جستجوی استاد راهنمای دانشگاهی

Dr. Howe Zhu is a Lecturer of Interactive Design at the University of Sydney's School of Architecture, Design and Planning. He holds a PhD in Computer Science from UTS (2022) and a BE in Biomedical Engineering from the University of Sydney (2017). His research focuses on human-centric technologies, including metaverse systems, assistive technologies for visually impaired individuals, and brain-computer interfaces. Education: PhD in Computer Science, UTS, 2022 BE in Biomedical Engineering (Mechatronics), University of Sydney, 2017 Research interests span virtual/augmented reality, spatial audio processing, and sensory augmentation systems. Recent work emphasizes auditory interfaces for navigation assistance and stress effects on neurotechnology. His publications explore metaverse infrastructure, binaural sound rendering, and human factors in assistive technologies. Notable contributions include studies on brain-computer interfaces in metaverse systems, acoustic touch for vision impairment, and spatial memory enhancement through auditory cues. His work bridges biomedical engineering with interactive design to create inclusive technologies.

• Virtual Reality
• Human-Computer Interaction
• Assistive Technologies
• +۵ مورد دیگر

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.

• Computer Science
• Artificial Intelligence
• Robotics
• +۱۶ مورد دیگر

Dr. Daria Anderson is a Lecturer in the School of Biomedical Engineering at The University of Sydney. Her work focuses on epilepsy, neurostimulation technologies, and computational models of neural activity. She advises three current PhD students: Josh MOSSE-ROBINSON, Michael SUN, and Joshua WOOLEY. Her research integrates engineering principles with clinical neuroscience to improve seizure prediction, neurostimulation efficacy, and patient-specific treatment outcomes. Key projects include analyzing circadian rhythms' impact on epilepsy therapies and developing automated tools for intracranial electrode localization. Education details are not explicitly provided, but her work spans computational neuroscience, biomedical device development, and clinical neurology. Research grants include a 2024 project on structural-functional decoupling in epilepsy, aiming to identify biomarkers for network restructuring. Anderson’s publications emphasize DBS optimization, seizure propagation pathways, and machine learning applications in neuroimaging. Recent work highlights closed-loop stimulation strategies and the role of structural connectivity in treatment outcomes for epilepsy and Tourette syndrome. No scientific awards are listed, though her contributions are significant in neuroengineering and clinical neuroscience. Labs/Teams: Her research aligns with the School of Biomedical Engineering and collaborations with the Brain and Mind Centre. Future directions include predictive modeling of seizure dynamics and advancing personalized neurostimulation therapies.

• Epilepsy Research
• Neurostimulation
• Deep Brain Stimulation (DBS)
• +۳ مورد دیگر

Dr. Jia Liu is a Research Fellow at the Centre for Biomedical Sensing and Informatics , affiliated with the School of Biomedical Engineering at the University of Sydney . As a member of the University of Sydney Nano Institute , her work bridges neuro-engineering, brain-computer interfaces, and physiological signal analysis. Research Fellow, School of Biomedical Engineering, University of Sydney Member, University of Sydney Nano Institute Research Interests: Cognitive Enhancement through physiological signal analysis Advanced Brain-Computer Interface (BCI) development Neuro-Engineering applications in real-world scenarios Mobile Brain/Body Imaging (MoBI) system design Human orientation skills and therapeutic interventions Cognitive workload and physical fatigue interplay Publication Trends: Recent work focuses on graph neural networks for drowsiness detection, ERP-based inattentional blindness classification, and virtual global landmakr applications in spatial learning. Her methods integrate MoBI systems, VR, and real-time signal processing. Scientific Contributions: Published in prestigious journals (Nature Group, IEEE Transactions) Pioneering work on cognitive workload assessment using optical tomography Developed parameter-sharing neural networks for human state estimation Erratum corrections demonstrating rigorous research methodology Laboratory Affiliation: Works within the Centre for Biomedical Sensing and Informatics , leveraging interdisciplinary approaches to translate neuro-engineering research into practical applications.

