جستجوی استاد راهنمای دانشگاهی

Levin Kuhlmannمشاهده پروفایل

دانشیار

• Digital Health
• Machine Learning
• Signal Processing
• +۶ 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.

• Blockchain Law
• Technology Regulation
• Digital Assets
• +۵ 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.

• Genomics
• Epigenetics
• Personalised Health
• +۴ 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)

• Mobile Robotics
• Computer Vision
• Machine Learning
• +۷ 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.

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

Yuzhe Tianمشاهده پروفایل

مدرس پاره‌وقت

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

• Biomedical and bioinspired engineering
• Optical/Infrared/mm-Wave/T-ray vision systems
• Game theory and information theory
• +۸ مورد دیگر

Professor Derek Abbott is a faculty member in the School of Electrical and Mechanical Engineering at the University of Adelaide, within the Faculty of Sciences, Engineering and Technology. He holds the academic rank of Professor and is actively involved in supervising Masters and PhD students. His research interests span a wide range of interdisciplinary fields, including biomedical engineering, optical systems, game theory, quantum mechanics, stochastic phenomena, computational neuroscience, and forensic engineering. Professor Abbott has also contributed to energy systems optimization and space-based sensor technology. His recent work includes studies on neural network robustness, gravitational redshift measurement, and cardiovascular disease prediction using machine learning. His research often bridges theoretical concepts with practical applications in engineering and healthcare. Key research areas include the development of terahertz technology, bio-inspired engineering systems, and quantum game theory frameworks. He has published extensively on topics ranging from deep learning security to renewable energy grid optimization. His interdisciplinary approach integrates principles from physics, mathematics, and computer science to address complex real-world problems. Professor Abbott is eligible to supervise postgraduate research students and collaborates internationally on projects related to forensic genealogy, platonism in science, and energy storage solutions. His work often emphasizes the intersection of technology and societal challenges, such as climate change and healthcare innovation.

Sergio Rodriguez Mendezمشاهده پروفایل

پژوهشگر ارشد

• Knowledge Graphs
• Ontology Engineering
• Linked Data & Semantic Web
• +۷ مورد دیگر

Sergio Rodriguez Mendez is a Research Fellow in Knowledge Graph Engineering at the School of Computing, Australian National University. His work focuses on advancing ontology engineering, linked data, semantic web technologies, and their applications in domains like astronomy, brain-computer interfaces, and IoT. He is a member of the Australian Government Linked Data Working Group (AGLDWG) and the W3C Knowledge Graph Construction Community Group, and holds a senior role at the Software Innovation Institute (SII). His research interests include Knowledge Graphs, Ontology Engineering, Linked Data, Data Science, Machine Learning, Natural Language Processing, Brain-Computer Interfaces, IoT, Cloud/Fog/Edge Computing, and Software Engineering. He has contributed to frameworks like pathfinder for astronomical literature review and Doc-KG for document-to-KG conversion. Recent work emphasizes integrating large language models (LLMs) with knowledge graphs, such as AstroLLaVA for astronomical data unification and hybrid frameworks for entity linking. His publications span conferences like WWW, JCDL, and the ACM/IEEE Joint Conferences. He actively supervises research students and is involved in initiatives like the ASKG project for enriching scholarly knowledge graphs. His work addresses challenges in semantic data representation, automated query processing, and syntactic complexity reduction, with a focus on domain-specific applications in science and cultural heritage.

Mahesh Suryawanshiمشاهده پروفایل

مدرس

• Photovoltaics
• Renewable Energy Engineering
• Materials Science
• +۳ مورد دیگر

Mahesh Suryawanshi is a Senior Lecturer and ARC DECRA Fellow at the School of Photovoltaic and Renewable Energy Engineering (SPREE), UNSW Sydney. He holds a Ph.D. in Physics (Materials Science) from Shivaji University, India (2015), and completed postdoctoral work at Chonnam National University, South Korea (2015-2019) under the Brain Korea (BK)-21 Fellowship. Research Interests: Development of earth-abundant nanocrystals/quantum dots for solar energy conversion, surface ligand engineering, solution-processed thin films for photovoltaics and water splitting, and electrocatalytic systems for hydrogen production. His work emphasizes scalable synthesis methods and in-situ operando characterization. Grants & Awards: ARC DECRA Fellowship (2021-2024), Early Career Researcher Award (European Commission, 2019-2021), and multiple accolades including the Key Scientific Article Award (REGI, Canada) and Best Presentation Award at AFORE 2018. Scientific Awards: ARC DECRA Fellowship Early Career Researcher Award Best Presentation Award (AFORE 2018) Key Scientific Article Award (REGI) Supervision: Mentors HDR students including Xinyao Guo and Yiming Xia. Established the Multifunctional NanoMaterials and Devices subgroup at SPREE, fostering international collaborations. Labs & Teams: Affiliated with SPREE at UNSW, previously worked with Prof. Jin Hyeok Kim at Chonnam National University and Prof. Xiaojing Hao/Martin Green at UNSW. Focuses on scalable nanocrystal synthesis and device integration.

