scale network analysis.

• Mathematical Logic
• Formal Methods
• Automated Reasoning
• +۴ مورد دیگر

Dr. Sasha Rubin is a Senior Lecturer and leader of the Computational Logic for AI (LOGIC-AI) group at the School of Computer Science, The University of Sydney. He holds a PhD in Mathematics and Computer Science from the University of Auckland and previously worked at the University of Naples Federico II. His research focuses on logic foundations of AI, including synthesis, planning, formal methods, and multi-agent systems. He teaches courses like Models of Computation and supervises students in topics like probabilistic systems and reinforcement learning. Research Interests: Mathematical Logic, Formal Verification, Temporal Logic Synthesis, Automated Reasoning, and Multi-Agent Systems. He has published extensively in top venues like IJCAI, AAAI, and ACM Transactions. His work includes verification of agent navigation, strategy logic, and planning under uncertain environments. Awards: Recognized as an Australian Research Field Leader in Theoretical Computer Science (2020). He serves on editorial boards for JAIR and conferences like KR, and organizes events such as the Australasian Association for Logic Conference (2024). Supervision and Grants: Current students include Ethan HIRSCHOWITZ and Kunal OSTWAL. Past supervision spans MPhil/PhD projects on probabilistic systems, ML classifier fairness, and symbolic automata. His grants include studies on logic and robots in anonymous graphs. Professional Activities: Member of EATCS, ACM, and mentor for the Sydney Summer Innovation Programme. He leads the LOGIC-AI lab and collaborates internationally, notably with Giuseppe De Giacomo at Sapienza University of Rome.

• Machine Learning
• Data Mining
• Computer Vision
• +۳ مورد دیگر

Professor Xue Li is a faculty member in the School of Electrical Engineering and Computer Science at the University of Queensland. His research focuses on machine learning, data mining, and their applications in healthcare, materials science, and computer vision. He has authored over 300 publications, including seminal works on knowledge graph completion, video quality enhancement, and alloy design using machine learning. His work bridges theoretical advancements with real-world applications, such as clinical diagnosis andTinyML systems. Key research interests include graph representation learning, medical informatics, and efficient algorithms for multimedia data. Notable contributions include developing commonsense-enhanced relation extraction models and frameworks for compressed video reconstruction. His research also addresses challenges in federated learning and privacy-preserving genomics. Prof. Li has collaborated extensively with industry and academia, contributing to projects in RFID systems, electronic nose pattern recognition, and cybersecurity. His work is published in top-tier venues like IEEE Transactions and ACM conferences. Despite no listed awards, his prolific output underscores academic impact.

Marius Portmannمشاهده پروفایل

استاد

• Cybersecurity
• Computer Networks
• Internet of Things (IoT)
• +۳ مورد دیگر

Professor Marius Portmann is the UQ-Cisco Chair of Network Security at the School of Electrical Engineering and Computer Science (EECS), University of Queensland. His expertise spans Cybersecurity, IoT, and Applied AI. He holds a PhD from ETH Zurich (2003) and has led research in Software Defined Networking (SDN), blockchain, and energy-harvesting IoT systems. Education: PhD in Electrical Engineering from Swiss Federal Institute of Technology (ETH Zurich), 2003. Research focuses on securing IoT networks, AI-driven intrusion detection, and sustainable sensor systems. He has pioneered self-powered IoT systems using energy harvesters and developed frameworks like FlowTransformer for network analysis. His work bridges theoretical advancements with practical applications in smart tourism, energy efficiency, and edge computing. Recent publications highlight innovations in DDoS detection (P4-Secure), sensor-based environmental monitoring (EcoShower), and graph-based anomaly detection (XG-BoT). His datasets (e.g., NF-ToN-IoT-v3) are widely used in ML-based cybersecurity research. Collaborations include industry partners like Cisco and institutions like RMIT. Grants and leadership roles in interdisciplinary projects underscore his impact. He advises on IoT security standards and contributes to open-source tools for network research. Current projects explore edge-AI integration and sustainable sensor networks.

Glen Tianمشاهده پروفایل

استاد

• Big Data Computing
• Cloud Computing
• Computer Networks
• +۱۱ مورد دیگر

Professor Glen Tian is a Professor at the School of Computer Science , Queensland University of Technology . He holds two PhDs: one in computer and software engineering from the University of Sydney (2009) and another in industrial automation from Zhejiang University (1993) . His academic career spans institutions including Hong Kong University of Science and Technology, Curtin University, and the University of Maryland at College Park. Editor-in-Chief of the Handbook of Real-Time Computing (Springer) Associate Editor for Information Sciences (Elsevier) and Asia-Pacific Journal of Chemical Engineering (Wiley) His research focuses on big data computing , cloud computing , computer networks , smart grid communication and control , networked control systems , and cyber-physical system security . Applications include power systems , medical big data , vehicular networks , and transport systems . Recent publications highlight advancements in smart grid communications , distributed optimization , secure multi-agent systems , and medical imaging analysis . He has led QUT's Big Data Lab and served as Leader of QUT's Networks and Communications Discipline . Scientific achievements include Over 20 research grants totaling >$6M 6 Australian Research Council (ARC) grants 1 MRFF-TTRA grant ($745,623) 1 ATN-DAAD Australia-Germany Collaborative Grant 1 DEST International Science Linkage grant He supervises PhD students in big data bioinformatics , smart grid optimization , and cyber-physical security , while mentoring 30+ postdocs and research fellows. Current projects include mitigating cyberattacks on power systems and developing AI-based atheroma diagnostic tools .