• Neuro-Engineering
• Brain-Computer Interfaces
• Cognitive Neuroscience
• +۵ مورد دیگر

Professor Lina Yao is Senior Principal Research Scientist and Science Lead for Translational Machine Learning at CSIRO's Data61, with conjoint appointments at UNSW, Macquarie University, and UTS. Her research develops explainable machine learning methods for recommender systems, computer vision, and neurotechnology applications. Professor Yao has received numerous honors including the CORE Outstanding Research Contribution Award and recognition as a Clarivate Highly Cited Researcher. She leads multiple ARC-funded projects on human-AI collaboration frameworks.

• Machine Learning
• Recommender Systems
• Brain-Computer Interfaces
• +۲ مورد دیگر

Joanne Bennett is a Senior Lecturer in Psychology at the School of Behavioural and Health Sciences, specializing in Traffic Psychology, Cognitive Psychology, and Public Health. Her research spans hazard perception, cognitive functioning in road users, neuropsychological deficits, and the psychological impacts of technology on behavior. She has published extensively on topics including vehicle automation, mobile phone distractions, and mental health implications of trauma and addiction. Her work focuses on systematic reviews and meta-analyses, addressing critical issues such as aging drivers, young driver safety, and disordered screen use. She collaborates widely, contributing to interdisciplinary studies in human factors, rehabilitation science, and legal aspects of transportation. Key themes in her research include improving road safety through behavioral insights, mitigating risks associated with emerging technologies, and understanding mental health challenges in vulnerable populations. No scientific awards were listed, though her contributions to traffic psychology and public health are notable.

• Traffic Psychology
• Cognitive Psychology
• Public Health
• +۳ مورد دیگر

Levin Kuhlmann is an Associate Professor at Monash University's Department of Data Science & AI, affiliated with the Victorian Heart Institute. He holds a PhD in Cognitive and Neural Systems from Boston University. His research focuses on applying machine learning and computational neuroscience to digital health, neural engineering, and neuroimaging, with a strong emphasis on epilepsy and anesthesia modeling. Key research interests include data science, signal processing, and control theory applied to clinical challenges like seizure prediction and brain-state analysis. He leads projects such as the CSIRO Next Generation AI system for NDIS coaching and Neurodesk, a collaborative neuroimaging tool. His work aligns with UN Sustainable Development Goals related to health and innovation. Education: PhD in Cognitive and Neural Systems, Boston University. Awards: Includes the Australian Post-Graduate Award (2001), Best Paper Honorable Mention (ACM 2021), and Boston University Doctoral Fellowship (2001–2006). Projects: Over 8 active projects, including AI-augmented healthcare systems, high-performance brain imaging, and epilepsy monitoring with wearable devices. Dr. Kuhlmann has published extensively on seizure prediction, neural dynamics, and reproducible neuroimaging. His research has been featured in media such as The Wire and ZDNet, highlighting breakthroughs in epilepsy diagnosis and AI applications.

