Associate Professor Xiu Wang is affiliated with the School of Computer Science at The University of Sydney, where she serves as Associate Director of the Multimedia Lab and a member of the Biomedical & Multimedia Information Technology (BMIT) Research Group. Her research focuses on panoramic data analysis, biomedical computing, image processing, and medical data fusion. Key projects include tumor treatment outcome prediction using deep learning, collaborative learning of multimodal medical imaging, and deformable image registration techniques. She teaches courses such as COMP5214 (Software Development in Java) and supervises graduate students in AI-driven medical diagnostics and imaging. Notable collaborations involve Dr. Hui Cui and Mr. Chaojie Zheng. Her work bridges computer science and healthcare, emphasizing AI applications in oncology, radiology, and neuroimaging. Recent articles highlight advancements in MRI segmentation, PET/CT radiomics, and graph neural networks for disease diagnosis. She actively contributes to interdisciplinary research, integrating computational methods with clinical data for precision medicine.
Dr. Khoa Phan is a Senior Lecturer in the Department of Computer Science and Information Technology at La Trobe University, Australia. He holds an ARC DECRA Senior Research Fellowship (2020-2023) and has held prior positions at UCLA, Monash University, and others. His academic background includes a B.Eng. (UNSW), two M.Sc. degrees (University of Alberta and Caltech), and a Ph.D. in Electrical Engineering from McGill University. Dr. Phan's research focuses on optimizing next-generation communication networks, particularly in wireless communications, IoT, satellite systems, and machine learning applications. He has secured significant grants, including ARC Discovery Projects and industry partnerships. His work emphasizes secure cyber-physical systems, federated learning, and edge computing. He has received prestigious awards such as the ARC DECRA and Atwood Fellowship. His research spans over 100 publications, with contributions to areas like OTFS modulation, secure satellite communications, and graph-based anomaly detection. He actively supervises PhD students and collaborates internationally, including initiatives to strengthen ties between La Trobe University and Vietnamese institutions. Grants include ARC Discovery Projects (totaling $1.3M+), CRC SmartSAT, and industry scholarships. His work addresses energy efficiency, secure resource allocation, and AI-driven solutions for 5G/6G networks and the metaverse.
Professor Sarah Johnson is a distinguished academic in the School of Engineering at the University of Newcastle, specializing in Electrical and Computer Engineering. She holds a PhD in Electrical Engineering from the same institution and has been awarded prestigious fellowships including an ARC Future Fellowship. Her research applies engineering solutions to digital information processing and error correction coding, with significant applications in secure communications and biomedical technologies. Her research interests span: Signal processing for secure data transmission Error correction codes for reliable communication systems Biomedical applications of digital signal processing Quantum-enabled secure communications Internet of Things communication protocols Her publications primarily focus on information theory, wireless communication systems, and biomedical engineering. Recent work shows strong emphasis on index coding optimizations, quantum cryptography implementations, and biomedical signal processing techniques for neuroimaging applications. Significant awards include: NSW Premier's Prize for Excellence (2017) Pro Vice-Chancellor's Research Excellence Award (2007) Professor Johnson has secured multiple ARC Discovery grants and industry-sponsored projects, including collaborations with Quintessence Laboratories on quantum key distribution. She co-founded HunterWISE to promote women in STEM fields and has supervised numerous graduate students across engineering disciplines. She leads interdisciplinary collaborations with biomedical researchers on rehabilitation technologies and neuroimaging analysis, developing systems to monitor recovery processes and brain activity patterns.
Dr. Usman Naseem is a Lecturer in Computing at Macquarie University’s School of Computing, Australia. Previously, he held academic roles at James Cook University and research fellowships at the University of Sydney and the University of South Australia. He earned his PhD in Computer Science from the University of Sydney and has over 10 years of industry experience in technical and leadership roles. Research Interests: NLP, multimodal analysis, and social computing, with focuses on socially aware methods for applications like cyber informatics, online sarcasm/opinion mining, low-resource language processing, and health informatics. He actively contributes to top-tier venues like ACL, EMNLP, and SIGIR. Grants & Awards: Recipient of the IEEE Transactions Best Paper Award (2022), DAAD AINet Fellowship (2023), and the Rising Star in AI Fellowship. His research has been funded by grants including Macquarie University’s MQRAS and Data Horizons initiatives. Recent Activities: Leads projects on combating AI-generated misinformation (VaxGuard grant), and has published extensively on topics like health misinformation detection, multimodal learning, and bias mitigation in AI systems. He is currently recruiting PhD and Master’s students in NLP, multimodality, and AI for social good. Labs & Collaborations: Affiliated with Macquarie’s Data Horizons Research Centre, Future Communications Research Centre, and Frontier AI Research Centre. Collaborates internationally on health informatics, social media analysis, and AI ethics.
