Find Academic Supervisors

James BirtView profile

Associate Professor

• Educational Technology
• Virtual Reality (VR)
• Augmented Reality (AR)
• +4 more

Dr. James Birt is an Associate Professor of Creative Media and Associate Dean for External Engagement at Bond University's Faculty of Society & Design. He specializes in Educational Technology with a focus on Virtual Reality (VR), Augmented Reality (AR), and immersive simulations. His research bridges theoretical knowledge and practical applications, emphasizing technology standardization (e.g., ISO/IEC 5927:2024) and industry collaboration. Birt holds a PhD in AI and Software Engineering and has contributed to global initiatives in immersive technology through committee work and partnerships. Education: PhD in Software Engineering (Bond University, 2006), Honours in Information Technology (Griffith University, 2003), Bachelor of Information Technology (Griffith University, 2000). Research Interests: Dr. Birt explores emerging technologies like VR/AR for enhancing learning, community engagement, and healthcare. His work includes developing safety standards for immersive technologies and investigating their applications in medical training, climate change communication, and esports education. Recent projects include the Mixed Reality Research Lab and the OPiC construction research incubator. Advising & Grants: Supervises projects on VR in medical investigations and esports diplomacy. Collaborates with organizations like the International Organization for Standardization and ASCILITE. Labs/Initiatives: Leads Bond University's Mixed Reality Research Lab, focusing on multimodal learning analytics and secure exam systems. Co-developed the ARBuilding and Corrigan Walk apps for cultural education and spatial visualization.

• Cybersecurity
• Machine Learning
• Cryptography
• +3 more

Dr. Aqeel Sahi is a Lecturer in Computing at the University of Southern Queensland's School of Mathematics, Physics and Computing. He holds an MSc from Universiti Utara Malaysia and a PhD in Cybersecurity and Machine Learning from USQ. With over 15 years of teaching experience, Dr. Sahi instructs courses including Algorithms and Data Structures, Object-Oriented Programming, and Web Technologies. His research spans cybersecurity, machine learning, cryptography, and software engineering, with particular focus on developing advanced security algorithms and machine learning applications for network protection. Recent publications demonstrate strong emphasis on AI-driven security solutions, healthcare applications, and network defense mechanisms. Dr. Sahi maintains professional memberships with IEEE and ACS, bridging academic and industry expertise through his background as a senior software engineer.

Jean-Guy SchneiderView profile

Professor

• Software Engineering
• Quantum Computing
• Cloud Computing
• +4 more

Prof. Jean-Guy Schneider is a Professor and Associate Dean (Education) in the Faculty of IT at Monash University. He holds a PhD in Computer Science from the University of Bern, Switzerland, and has over 20 years of experience in higher education. His research focuses on reliable software technologies, including component-based systems, cloud/mobile computing, quantum software, and agile methodologies. He actively contributes to software engineering education and industry-relevant research. His key research areas include energy-efficient IoT architectures, machine learning model security (e.g., MLGuard project), and quantum computing abstractions. Recent work emphasizes optimizing workflows for energy/performance trade-offs and addressing challenges in open-source ML projects. Prof. Schneider has published extensively on topics like service virtualization, Docker container monitoring, and anomaly detection in cloud systems. He supervises PhD candidates in software engineering for machine learning and quantum computing.

Helen PaikView profile

Senior Lecturer

• Service-oriented Software Design
• Distributed Data and Application Integrations
• Blockchain
• +6 more

Associate Professor Helen Paik is a Senior Lecturer at the School of Computer Science and Engineering at the University of New South Wales (UNSW). She holds a PhD in Computer Science (Web Data Integration) from UNSW (2004). Her research focuses on Service-oriented Software Design, Blockchain Technology, Distributed Ledger Systems, and Cyber Security. Before joining UNSW, she worked at QUT and in industry with IBM Australia. Her research emphasizes blockchain governance, decentralized identity management, and privacy-preserving technologies. Notable contributions include work on federated learning architectures, self-sovereign identity systems, and ethical AI frameworks. She has supervised PhD and Master’s students in areas like privacy-preserving AI, IoT security, and distributed systems. Helen’s publications span top-tier journals and conferences, including IEEE Transactions, ACM, and Springer. She actively contributes to interdisciplinary collaborations, integrating machine learning with public health for epidemic prediction and governance models for AI systems.

