Find Academic Supervisors

Fu Swee TeeView profile

Lecturer

• Artificial intelligence
• Deep learning
• Computer vision
• +3 more

Dr. Fu Swee Tee serves as a Lecturer in Computing within the Faculty of Engineering, Computing and Science at Swinburne University of Technology Sarawak. Her academic journey includes a BSc (Hons) in Computing from the University of Portsmouth (2006), a Master of Advanced Information Technology from Universiti Malaysia Sarawak (2013), and a PhD from Swinburne University of Technology (2025), following industry experience as a software developer and six years teaching at a skills training college. Her educational background: PhD, Swinburne University of Technology, 2025 Master of Advanced Information Technology, Universiti Malaysia Sarawak, 2013 BSc (Hons) in Computing, University of Portsmouth, 2006 Dr. Fu Swee Tee's research pioneers deep learning applications for intelligent video analytics, specializing in abnormal event detection within complex environments. Key focus areas include: Traffic accident recognition in mixed-traffic urban scenarios Cyberbullying detection through digital game interventions Sociodemographic analysis of online behavioral risks Her work bridges theoretical AI advancements with practical societal impact in transportation safety and digital wellbeing. Analysis of her 2018-2024 publications reveals an evolving research trajectory: early work on ontology reuse for multiagent systems transitioned into current deep learning applications for video analytics. Recent publications (2022-2024) demonstrate concentrated expertise in traffic safety systems and cyberbullying prevention, with increasing interdisciplinary collaboration across computer science, transportation engineering, and behavioral psychology. No major scientific awards are documented in available sources. However, her publication record in high-impact venues including IEEE Access and the Journal of Technology in Behavioral Science demonstrates scholarly recognition and research impact within her specialized fields. Dr. Fu Swee Tee actively recruits PhD and Master's students for AI research projects, emphasizing practical applications and cross-disciplinary collaboration. Her supervision approach integrates industry-relevant problem solving with academic rigor, as evidenced by publications spanning technical AI development and behavioral studies. Current research momentum suggests active grant funding supporting her traffic safety and cyberbullying projects.

Maolin TangView profile

Senior Lecturer

• Cloud Computing
• Big Data
• Energy Efficiency
• +5 more

Dr. Maolin Tang is a Senior Lecturer in the School of Computer Science at Queensland University of Technology (QUT). He holds a PhD in Engineering from Edith Cowan University, a Master of Engineering in Computer Science from Chongqing University, and a Bachelor of Engineering in Computer Software from Huazhong University of Science and Technology. His research focuses on Big Data Cloud Computing, Energy-Efficient Data Centres, QoS-Aware Web Service Composition, and SaaS Optimization in the Cloud. Dr. Tang’s work addresses challenges such as MapReduce computation in dynamic cloud environments, energy efficiency in data centres, and composite service optimization. He has supervised numerous PhD students and published extensively in top-tier journals like IEEE Transactions on Industrial Electronics and Expert Systems with Applications. His research combines evolutionary computation techniques, genetic algorithms, and optimization strategies to solve complex computational problems. Education : PhD (Engineering), Edith Cowan University Master of Engineering (Computer Science), Chongqing University Bachelor of Engineering (Computer Software), Huazhong University of Science and Technology Dr. Tang’s research interests emphasize energy-efficient data centre management, cloud resource provisioning, and the application of computational intelligence to real-world challenges. His work on MapReduce in cloud computing aims to improve scalability and QoS guarantees, while his energy-efficient frameworks reduce operational costs and environmental impact. He is actively involved in supervising PhD students and collaborating on projects funded by initiatives like CRC for Smart Services. His publications span topics such as virtual machine placement optimization, SaaS deployment, and algorithmic approaches to dynamic resource management. Dr. Tang teaches advanced courses in algorithms and computational complexity at both undergraduate and postgraduate levels.