Dr. Vera Miloslavskaya is a Lecturer in Information Technology at the University of New England's School of Science and Technology. She holds a PhD from Peter the Great St. Petersburg Polytechnic University and specializes in error-correction coding and AI applications for telecommunications. Research Focus: Miloslavskaya develops machine learning-enhanced coding schemes for next-generation wireless systems. Her work on neural network-based polar coding and graph neural network applications in MIMO detection aims to improve reliability and efficiency in 6G networks. She maintains collaborations with the University of Sydney where she previously worked as a Postdoctoral Research Associate. Recognition: Awarded the IEEE Transactions on Communications Exemplary Reviewer (2022) and multiple Russian academic awards including the Gold Medal of the Russian Academy of Science (2012).
Adjunct Professor Shuai Wan is affiliated with the School of Engineering at RMIT University (City Campus, Australia). His research focuses on computer vision, machine learning, 3D point cloud compression, neural video coding, and remote sensing . Key contributions include lightweight deep learning frameworks for image/video compression, spatio-temporal context models for point clouds, and adaptive quantization techniques. Research Outputs Insights : Wan’s work spans 2024–2025 , emphasizing end-to-end deep learning solutions for challenges in Exemplar-based colorization with semantic attention Rendering-oriented 3D point cloud compression Slimmable video codecs with variable bitrate G-PCC standard enhancements for quantization and entropy coding Adversarial example detection in remote sensing Technical Domains : His articles intersect artificial intelligence, signal processing, and computer graphics , with applications in cloud gaming, SAR systems, and industrial data compression. Methods include transformers, attention networks, and 3D convolutional architectures .
Lim Mei Kuan is a Senior Lecturer at the School of Information Technology, Monash University Malaysia. She holds a PhD in Computer Vision from Universiti Malaya and has conducted post-doctoral research in Artificial Intelligence. Her career includes roles as a researcher at MIMOS Berhad (2004-2007) and visiting researcher at Kingston University (2012-2013). Education: BSc (First Class Honours) in Computer Science, Universiti Malaysia Sarawak (2007) PhD in Computer Vision, Universiti Malaya (2015) Research Interests: Her work spans computer vision, machine learning, and their applications in smart manufacturing and digital health. Current projects include social media analytics for mental health monitoring, anomaly detection in manufacturing, and collaboration on clinical teletherapy systems. She actively explores swarm intelligence and deepfake detection technologies. Grants & Collaborations: DELTA: Inclusive Teletherapy (2022-2024) ADSM: Anomaly Detection for Smart Manufacturing (2022-2023) Sense-ED: Eating Disorder Relapse Detection (2021-2022) Awards: ITEX 2022 Silver Award for Self-Mind mental health app Labs & Teams: Active contributor to interdisciplinary projects with industry partners, focusing on AI-driven solutions for healthcare and manufacturing sectors.
T M Indra Mahlia , a Distinguished Professor at the School of Civil and Environmental Engineering , University of Technology Sydney (UTS), leads cutting-edge research in sustainable energy systems and environmental engineering. As a core member of the Centre for Technology in Water and Wastewater and the Centre for Advanced Modelling and Geospatial Information Systems , he bridges engineering innovation with practical climate solutions. PhD from University of Malaya (Kuala Lumpur, Malaysia) Fluency in English, Indonesian, Malay, and Achinese for peer review His research spans Techno-Economic Analysis , Circular Economy , and Water-Energy Nexus challenges, supported by over $5 million in grants. His work focuses on: Hydrogen energy systems optimization Advanced materials for energy storage Low-cost water purification technologies Sustainable biodiesel production Thermal management innovations As a Highly Cited Researcher (Clarivate Analytics, 2017-2022) and The Australian 's 2019/2025 Sustainable Energy Leader , he mentors future researchers - notably guiding two Highly Cited PhD students ( H.C. Ong and A.S. Silitonga ). His publications across 2024-2026 demonstrate technical advancements in: Hydrogen carrier systems Microalgae-derived lubricants High-entropy alloy corrosion resistance Artificial neural network optimization Phase change material thermal sinks Biohydrogen production pathways
Shui Yu is a Professor of the School of Computer Science in the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS), where he also serves as the Deputy Chair of the UTS Research Committee. His academic career spans over 20 years in Australia and 7 years in China, with additional teaching experience in Hong Kong and Indonesia. He has developed more than 10 units in cybersecurity, computer science, data analytics, and computer games, serving as the Course Director for Computer Science undergraduate programs. Professor Yu's research interests center on cybersecurity, privacy, networking aspects of Big Data, and applied mathematics for computer science. He pioneered the field of 'networking for big data' in 2013 and edited the seminal book 'Networking for Big Data' published in 2015. His work has practical applications in industry, including Amazon Cloud's auto-scale strategy against distributed denial-of-service attacks. Current research focuses include privacy and security concerns associated with big data, security issues in smart grids, anonymous transactions on Blockchain, and anonymous communication for web browsing privacy. Analysis of his recent publications reveals a strong research trajectory spanning cybersecurity, privacy-preserving technologies, networking for big data, and applied mathematics. His work shows increasing focus on quantum-resistant cryptography, federated learning security, and adversarial robustness in AI systems. The interdisciplinary nature of his research bridges theoretical foundations with practical applications in IoT, blockchain, and cloud environments. Fellow of IEEE (2023) Distinguished Lecturer of IEEE Communications Society (2018-2021) Distinguished Visitor of IEEE Computer Society (2022-2024) Professor Yu has secured numerous research grants from the Australian Research Council, including current projects on privacy and fairness in high intelligence models (DP240100955), improved security and privacy for online platforms (LP220200808), and secure blockchain for financial applications (LP220100453). He has served on editorial boards of multiple IEEE journals including IEEE Communications Surveys and Tutorials, IEEE Communications Magazine, and IEEE Internet of Things Journal. His service extends to organizing major conferences such as IEEE Globecom 2015 and IEEE INFOCOM 2016-2017.