David Tsaiمشاهده پروفایل

مدرس ارشد

• Biomedical Engineering
• Microelectronics
• Neural Interfaces
• +۴ مورد دیگر

Dr. David Tsai is a Senior Lecturer at the University of New South Wales (UNSW), jointly appointed between Biomedical Engineering and Electrical Engineering. He leads the Biomedical Microsystems Lab , focusing on miniature microelectronic devices for brain-machine interfaces and subcutaneous biosensing. His research has been continuously funded by the NHMRC since 2013, including an ongoing Ideas grant for soft brain-machine interfaces. He has secured >$3.8M in total funding, with support from the Kavli Foundation and ARC Linkage Infrastructure Grants . His work has appeared in Nature Communications , Nature Nanotechnology , and IEEE Transactions on Biomedical Circuits and Systems . Scientific Recognition: IEEE EMBC Student Paper Award (twice) IEEE EMBC Best Papers Award NHMRC CJ Martin Fellowship (2013-2017) Kavli Foundation Postdoctoral Fellowship (2012-2013) Education: PhD in Biomedical Engineering (2012), UNSW MBiomedE (2007), UNSW BE (Software, First Class Honours) (2007), UNSW Research Themes: Development of ultra-dense microelectrode arrays for cellular-resolution electrophysiology, computational modeling of retinal responses to electrical stimulation, and standardization of neurotechnology data formats. His lab collaborates with industry partners like LeafLabs LLC , BlackRock Microsystems , and Contactile .

Kerry Houriganمشاهده پروفایل

استاد

• Fluid Dynamics
• Computational Fluid Dynamics
• Flow-Induced Vibration
• +۷ مورد دیگر

Kerry Hourigan is a Professor in the Department of Mechanical and Aerospace Engineering within the Faculty of Engineering at Monash University. He serves as Director of the Laboratory for Biomedical Engineering (LBE) and Co-Director of the Fluids Laboratory for Aeronautical and Industrial Research (FLAIR), highlighting his leadership in interdisciplinary fluid dynamics research. PhD in Astrophysics, Monash University (1981) BSc in Applied Mathematics and Physics, Monash University (1975) His research centers on fluid dynamics, particularly bluff body flows, flow-induced vibrations, and bio-inspired fluid systems. He combines experimental and computational approaches to study vortex dynamics, fluid-structure interactions, and novel engineering applications in biomedical and aeronautical contexts. His work spans fundamental fluid mechanics to applied engineering solutions. The recent articles highlight a strong trend in using data-driven and machine learning techniques to model and control complex fluid-induced vibrations, especially around bluff and elliptical bodies. His work integrates computational fluid dynamics with physical experiments, often targeting applications in energy harvesting and biomedical devices. The research consistently appears in top-tier journals such as Journal of Fluid Mechanics and Physics of Fluids , reflecting sustained scholarly impact. His primary scientific recognition is as a Fellow of Engineers Australia, awarded in 1996, acknowledging his contributions to engineering science and practice. Lead investigator on multiple ARC and NHMRC-funded projects, including studies on wake transitions, bioreactors for stem cell culture, and intracellular delivery systems. Actively supervises PhD students and collaborates internationally with institutions in France (CNRS), Denmark (Technical University), and the USA (Caltech). He leads the Laboratory for Biomedical Engineering (LBE) and co-directs the Fluids Laboratory for Aeronautical and Industrial Research (FLAIR), both fostering collaborative, cross-disciplinary research in fluid mechanics and biomedical applications.