• Digital Health
• Machine Learning
• Signal Processing
• +۶ مورد دیگر

Lachlan Robb is a legal academic at Queensland University of Technology's Faculty of Business & Law, School of Law, specializing in the intersection of law and emerging technologies. His research primarily focuses on blockchain applications, digital asset regulation, and the legal implications of technological innovation. Robb's research interests span blockchain law, technology regulation, digital assets, regulatory overlap, smart cities jurisprudence, semiotics of law, and property law as it relates to technology. His work demonstrates a consistent focus on how legal frameworks must adapt to technological advancements, particularly in the financial and urban development sectors. He has developed a distinctive approach examining both the technical and cultural dimensions of technology regulation. An analysis of Robb's recent publications reveals a clear trajectory in his research, moving from foundational studies on blockchain technology's legal implications toward more nuanced examinations of specific applications like brain-computer interfaces and autonomous vehicles. His work consistently addresses the tension between innovation and regulation, often employing interdisciplinary methods drawing from legal theory, semiotics, and socio-technical studies. Regulatory Overlap 2011-2021: A Systematic Quantitative Literature Review (2022) Smart cities as panopticon: Highlighting blockchain's potential for smart cities through competing narratives (2021) Professions and expertise: How machine learning and blockchain are redesigning the landscape of professional knowledge and organization (2018-2020) Robb has established productive research collaborations across multiple institutions, frequently working with Felicity Deane, Kieran Tranter, and John Flood. His research has practical implications for policymakers, particularly in the areas of digital asset regulation and smart city development. His recent work on sustainable development goals integration in legal education demonstrates his commitment to addressing global challenges through legal education reform.

• Blockchain Law
• Technology Regulation
• Digital Assets
• +۵ مورد دیگر

Dr Anita Sathyanarayanan is a Postdoctoral Research Fellow at the Centre for Genomics and Personalised Health, University of New South Wales. Her work focuses on integrating multi-omics data to understand complex diseases such as psychiatric disorders, cancers, and infectious diseases. She specializes in epigenetic mechanisms, genetic risk prediction, and translational biomarker discovery. Key research areas include: Epigenetic effects of trauma and childhood adversity Genetic links between blood analytes and severe diseases Multi-omics approaches for PTSD and cancer subtyping Pharmacogenetic optimization of lithium therapy Her methodological contributions span bioinformatics tool development for omics integration, ChIP-Seq analysis, and exome sequencing interpretation. Current projects emphasize personalized medicine applications in oncology and mental health. Lab affiliations: Centre for Genomics and Personalised Health (UNSW)

• Genomics
• Epigenetics
• Personalised Health
• +۴ مورد دیگر

Prof Yan Li is a full Professor of Computing at the University of Southern Queensland (UniSQ) , Australia, serving as Associate Head (Research) and Chair of the Research Committee in the School of Mathematics, Physics and Computing . She holds a PhD from Flinders University and has led the UniSQ AI Research group since 2018. Her research focuses on Artificial Intelligence, Machine Learning, Big Data, Network Security, Signal/EEG Processing , and Internet Technologies. With over 250 publications and $3.5M in grants, Prof Li has supervised dozens of PhD students. She is renowned for awards like the 2012 Australia National Teaching Citation and 2008 Queensland Smart Women Award. Her work bridges healthcare and technology, including EEG-based diagnostics for neurological disorders (e.g., Alzheimer’s, schizophrenia) and cybersecurity for IoT systems. She also contributes to telehealth systems and data-centric intelligent computing initiatives. Prof Li chairs UniSQ’s Academic Board Executive Committee and is a member of the Australian Research Council’s College of Experts. Her interdisciplinary projects integrate machine learning, signal processing, and healthcare analytics to address global challenges in health and security.

• Artificial Intelligence
• Machine Learning
• Big Data
• +۴ مورد دیگر

Dr. Tobias Low is a Senior Lecturer in Mechanical Engineering (Mechatronics) at the School of Engineering, University of Southern Queensland. He holds a BEng and PhD from Queensland institutions. With a career spanning over 14 years at USQ, he specializes in Mobile Robotics, Computer Vision, and Mechatronics. His research integrates autonomous systems, tactile sensing, and robotic navigation in agricultural and industrial contexts. Key research areas include robotic obstacle avoidance, deep learning applications in vision systems, and sensor technologies for precision agriculture. He has published extensively on topics like tactile feedback in robotic meat processing, stereo vision for leaf segmentation, and autonomous robot navigation in livestock environments. His work often bridges mechanical engineering with interdisciplinary fields such as nanotechnology (e.g., biodegradable nanofiber materials for fertilizer delivery) and environmental monitoring. Notable projects include developing tyre strain sensing systems for slip detection and integrating WSNs with mobile robots for agricultural applications. Dr. Low’s contributions span theoretical advancements (e.g., transfer learning in crack detection) and applied engineering solutions, reflecting a commitment to practical robotics and sensor innovation.