• Supply Chain Management
• Advanced Manufacturing
• Mathematical Optimization Modelling
• +2 more

Amir Hossein Ordibazar is a PhD candidate at the School of Business, UNSW Canberra. He holds a Bachelor's and Master's degree in Industrial Engineering from the University of Tehran, Iran (2016 & 2018), and has experience as a teaching assistant and software teacher at the University of Tehran. His research focuses on developing an intelligent framework for real-time Supply Chain Risk Management (SCRM) using Mathematical Optimization Modelling , Artificial Intelligence , and Machine Learning techniques. Educational Background Bachelor's of Industrial Engineering (University of Tehran, 2016) Master's of Industrial Engineering (University of Tehran, 2018) Research Interests Amir's work bridges Supply Chain Management , Advanced Manufacturing , and Mathematical Optimization Modelling with a focus on real-time risk mitigation. His application of Artificial Intelligence and Machine Learning to SCRM demonstrates an interdisciplinary approach to solving complex industrial problems. Publications Trends Amir's publications span Supply Chain Management , Mathematical Optimization , and Project Scheduling , reflecting his expertise in integrating technical methods with industrial applications. His work includes a 2022 paper on risk mitigation via counterfactual explanations, a 2021 book chapter on project scheduling, and a 2020 journal article on sustainable supply chain network design.

Dennis LiuView profile

Lecturer

• Blockchain
• Cybersecurity
• Applied Cryptography
• +2 more

Dennis Liu is a Lecturer at the Department of Software Systems & Cybersecurity, Monash University. He holds a PhD, MPhil, and BSc in Computer Science from City University of Hong Kong, with over 15 years of experience in tertiary education and cybersecurity/blockchain training. BSc (1st Hons) in Computer Science, City University of Hong Kong MPhil in Computer Science, City University of Hong Kong PhD in Computer Science, City University of Hong Kong His research focuses on blockchain technologies, cybersecurity, and pedagogy. He has developed the first blockchain postgraduate program in Hong Kong and led teaching initiatives to enhance cybersecurity education through funded projects. Recent publications highlight his work in blockchain applications for logistics security, RFID/NFC integration with digital twins, and blockchain pedagogy for IT practitioners and secondary students. His research also spans computational thinking education via competitive programming. Faculty Outstanding Award in Teaching (Team) 2021/22 Faculty Merit Award in Teaching (Individual) 2019/20 Outstanding Teacher Award 2011 Best Paper Award in IEEE TALE 2019 He has served as Deputy Programme Leader for computing and blockchain programs at PolyU and acted as an External Examiner for IT and cybersecurity programs. His industrial work includes blockchain research and consultancy projects advising on cryptographic protocols and system implementations.

Tristan ReedView profile

Lecturer

• Transport System Analysis
• Transport Modelling
• Software Applications for Problem Solving
• +3 more

Tristan Reed is a Lecturer in the Department of Management and Organisations at the UWA Business School, affiliated with the Centre for Business Data Analytics. He holds a BEng (Hons) and PhD in Spatial Sciences, with expertise in transport system analysis, software engineering, and business intelligence. His research focuses on applying software applications to solve real-world transport challenges, particularly through collaborations with the Planning and Transport Research Centre (PATREC) and iMOVE CRC. Education: Bachelor of Engineering (Honours) PhD in Spatial Sciences Research Interests: Transport system analysis and modeling Software applications for urban problem-solving Business intelligence (databases, visualization) Semantic web techniques for geospatial data Smart city technologies Current Projects: Transport Mode Choice using Perth Area Transport and Household Survey (PATHS) Data Impact of e-Rideables on Transport Tasks in Western Australia Grants and Collaborations: Investigator on the AI Adoption in WA Volunteering Sector project (2025–2026). Collaborations with PATREC, iMOVE CRC, and Curtin University (as a Research Associate). Labs/Teams: Centre for Business Data Analytics Planning and Transport Research Centre (PATREC)