Naipeng DongView profile

Lecturer

• Formal Verification
• Cybersecurity
• Privacy
• +3 more

Dr. Naipeng Dong is a Lecturer at the School of Electrical Engineering and Computer Science, The University of Queensland. Her expertise lies in automatic formal verification of security and privacy in cryptographic protocols, Android applications, and blockchain systems. She holds a PhD from the Université du Luxembourg. Education: Doctor of Philosophy (PhD), Université du Luxembourg Research Interests: Dr. Dong focuses on developing efficient formal verification techniques for analyzing cryptographic protocols, ensuring fault-tolerance in systems with dishonest participants, and exploring applications in e-auction, e-health, Single-Sign-On (SSO) authentication, and blockchain consensus mechanisms. Her work also addresses blockchain-based systems, NFT applications in music copyright, and cybersecurity in industrial control systems. Advising and Grants: While specific grant details are not detailed, her research involves collaborative projects with industry and academic partners, emphasizing practical applications of formal verification and cybersecurity. She actively contributes to academic supervision. Labs and Teams: She is part of the Cyber Security and Software Engineering (CSS) discipline at UQ, collaborating with researchers like Associate Professor Guangdong Bai on trustworthy AI, privacy compliance, and formal methods.

Yunlong TangView profile

Lecturer

• Additive Manufacturing
• Smart Manufacturing
• Digital Twin Technology
• +5 more

Dr. Yunlong Tang is a Lecturer jointly appointed by the Department of Mechanical and Aerospace Engineering and the Department of Materials Science and Engineering at Monash University. He also serves as Assistant Director of the Monash Centre for Additive Manufacturing (MCAM). His research focuses on digital additive manufacturing, AI-driven design tools, and smart manufacturing systems. He holds a Ph.D. from McGill University, a Master’s from Beihang University, and a Bachelor’s from Harbin Institute of Technology. Education: Ph.D. in Mechanical Engineering, McGill University, 2018 M.Sc. in Aerospace Manufacturing Engineering, Beihang University, 2013 B.Eng. in Mechanical Engineering, Harbin Institute of Technology, 2010 Research Interests: Design for Additive Manufacturing (DfAM) and open-source tools like IntraLattice AI and computational design for material-process-structure integration Digital twin-enabled smart manufacturing and process optimization Hybrid materials design and digital manufacturing processes Advising & Grants: He supervises PhD students in topics such as AI-aided DfAM, digital twin process planning, and bio-inspired composites. He leads projects like 'Smart In-Process Quality Inspection' and collaborates on waste management decision analysis. Labs & Teams: He directs the Intelligent Digital Manufacturing and Design (I-DMD) Lab , a cross-departmental team advancing AI and digital twin technologies in manufacturing. The lab focuses on sustainable, adaptive, and personalized manufacturing solutions.

Jian YangView profile

Professor

• Graph Mining
• Fake News Detection
• Fraud Detection
• +4 more

Prof. Jian Yang is a Professor at Macquarie University's School of Computing and holds leadership roles in the Data Horizons Research Centre and Applied Artificial Intelligence Research Centre. She earned her PhD in Data Integration from The Australian National University (1995). Prior to Macquarie, she held roles at Tilburg University (Netherlands), CSIRO, and the University of New South Wales. Recognized as a Top 2% Global Scientist (2019–2024), her research focuses on graph mining, fraud detection, and smart city technologies. She has led over 33 projects funded by ARC, CRCs, and EU frameworks. Notable awards include Best Student Paper Awards (2021, 2024) and Excellence in HDR Supervision (2019). Education: PhD in Data Integration, ANU (1995) External Positions: Director of Industry PhD Program at Digital Finance CRC Research Interests: Prof. Yang’s work spans graph mining, trust and spam detection in social media, fraud detection in finance, data fusion for medical data, and smart city applications. Recent projects include detecting thyroid cancer via data fusion and enhancing trust in web-based systems. Grants & Projects: Active projects include MQRC Consilience Data Research Centre (2023–2028), Data-to-Data Products for Trusted Economies (2023–2027), and Graph Mining for Social Events (2023–2025). Past work includes EU Six Framework and CSIRO collaborations. Labs/Teams: Leads the Data Horizons Research Centre and collaborates with global teams on service-oriented computing and AI ethics. She chairs international conferences like ICSOC and BPM.