Rasool Keshavarz is a Senior Research Fellow at the University of Technology Sydney (UTS), affiliated with the School of Electrical and Data Engineering within the Faculty of Engineering and Information Technology. He holds a Ph.D. in Telecommunications Engineering from Amirkabir University of Technology, Iran. His research focuses on RF/microwave/mm-wave systems, antennas, sensors, and electromagnetic compatibility (EMC), with a strong emphasis on applications in precision agriculture and IoT. He leads projects like 'Sustainable Sensing for Precision Agriculture' (funded by Food Agility-CRC and NTT) and collaborates with Zetifi Company on rural connectivity solutions. Education: Ph.D. in Telecommunications Engineering (Amirkabir University of Technology), M.Sc./B.Sc. details not specified. Professional roles at UTS include Senior Research Fellow (2023–present), Postdoctoral Research Fellow (2022–2023), and Visiting Fellow (2019–2021). He teaches courses such as 'Introduction to Satellite Communication and Sensing' and supervises graduate projects in 5G antennas, energy harvesting, and sensor design. Research interests span metamaterials, wireless power transfer, agricultural sensing systems, and antenna design for IoT. Key projects involve developing compact, low-cost RF systems for rural connectivity and sensor PCBs for soil quality analysis. His work integrates AI-driven data fusion strategies and advanced electromagnetic modeling. Recent publications highlight innovations in THz beamforming, soil permittivity spectroscopy, and reconfigurable antennas for smart agriculture. He is a technical leader in EMC compliance testing and contributes to industry partnerships for agricultural technology advancements.
Dr. Ruben Laukkonen is a Senior Lecturer (Associate Professor equivalent) in cognitive science and computational neuroscience at Southern Cross University, with honorary fellowships at Vrije Universiteit Amsterdam and The University of Queensland. His award-winning research integrates neural, psychological, and computational approaches to study meditation, insight, and consciousness. Research highlights: Bayesian models of advanced meditation states Mechanisms of true/false insight experiences Neural correlates of consciousness using EEG/Machine Learning Chief Investigator on Australia's largest psychedelic clinical trial ($4M funding) He publishes in leading journals, speaks internationally, and consults for the OECD on AI and education. His work explores rare states of consciousness across multiple explanatory levels, from neural dynamics to subjective phenomenology. Laukkonen received the 2024 Mid-Career Researcher Award for Research Excellence.
Qinglong Han is the Pro-Vice Chancellor (Research Quality) and a Distinguished Professor at Swinburne University of Technology in Melbourne, Australia. He previously held academic and leadership roles at Griffith University and Central Queensland University. His research focuses on networked control systems, multi-agent systems, time-delay systems, smart grids, and unmanned vehicles. He is a Fellow of IEEE, IFAC, and multiple other institutions, and has received prestigious awards including the IEEE Dr.-Ing. Eugene Mittelmann Achievement Award (2024) and Norbert Wiener Award (2021). His research interests span control engineering, applied mathematics, and artificial intelligence. Notable contributions include secure platooning control for autonomous vehicles, resilient control under cyber-physical threats, and optimization of industrial systems. He leads editorial roles in journals like IEEE Transactions on Industrial Informatics and IEEE/CAA Journal of Automatica Sinica. His work emphasizes interdisciplinary applications in smart grids, robotics, and industrial automation. Dr. Han has supervised numerous PhD students in areas like networked control and vehicle dynamics. He has secured grants from ARC and NSFC for projects on networked control systems and renewable energy integration. His achievements include multiple best paper awards and recognition as a Clarivate Highly Cited Researcher in Engineering and Computer Science.