Aaron S.W. WongView profile

Part-Time Lecturer

• Computer Science
• Artificial Intelligence
• Robotics
• +16 more

Dr Aaron Wong is an Honorary Lecturer at the School of Psychology , University of Newcastle , with dual affiliations in Computer Science and Software Engineering . His career spans interdisciplinary research in robotics, cognitive neuroscience, and neuroimaging, supported by roles in the Functional Neuroimaging Laboratory and Priority Research Centre for Stroke and Brain Injury . Education: PhD in Computer Science, University of Newcastle Bachelor of Engineering (Computer Engineering) with Honours Bachelor of Computer Science Research Focus: Dr Wong's work bridges machine learning , humanoid emotion modeling , and multimodal neuroimaging (MRI/EEG). Key projects include developing brain-computer interfaces , acoustic localization systems for rescue robots, and semi-supervised manifold alignment techniques. Publication Trends: Recent articles emphasize theta oscillations in cognitive control , EEG-MRI joint modeling , and deep learning for speech emotion recognition . Collaborative themes span neurodevelopmental studies , stroke research , and urban robotics . Scientific Awards: 2008 RoboCup SPL World Champion 2011 RoboCup Australian Open Champion 2014 Global Leader of Innovation (UON) 2011 Best Student Paper (ANZAScA) Supervision & Grants: Served as co-supervisor for two PhD students. Secured $23,775 in grants including a 2018 Hunter Medical Research Institute award for EEG-MRI predictive modeling and 2016 Keats Endowment funding for cognitive flexibility research . Labs & Teams: Central to the Functional Neuroimaging Laboratory and PRC Stroke and Brain Injury , with global RoboCup collaborations and contributions to the Age-ility Project data repository.

Chengbo ZhengView profile

Research Fellow

• Data Visualization
• Human-Computer Interaction (HCI)
• Artificial Intelligence
• +3 more

Dr. Chengbo Zheng is a Postdoctoral Research Fellow at the School of Electrical Engineering and Computer Science, University of Queensland. His research focuses on data visualization, human-computer interaction, and educational technology, particularly leveraging AI to enhance collaborative work, decision-making, and learning environments. Zheng has contributed to interdisciplinary projects such as AI tools for self-assessment in education, human-AI co-exploration systems, and visualization techniques for complex data analysis. His work bridges theoretical advancements with practical applications, including improving data storytelling, combating misinformation, and optimizing transportation networks through visual analytics. Recent projects emphasize AI's role in collaborative processes, such as group decision-making fairness and interdisciplinary information seeking. Zheng's methodologies often combine computational tools with user-centered design principles to address real-world challenges. He has presented at top venues like CHI, UIST, and IEEE Visualization conferences, showcasing innovations in interactive systems, AI integration, and visualization design. His research has implications for education, scientific collaboration, and urban planning.

Nisansala YatapanageView profile

Senior Lecturer

• Formal Methods
• Concurrency Verification
• Safety-Critical Systems
• +7 more

Nisansala Yatapanage is a Senior Lecturer at the Australian National University (ANU) since January 2025, and served as a Lecturer from 2022 to 2024. She holds the position of Interim Associate Director of Engagement and Impact in the School of Computing within the ANU College of Systems & Society. Prior to ANU, she was a Senior Lecturer/Lecturer at De Montfort University, Leicester, U.K. (2017-2019), and worked with Prof. Cliff Jones at Newcastle University, U.K. (2013-2017) on the "Taming Concurrency" project. Her educational background includes a PhD from Griffith University (2012), supervised by Dr. Kirsten Winter. Before her PhD, she was a researcher in the ARC Centre for Complex Systems and Griffith University (2004-2007), working on specification and verification for safety-critical systems using Behavior Tree language and model checking. Nisansala's research focuses on the application of formal methods for various applications, particularly in concurrency, safety-critical systems, and security. She is currently investigating concurrency verification using rely/guarantee, separation logics, and temporal logic. Her work also explores the verification of security protocols and the foundations of concurrency, with recent research examining the links between rely/guarantee reasoning and linearisability for non-blocking algorithms. She has developed techniques for reducing Behavior Tree models prior to model checking and created a novel form of branching bisimulation called "Next-preserving Branching Bisimulation." Her publications demonstrate a consistent focus on formal verification methods, with particular emphasis on concurrency and safety-critical systems. Over the years, her work has evolved from Behavior Tree specifications and model checking to more advanced techniques involving rely/guarantee reasoning and separation logic. Recent publications show increasing focus on security protocols and the theoretical foundations of concurrent systems. Fellow of AdvanceHE Commended in Australian Photographer of the Year Competition 2020 (Travel category) Nisansala has extensive teaching experience across multiple institutions. At ANU, she has served as Course Convenor for multiple courses including COMP4011/8011 Special Topics in Formal Methods and Programming Languages, COMP1600 Foundations of Computing, and COMP1100/1130 Programming as Problem Solving. Previously at De Montfort University, she was Deputy Programme Leader of the BSc Computer Science & BSc Software Engineering degrees and Course Convenor for Data Structures & Algorithms and Concurrent & Parallel Algorithms. She has also taught at the ANU Logic Summer School. She has been involved in several significant research projects including "Taming Concurrency" at Newcastle University (2013-2017), a Model-Based Safety Analysis of Air Traffic Control Operational Procedures at UQ (2011-2012), and her PhD project on Slicing Behavior Trees for Verification of Large Systems at Griffith University (2007-2011).