• Mobile Robotics
• Computer Vision
• Machine Learning
• +۷ مورد دیگر

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

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

Priya Rani is a Lecturer in the School of Engineering at RMIT University. Her research focuses on interdisciplinary areas including Biomedical Engineering, Artificial Intelligence, and Neurosciences. She actively supervises research projects such as developing peripheral electronics for neural recording systems and applying machine learning for clinical delirium diagnosis. Dr. Rani’s work bridges computational methods with healthcare applications, emphasizing robust machine learning models and medical imaging analysis. She is affiliated with RMIT’s City Campus and contributes to advancing technologies for sustainable and intelligent systems. Research Interests: Her primary areas include computational theory, biomedical engineering, and AI-driven solutions for healthcare challenges. Notable projects involve semantic segmentation using attention-augmented networks and damage monitoring in advanced materials. Dr. Rani’s research trends highlight machine learning robustness, medical image analysis, and smart home technologies for aging populations. Supervision Focus: Neural recording systems, clinical AI applications Key Projects: Cortical neural interfaces, delirium prediction algorithms Technical Expertise: Machine learning, image processing, medical diagnostics Collaboration and Impact: Her work addresses real-world challenges through interdisciplinary approaches, with publications spanning medical IoT, nanosensors, and composite materials analysis. Dr. Rani’s contributions emphasize practical applications of AI and computational methods in healthcare and engineering domains.

• Biomedical Engineering
• Paediatrics and Reproductive Medicine
• Computation Theory and Mathematics
• +۳ مورد دیگر

Dr. Sorel De Leon Vergara is a Research Fellow in the School of Engineering at RMIT University, specializing in biomedical engineering and materials science. His work focuses on developing biomedical devices, particularly cortical implants and brain-machine interfaces. Currently, he is advancing carbon fiber electrode technology for cortical recording. With 4+ years of experience, he has expertise in in vivo/in vitro testing of implants and proficiency in programming languages like Python, C, MATLAB, and JavaScript. Research interests include biomedical devices, nanotechnology, and condensed matter physics, with a focus on neural engineering and biomaterials. He supervises projects such as the development of peripheral electronics for cortical neural recording systems. Key Skills: Electronics engineering, device design, impedance spectroscopy, material characterization. Current Projects: Carbon fiber electrode development for neural recording. Collaborations: Interdisciplinary research in biomaterials and neural interfaces. No scientific awards have been listed. His contributions span peer-reviewed journals, with recent work published in Bioengineering & Translational Medicine and ACS Applied Materials and Interfaces .

• Biomedical Engineering
• Materials Engineering
• Nanotechnology
• +۴ مورد دیگر

Yuzhe Tian is a Part-Time Lecturer at the School of Computing, Macquarie University, within the Faculty of Science and Engineering. His research focuses on interdisciplinary applications of machine learning, including anomaly detection in industrial IoT systems, sleep stage recognition via graph networks, and brain-computer interface (BCI) technologies. He holds a Doctor of Philosophy and has published extensively in top-tier conferences and journals since 2019. Research interests include real-time BCI systems using geometric learning, optimization of neural networks (e.g., model pruning and quantization), and healthcare applications like sleep analysis through graph attention networks. His work bridges computational methods with practical challenges in biomedical engineering and industrial automation. Yuzhe has collaborated on projects leveraging multi-view learning for anomaly detection and swarm intelligence algorithms (e.g., Krill Herd Algorithm). His publications span topics from lightweight BCI frameworks to cybersecurity in IIoT environments, demonstrating a strong focus on both theoretical advancements and real-world implementation.

• Anomaly Detection
• Industrial Internet of Things (IIoT)
• Sleep Analysis
• +۵ مورد دیگر