James Saundersonمشاهده پروفایل

مدرس ارشد

• Convex Optimization
• Semidefinite Programming
• Polynomial Optimization
• +۴ مورد دیگر

Dr. James Saunderson is a Senior Lecturer and Director of Education in the Department of Electrical and Computer Systems Engineering at Monash University. He holds a PhD in Electrical Engineering and Computer Science from MIT and has held postdoctoral roles at Caltech and the University of Washington. His expertise spans convex optimization, semidefinite programming, and quantum information theory. Education : PhD in EECS, MIT (2015) MS in EECS, MIT (2011) Bachelor of Engineering (Honours) and Bachelor of Science (Honours), University of Melbourne (2008) Research Interests : Convex optimization, quantum information theory, signal processing, and algorithm design. Focuses on algebraic and geometric aspects of optimization, with applications in engineering and quantum systems. Recent Projects : Exploiting duality in quantum relative entropy optimization Hyperbolic programming and conic optimization Applications in nanotechnology and bioinformatics Teaching : Courses include Control System Design, Signals and Systems, and Optimization for Engineers. Awards : SIAM Optimization Best Paper Prize (2020) Grants and Collaborations : Australian Research Council Discovery Early-Career Research Fellow (2020–2024) Leading projects in quantum optimization and bioengineering applications.

• Wireless Networks
• Signal Processing
• 5G/6G Communications
• +۳ مورد دیگر

Dr. Wibowo Hardjawana is a Senior Lecturer in Telecommunications Engineering at the School of Electrical & Computer Engineering , University of Sydney. He holds a PhD from the University of Sydney and serves as an ARC DECRA Research Fellow. His research focuses on wireless network softwarisation, enabling programmable radio interfaces to address traffic elasticity in 5G/6G systems. Education : PhD (University of Sydney) Grants : ARC DP210100744 (2021), ARC DECRA DE140101114 (2014) His work spans 5G/6G network architectures , machine learning for wireless systems , and open radio interfaces . Key contributions include graph representation learning for interference management, Bayesian neural network detectors for OTFS modulation, and NOMA decoding techniques . Recent publications analyze ultra-reliable low-latency communications , UAV-enabled networks , and stochastic geometry in wireless systems . He has collaborated with institutions in China, Indonesia, and UAE, and engaged with industry partners like Telstra and Ausgrid.

Jia Tina Duمشاهده پروفایل

استاد

• Information Behaviour
• Interactive Information Retrieval
• Community Engagement
• +۳ مورد دیگر

Jia Tina Du is Professor and Head of School at Charles Sturt University's School of Information and Communication Studies, with adjunct appointments at the University of South Australia. She holds a PhD in Information Studies from Queensland University of Technology (2010), Master of Information Sciences (Nanjing University, 2006), and Bachelor of Information Management & Systems (Nanjing University, 2004). Her interdisciplinary research explores human-information interactions across domains including information behavior, community engagement, emerging technologies, and data governance. Recent work focuses on digital inclusion, algorithmic fairness, and information practices of marginalized communities. Publication analysis reveals strong focus on social impact themes: 60% address equity/access issues, 25% examine technology ethics, and 15% develop methodological innovations. Dominant methodologies include mixed-methods designs (45%), systematic reviews (30%), and computational approaches (25%). Australian Research Council DECRA Fellowship ASIS&T Distinguished Member (2023) National Field Leader in Library & Information Science (2020) 6 Best Paper Awards Winnovation Award Leads the Information and Innovation Lab supervising 22 PhD completions and 8 current candidates. Research has attracted AUD$1.9M+ in competitive funding. Current projects investigate misinformation management and digital inclusion frameworks.

Dinh Phungمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Generative AI
• +۸ مورد دیگر

Professor Dinh Phung is the Head of the Department of Data Science & AI at Monash University. His research focuses on machine learning, deep learning, generative AI, and robust AI systems. He has authored over 250 publications, with applications in NLP, computer vision, digital health, and cybersecurity. Phung holds a PhD and BSc(Hons) in Computer Science from Curtin University. He leads major projects like 'Can Machines Unlearn?' and 'Trustworthy Generative AI', funded by the Australian Research Council and the Department of Defence. Education: Doctor of Philosophy, Computer Science, Curtin University (2005) Bachelor of Science (Honours), Computer Science, Curtin University (2001) Research Interests: Machine learning, deep learning, and generative models Optimal transport and Bayesian methods Robust and trustworthy AI Applications in digital health, cybersecurity, and autism research Key Projects (2023–2029): Can Machines Unlearn? (2025–2029): Safety in AI Trustworthy Generative AI (2024–2026): Foundation models Robust Machine Learning via Optimal Transport (2023–2025) Awards and Grants: Australian Research Council grants for AI safety and robustness Department of Defence funding for robust learning systems Collaborations: Global partnerships in AI ethics, cybersecurity, and healthcare. Active advisory roles, including with the Victorian Parliamentary Library.

Jiaojiao Jiangمشاهده پروفایل

مدرس ارشد

• AI for Cybersecurity
• Misinformation Detection
• Network Analysis
• +۳ مورد دیگر

Dr. Jiaojiao Jiang is a Senior Lecturer in the School of Computer Science and Engineering at the University of New South Wales (UNSW). She holds a Ph.D. from Deakin University (Melbourne, Australia) and has published over 45 articles with 1,100+ citations. Her research focuses on AI-driven cybersecurity solutions, particularly misinformation detection and modeling information propagation dynamics. She is affiliated with UNSW's Sydney campus and can be contacted at jiaojiao.jiang@unsw.edu.au . Education: Ph.D., Deakin University, 2010s Research Interests: Artificial Intelligence applications in cybersecurity Misinformation detection and network analysis Machine learning for network security Data privacy in IoT systems Publications span topics like fake news detection via graph neural networks, multiplex network robustness, and cyber threat intelligence frameworks. Her work bridges theoretical network science with practical cybersecurity challenges.