Kevin LeoView profile

Research Fellow

• Constraint Programming
• Modelling
• Presolving
• +3 more

Kevin Leo is a Research Fellow in the Department of Data Science & AI at Monash University. His work contributes to the United Nations Sustainable Development Goals (SDGs), though specific goals are not detailed in the text. **Research Interests**: Constraint Programming Modelling and Presolving Techniques Operations Research Programming Languages Algorithm Design for Optimization Applications in Medical Science and Autonomous Systems His recent research emphasizes core-guided reformulation, human-centred feasibility restoration, and globalization of constraint models. These advancements address both theoretical challenges and real-world applications such as UAV autonomy and medical treatment planning. Collaborations with international researchers are noted, though specifics are not elaborated. Kevin has no recorded part-time status or scientific awards. His advising and grants sections remain empty, with no listed students or active grants. His contributions focus on peer-reviewed publications in artificial intelligence and constraint satisfaction domains.

Mehwish NasimView profile

Senior Lecturer

• Complex Systems
• Social Network Analysis
• Human-Centric Cyber Security
• +5 more

Mehwish Nasim is a Senior Lecturer at The University of Western Australia (UWA), affiliated with the School of Physics, Maths and Computing's Department of Computer Science and Software Engineering. She previously held roles at the University of Adelaide, Flinders University, and CSIRO. As the Social Media Coordinator for the Australian Mathematical Society (AustMS), she bridges academic communication and public engagement. Her research focuses on complex systems, social network analysis, cyber security, and health analytics. Current projects include AI-driven detection of misinformation, polarization modeling on social media, and predictive models for population-level events. She also explores decision-making frameworks using complex systems methodologies. Recent publications highlight her work on large language models in social science, video moment retrieval, and mental health surveillance. Her contributions span computational methods for social good, environmental prediction, and ethical AI applications. Awards: Shining Star in AI (WiTWA 2023), PMC School Special Commendation (2023), Anne Penfold Street Award (2023) External Roles: Adjunct Lecturer at Flinders University and University of Adelaide; Visiting Scientist at CSIRO-Data61; Associate Investigator at ARC Centre of Excellence for Mathematical and Statistical Frontiers Activities: Organized the 1st International Workshop on Multimodal Content Analysis for Social Good (2023); Public outreach on cybersecurity and data science She actively supervises PhD students in areas like AI ethics and social network dynamics, contributing to UWA's research degree opportunities.

Jo LaneView profile

Researcher

• Mathematical Logic
• Artificial Intelligence
• Automated Reasoning
• +2 more

Dr. Jo Lane is affiliated with the Australian National University as a member of the John Curtin School of Medical Research . She collaborates with the Maddess Group , focusing on diagnostics for eye diseases, though her research spans multidisciplinary areas including mathematical logic, artificial intelligence, and automated reasoning. Academic Rank : Researcher Research Themes : Logic, theorem proving, constraint modelling, and AI Her recent work explores paraconsistent mathematics, relevant arithmetic, conflict-resolution algorithms for SAT solvers, and optimization techniques. She contributes to tools like Scavenger and Logic for Fun, bridging logic with problem-solving frameworks. Key article trends include advancements in automated reasoning (e.g., conflict-driven clause learning), applications of logic to AI planning (non-Markovian rewards), and interdisciplinary efforts connecting mathematical theory to computational methods. Dr. Lane’s collaborations and publications highlight expertise in logic, computational complexity, and medical diagnostics, though no explicit awards or student advising details are provided in the text.