Dr. Will Harrison is an Honorary Research Fellow at the School of Psychology , The University of Queensland , Australia. His research focuses on understanding the neural and computational mechanisms underlying visual perception, attention, and working memory. Academic Rank: Research Fellow Email: w.harrison@psy.uq.edu.au Research Interests: Dr. Harrison investigates how the human visual system integrates information across eye movements, the role of natural image statistics in perception, and the neural coding of orientation and spatial uncertainty. His work bridges experimental psychology, computational neuroscience, and psychophysics. Publications (2019–2025): Recent studies examine transsaccadic attention allocation , prior expectations in visual neural tuning , confidence judgments in multisensory decisions , and visual crowding mechanisms . His computational models often incorporate gain fields, Bayesian inference, and feature binding dynamics.
Dr. Blake Saurels is a Postdoctoral Research Fellow at the School of Psychology within the Faculty of Health, Medicine and Behavioural Sciences at The University of Queensland. He completed his PhD in Psychology at UQ in 2022 with a thesis titled 'The perceptual and neural consequences of different types of prediction'. His educational background includes a Bachelor (Honours) of Psychology with First Class Honors (Hons Class 1A) from The University of Queensland. Dr. Saurels' research focuses on visual perception, neural correlates of vision, and cognitive neuroscience. His work examines predictive processing in the brain, face recognition mechanisms, binocular rivalry phenomena, and visual imagery. His recent publications reveal a strong interest in how the brain processes visual information, particularly regarding face pareidolia, neural prediction errors, and the relationship between visual imagery and perception. Analysis of his 15 most recent publications shows consistent exploration of neural and perceptual mechanisms related to prediction, visual processing, and imagery. His work frequently employs EEG methodology and experimental paradigms to examine how expectations shape perception and neural responses. Dr. Saurels is currently available for supervision and serves as an Associate Advisor for a PhD project titled 'The Neural Encoding of Naturalistic Faces for Social Perception,' working alongside Dr. Amanda Robinson, Associate Professor Alan Pegna, and Associate Professor Jess Taubert.
Dr. Andrew Burrell is a Senior Lecturer in Visual Communication at the University of Technology Sydney's Faculty of Design and Society. He is a practice-based researcher and educator exploring virtual and digitally mediated environments as sites for the construction, experience, and exploration of memory as narrative. His work sits at the intersection of digital media, virtual reality, and environmental humanities, with a particular focus on more-than-human ecologies and queer approaches to virtual environments. Andrew's research investigates the relationship between imagined and remembered narrative and how the multi-layered biological and technological encoding of human subjectivity may be portrayed within, and inform the design of, virtual environments. His networked projects in virtual and augmented environments have received international recognition, with recent works including "Twice, again" and "overGround:underStory," which explore the role of memory and forgetting in machine-mediated spaces and more-than-human encounters between physical and virtual ecologies. His creative practice informs his traditional research outcomes, which include publications in journals such as the Leonardo Electronic Almanac and Virtual Creativity. Andrew is particularly interested in how emerging and speculative technologies are implicated in more-than-human ecologies, and he uses creative practice to research and understand the complexities of these technologies. Andrew is a member of the UTS Visualisation Institute, a multidisciplinary research group focused on the creation of data visualizations, stories, and immersive experiences, and the School of Design's Critical Visualisation research group. He has received funding from various sources including the Australian Research Council (ARC) Discovery Projects and Create NSW. Research Interests Virtual and Augmented Reality as narrative spaces Memory construction in digital environments More-than-human ecologies and digital storytelling Queer approaches to virtual embodiment Creative applications of machine learning and AI Data visualization and environmental storytelling Accessibility and ethics in digital humanities Notable Projects Twice, again : Examines the role of memory and forgetting in machine-mediated spaces overGround:underStory : Explores entangled networks between physical and virtual ecologies Waves of Words : ARC Linkage initiative investigating language movement in pre-colonial times can't buy me love : A virtual environment collaboration with Amala Groom Layered Horizons : A geospatial humanities research platform Scientific Recognition MMUVE IT - Inter-Arts Office Australia Council Grant (2008) International presentations at conferences including ISEA (International Symposium on Electronic Art) Teaching and Supervision Andrew is an advocate for studio-based learning in which students design solutions to real-world questions through iteration and experimentation. He considers design as an anchor for interdisciplinary practice and regularly brings cross-disciplinary perspectives into his teaching. He currently supervises five PhD and master's students, with an interest in working with students at the intersection of traditional and practice-based research approaches. Research Themes in Recent Publications Andrew's recent publications demonstrate a consistent focus on the intersection of virtual environments, narrative construction, and ecological thinking. His work explores how digital technologies can be used to create new forms of storytelling that acknowledge our entanglement with non-human entities. There's a strong emphasis on ethical considerations in digital design, particularly regarding accessibility and representation. His research also investigates the application of machine learning technologies in creative practice, examining both their potential and limitations for representing human experience.