Yue XuView profile

Associate Professor

• Data Analytics
• Machine Learning
• Knowledge Discovery
• +6 more

Associate Professor Yue Xu is affiliated with the School of Computer Science at Queensland University of Technology (QUT). She obtained her PhD in 2000 from the University of New England and has held academic positions at Tasmania University (2000–2002) and QUT since 2002, where she was promoted to Associate Professor in 2011. Her research focuses on data analytics, machine learning, and knowledge discovery. Key areas include pattern mining in large datasets, anomaly detection, vulnerability analysis, topic modeling for text summarization, and social media analytics for business and security improvements. She has developed methods to enhance recommendation systems through multi-dimensional user profiling, context-aware recommendations, and semantic-based approaches. Expertise: Text mining, social engineering attack detection, distributed algorithms for big data Research Themes: Cybersecurity policy frameworks, healthcare prediction models, and interpretable machine learning techniques Prof. Xu has received prestigious awards including the Best Paper Award at WEBIST 2014 and iiWAS2012. She leads research projects such as Web Services Reputation Management (funded by Australian Competitive Grant LP0776400, 2007). Her teaching responsibilities include courses like CAB430 and IFN645, and she coordinates the Master of Data Analytics program. Her current PhD supervisions address challenges in industrial control systems vulnerability detection, hospital readmission prediction, senior frailty assessment, and semantic topic modeling. Completed supervisions include impactful works on healthcare e-coaching systems, spammer detection on Twitter, and reputation models for recommender systems.

• Microscopy and Microanalysis
• Advanced Materials
• Thin Film Coatings
• +4 more

Professor Dougal McCulloch is a Professor and Director of the Microscopy & Microanalysis Facility at RMIT University's Research & Innovation department, based at the City Campus Australia. His research focuses on advanced materials characterization, including microscopy techniques, thin film coatings, and the study of carbonaceous and disordered solids. He leads projects on novel carbon phases under extreme conditions, corrosion-resistant coatings for aerospace alloys, and neuromorphic signal processing. McCulloch coordinates third-year Applied Physics and teaches first-year Life Science Service Physics. He supervises PhD and Masters students in areas like quantum correlation microscopy and carbon material analysis. His work bridges materials science and applied physics, emphasizing experimental and analytical methods. He collaborates on high-pressure synthesis and structural analysis of materials, contributing to both fundamental science and aerospace engineering applications. Research interests include electron microscopy innovations, advanced thin films for industrial applications, and the electronic structure of solids. Projects involve developing environmentally friendly coatings and exploring nanostructured carbons formed under shear or pressure. McCulloch's facility supports interdisciplinary research with cutting-edge microscopy tools. Teaching responsibilities include coordinating applied physics modules and directing the Microscopy Facility, integrating research and education. Supervision focuses on experimental projects at the intersection of materials science and physics. He actively publishes on carbon phase transformations, memristor technologies, and high-pressure material synthesis, reflecting his commitment to advancing analytical and applied materials research.