• Learning and Teaching
• Computer Education
• Serious Games
• +7 more

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

Asif KarimView profile

Lecturer

• Machine Learning
• Health Informatics
• Blockchain Applications
• +7 more

Dr. Asif Karim is a Research Active Lecturer in the Department of Information Technology at the Faculty of Science and Technology, Charles Darwin University, Australia. He has been a full-time lecturer since August 2021, following a sessional role from 2018 to 2021. Prior to his current position, he served as a lecturer at Daffodil International University and Uttara University in Bangladesh. His research focuses on the application of machine intelligence in health informatics and blockchain technologies. He has significant industry experience in Software Engineering and actively supervises postgraduate research students. Machine Learning Health Informatics Blockchain Applications Smart Contracts Deep Learning Anomaly Detection The recent publications of Dr. Karim span a diverse range of applications in artificial intelligence, particularly in healthcare and secure computing. His work includes developing efficient deep learning models for medical diagnosis, privacy-preserving classification of diseases from medical images, and anomaly detection in cybersecurity. He also explores applications in mobile cloud computing and agricultural technology, demonstrating a broad interdisciplinary approach to solving real-world problems using machine learning. Dr. Karim actively contributes to research projects and supervises postgraduate students. He led the project "Machine Learning Diagnostics System for Bronchiectasis" and has extensive experience in teaching undergraduate and postgraduate courses in computer science, including Machine Learning, Operating Systems, and Software Engineering. He is involved in organizing academic events, such as a digital awareness workshop for rural indigenous communities, reflecting his commitment to community engagement and technology outreach.

Hamid RoshanView profile

Professor

• THMC Experimental and Computational Modelling
• Carbon Capture, Utilization and Storage
• Coal Seam Gas Engineering
• +7 more

Professor Hamid Roshan is a faculty member at the School of Minerals and Energy Resources Engineering within the Faculty of Engineering at UNSW Sydney. He graduated with a PhD in Petroleum Geomechanics Engineering from UNSW Sydney in 2012, followed by 3.5 years of postdoctoral training in the School of Civil and Environmental Engineering. He was appointed to his current position in 2016 after gaining valuable industry experience with the Underground Gas Storage Company, where he worked on the Sarajeh field gas storage project. Professor Roshan's research spans multiphysics geomechanics and rock characterization, with applications across Mining, Civil, and Petroleum Engineering sectors. His work integrates theoretical, numerical, and experimental approaches to solve complex geomechanical problems. Since 2017, he has developed the advanced GeoEngineering Research Lab at UNSW, where next-generation equipment for coupled geomechanics-rock characterization has been designed and built, offering state-of-the-art services to industry. His research interests include THMC Experimental and Computational Modelling in CCUS, Coal Seam Gas and Shale Gas Engineering, Geophysics and Data-driven Rock Mass Characterization, Borehole Geotechnical Logging, In-situ Stress Measurement and Estimation, and Fundamentals of Rock Mechanics with a focus on Multiphysics Geomechanics. His recent publications demonstrate expertise in ultramafic rock interactions, geothermal energy storage, shale gas reservoirs, and advanced computational modeling techniques. Professor Roshan has developed and patented field-scale downhole logging tools for stress-mechanical property measurements along with software solutions for the mining industry. His work has practical applications in carbon sequestration, underground hydrogen storage, and unconventional gas extraction. Professional Recognition: American Rock Mechanics Association Future Leader Professional Memberships: Australian Geomechanics Society, International Society of Rock Mechanics, Society of Petroleum Engineers Professor Roshan teaches Petrophysics (PTRL2020), Formation Evaluation (PTRL5107), Integrated Oil and Gas Reservoir Evaluation (PTRL4010), and Geomechanics A, while actively seeking students with strong academic backgrounds for research opportunities.

Mark WallaceView profile

Professor

• Optimization
• Constraint Programming
• Artificial Intelligence
• +5 more

Professor Mark Wallace is a renowned academic at Monash University , specializing in modelling and software platforms for planning, scheduling, and optimization problems . He has led groundbreaking projects such as the development of the ECLiPSe constraint programming platform (acquired by Cisco Systems) and the G12 hybrid optimization platform , which was commercialized through his company, Opturion . His research consistently bridges theoretical innovation with real-world applications, supported by industry funding from major companies like British Airways, Qantas, and Woodside Energy. Education: MA in Mathematics and Philosophy from Oxford University; MSc in Artificial Intelligence from Queen Mary College, London; PhD in Communicating with Databases in Natural Language from Southampton University. His work focuses on application-driven research in constraint programming, hybrid optimization systems, and decision support technologies. Recent publications highlight advancements in public transport routing , autonomous vehicle fairness constraints , and human-centred feasibility restoration . He actively collaborates with industry partners on projects involving Melbourne Water , Woodside , and the Alertness CRC , driving innovations in smart infrastructure and transport systems.