Timothy ChappellView profile

Lecturer

• Large-scale Data Analysis
• Bioinformatics
• Clustering Algorithms
• +1 more

Dr. Timothy Chappell is a Lecturer in the School of Computer Science at Queensland University of Technology. His research focuses on developing efficient algorithms for large-scale data analysis, particularly in bioinformatics and remote sensing applications. He develops methods for clustering, similarity search, and metagenomic analysis that scale to massive datasets. Dr. Chappell's recent work includes the Crackling method for rapid CRISPR guide RNA design, metagenomic geolocation using read signatures, and parallel K-Tree clustering for extreme-scale datasets. He has applied these methods to diverse domains including urban flood mapping using satellite data, microbiome analysis, and biological sequence clustering. He teaches programming principles (CAB302) and systems programming (CAB403). Dr. Chappell maintains collaborations with government and industry partners, including developing change detection tools for Queensland's Department of Natural Resources.

• Leadership
• Organisational Behaviour
• Higher Education
• +13 more

Dr Joseph Crawford is a Senior Lecturer in Management at the Tasmanian School of Business and Economics, University of Tasmania. He is an accomplished researcher, educator, and community leader with expertise in leadership, organisational behaviour, higher education, and the psychological impacts of artificial intelligence. His work bridges theory and practice, influencing both academic and industry domains. PhD, University of Tasmania (2019) Bachelor of Business (First Class Honours), University of Tasmania (2015) Bachelor of Education (Professional Honours), University of Tasmania (2018) Dr Crawford's research focuses on leadership development, student and workplace belonging, authentic leadership, and the role of AI in human connection and education. He employs psychometric evaluation, quantitative methods, and systematic reviews. His work has been published in top journals including Leadership Quarterly and Computers and Education . The recent articles reflect a strong trend toward interdisciplinary research, integrating leadership theory with digital transformation, sustainability, and mental health in educational and organisational contexts. Scientific recognition includes: Top 1% most cited researcher globally (Google Scholar) Top 2% on Stanford’s Top Scientists list (2022) Vice Chancellor's Innovation Award (2021) Launceston Chamber of Commerce Young Professional of the Year Community Service Award from Rotary International Dr Crawford leads major research projects on leadership, belonging, and AI, funded by organisations including the Department of Education, Menzies Foundation, and Kravis Leadership Institute. He supervises multiple PhD and master’s students and is actively involved in teaching, having coordinated units in leadership, health informatics, and research methods. He serves as Editor-in-Chief of the Journal of University Teaching and Learning Practice and Editorial Board Chair of the Journal of Applied Learning and Teaching , playing a key role in shaping scholarly discourse in higher education. He is also a sought-after keynote speaker and media commentator on leadership, AI, and student wellbeing, and leads community initiatives promoting sustainable leadership and social connection.

• Software Engineering
• Information Systems
• Enterprise Information Systems
• +3 more

Leszek Maciaszek is an Associate Professor and Honorary Research Fellow at the School of Computing, Macquarie University, specializing in software engineering and information systems with emphasis on architectural design and enterprise solutions. His research spans software engineering (100% fingerprint match), architectural design (83%), information systems (67%), enterprise information systems (66%), software process (41%), software production (38%), software complexity (38%), and modern software (36%). He focuses on practical applications in service-oriented architectures, particularly for independent and assisted living domains, addressing business process modeling and software integration challenges. Recent publications demonstrate consistent contributions to software engineering conferences and edited volumes, with notable focus on service e-marketplaces and business-software integration challenges. His work shows strong alignment between theoretical software engineering principles and real-world business process applications, especially in healthcare-adjacent domains. He has participated in research projects including 'Strengthening research collaborations and IT industry links in Europe and linking it to Australian research grants, centres and PhD programmes' (2010), indicating active engagement in international academic-industry partnerships.

Wai Peng WongView profile

Associate Professor

• Machine Learning
• Human Centered AI
• Supply Chain Risk Management
• +7 more

Wai Peng Wong is an Associate Professor at the School of Information Technology, Monash University, Malaysia. She is actively involved in research and supervises PhD students, contributing to cutting-edge advancements in information technology and data analytics. Ph.D, National University of Singapore, 2009 Her research focuses on the integration of machine learning, Data Envelopment Analysis (DEA), and blockchain technology in logistics, supply chain, and health epidemiology. She investigates feature selection for decision-making, develops diffusion models for innovative technologies in agriculture, and applies geospatial analytics to predict non-communicable diseases. Her interdisciplinary work bridges industrial engineering with modern AI techniques. The recent publications demonstrate a strong trend in applying machine learning and blockchain to logistics and agricultural supply chains, with increasing emphasis on smart systems, game theory, and energy-efficient technologies like UAV swarming. Her work spans journals and conferences in operations research, business logistics, and computational economics. Scientific Awards: British Academy Newton Advanced Fellowship (2017) Australian Endeavour Executive Fellowship (2015) Wai Peng Wong has led research projects funded by Malaysia’s Ministry of Higher Education, Motorola Technology Pte Ltd, and the Japan Sumitomo Foundation. She serves on the editorial boards of several international journals, demonstrating leadership in the academic community. Her current projects include energy-efficient Internet of Flying Things and blockchain applications in agriculture. She is affiliated with research networks focusing on sustainable development, contributing to UN SDGs such as responsible consumption and production, and zero hunger through technological innovation in supply chains.

Anna GullerView profile

Research Fellow

• Biomedical engineering
• Pathology
• Human biophysics
• +6 more

Dr. Anna Guller is a multidisciplinary, clinically-oriented scientist currently serving as Senior Scientist at Children's Cancer Institute Australia and Senior Research Fellow at Macquarie University's Faculty of Medicine and Health Sciences. Her work bridges experimental pathology and biomedical engineering, with a focus on developing clinically relevant solutions for tissue engineering, cancer research, and regenerative medicine. Her educational background includes: PhD in Physics from Macquarie University (2014-2017) Postgrad. Cert. in Experimental Pathology (PhD level) from Sechenov University (1999-2003) BSc and MSc in Human and Animal Physiology and Biophysics from V.I. Vernadsky Taurida National University (1990-1995) Dr. Guller's research spans tissue engineering, tumor modeling, biomaterials development, and the application of physical factors in medicine. She specializes in creating 3D engineered microenvironments for both in vitro and in vivo applications, with particular focus on cancer biology, drug testing, and the development of smart biomaterials. Her current work includes analysis of biological effects and biomedical applications of magnetic fields, especially for regenerative medicine and cancer treatment. Analysis of her recent publications reveals a strong trend toward translational research connecting tissue engineering models with clinical applications, particularly in cancer treatment. Her work increasingly focuses on the kynurenine pathway in cancer metastasis and neurodegenerative conditions, magnetic field applications in cancer therapy, and advanced 3D modeling techniques for both education and research purposes. Her notable awards include: iMQREs scholarship (2014) MQRF fellowship (2020) Outstanding Service and Leadership Award, Faculty of Medicine, Health, and Human Sciences, Macquarie University (2024) Dr. Guller has secured approximately $5.7M in research funding since 2005 from diverse sources including ISTC, RFBR, RSF, INTAS, CRDF, FABLS, Tour de Cure foundation, Macquarie University, ARC, NHMRC, and ACRF. Her collaborative work demonstrates extensive mentorship across multiple projects. She leads work in the Computational NeuroSurgery Lab and collaborates extensively across disciplines, developing tissue engineering models that serve as alternatives to animal testing for cancer biology research, drug testing, and diagnostic tool development.

• Artificial Intelligence
• Machine Learning
• Cloud Computing
• +4 more

Cheng-Hao Cai serves as an Adjunct Lecturer in the Department of Data Science & AI at Monash University. His research focuses on interdisciplinary applications of AI, including cloud computing, software engineering, and industrial process optimization. He collaborates with the Monash Suzhou Research Institute on patents related to smart manufacturing and data-driven methodologies. Key research interests include AI-driven modeling for quality prediction in cokemaking, service-oriented cloud scheduling, and advanced NLP techniques like Chinese named entity recognition. His work integrates deep learning frameworks with domain-specific challenges, such as lattice-transformer-graph models for language processing and automated refactoring of state transition models. Cai has contributed to 23 research outputs since 2014, with recent publications emphasizing practical AI solutions for industry and computational systems. His patents highlight collaboration between academia and industry, particularly in Suzhou.