Shaun Clohertyمشاهده پروفایل

مدرس

• Systems Neuroscience
• Neural Coding and Information Processing
• Biomedical Engineering
• +۴ مورد دیگر

Shaun Cloherty is a Lecturer in the Department of Biomedical Engineering at RMIT University's School of Engineering. He holds a BE (Hons) in Aerospace Avionics from Queensland University of Technology and a PhD in Biomedical Engineering from the University of New South Wales. His research focuses on systems neuroscience, integrating experimental and computational methods to understand neural coding, information processing in the brain, and the neural basis of perception and behavior. Cloherty has held research positions at UNSW, Australian National University, National Vision Research Institute, and Monash University. His teaching interests include undergraduate courses such as Image Processing, Computer Architecture, and Biomedical Signal Analysis, alongside postgraduate courses in Image Systems Engineering. He is open to supervising Masters and PhD students in areas like neural prosthetics, retinal implantation safety, and motor imagery recovery. Cloherty's research spans topics including retinal prosthesis safety, visual processing in primates, and the application of virtual reality in post-stroke rehabilitation. His work has been published in journals like *Progress in Biomedical Engineering* and *Journal of Neuroscience*. He actively contributes to collaborative projects and maintains a GitHub profile for software development related to mission control training and biomedical systems. His research projects include investigating motor imagery and VR for stroke recovery, developing chronic neural electrode arrays, and optimizing solar cell light-trapping designs. Cloherty's interdisciplinary approach bridges engineering and neuroscience, with a focus on translational applications in health technology.

• Artificial Intelligence
• Brain-Computer Interfaces
• Fuzzy Neural Networks
• +۸ مورد دیگر

Distinguished Professor Chin-Teng Lin is a leading academic at the University of Technology Sydney (UTS) , where he serves as Co-Director of the Australian AI Institute (AAII) and Director of the Computational Intelligence and Brain Computer Interface Lab . With a career spanning decades, he has pioneered advancements in artificial intelligence (AI) and brain-computer interfaces (BCI) , focusing on human-machine collaboration, wearable EEG systems, and neuroergonomics. School of Computer Science, UTS Co-Director, Australian AI Institute Director, Computational Intelligence and BCI Lab Lin’s research interests are deeply rooted in machine-intelligent systems , cognitive neuroscience , and human-centric AI . He has developed groundbreaking technologies like fuzzy neural networks (FNNs) in 1992, which revolutionized AI by integrating human-like reasoning. His work extends to multi-agent reinforcement learning for cybersecurity, wearable EEG devices for real-world applications, and neurofeedback interventions for chronic pain management. His research outputs include over 950 peer-reviewed publications , with a focus on deep learning , transformer models , and clustering algorithms . Articles like the MGRW-Transformer (2025) and Autonomous Clustering (2025) highlight his leadership in interpretable AI and parameter-free methods. Scientific awards and recognitions include: IEEE Fellow (2005) IFSA Fellow (2012) IEEE Fuzzy Systems Pioneer Award (2017) Outstanding Achievement Award, Asia Pacific Neural Network Assembly Lin has supervised 72 PhD candidates , 30 postdoctoral fellows , and 237 research Masters students since 1992, mentoring notable alumni such as Dr. Zehong Cao (ARC DECRA Fellow) and Prof. Chia-Feng Juang (IEEE Fellow). His funding portfolio includes $10M+ from the US Army Research Lab , $3.8M from the Australian Defence Innovation Hub , and $30.2M in industry collaborations .

• Machine Learning
• Artificial Intelligence
• Data Analytics
• +۹ مورد دیگر

Dr. Mukesh Prasad is an Associate Professor at the School of Computer Science , University of Technology Sydney (UTS). With expertise in Machine Learning , Artificial Intelligence , and Computer Vision , his research addresses applications in healthcare, biomedical science, and smart infrastructure. He holds a Ph.D. in Computer Science from National Chiao Tung University, Taiwan, and an M.S. in Computer and Systems Sciences from Jawaharlal Nehru University, India. Key research areas: Machine Learning, AI, Brain-Computer Interfaces, IoT, and Evolutionary Computation Industry experience: Principal Engineer at TSMC (2016-2017), Postdoctoral Researcher at National Chiao Tung University Dr. Prasad has secured competitive grants for AI applications in disaster response, conversational agents, and medical diagnostics. His work has been published in high-impact venues like IEEE , ACM Transactions , and Springer Nature , with over 200 peer-reviewed papers. He serves on editorial boards for journals including Frontiers in Neurorobotics and ACM Computing Surveys . Scientific Awards: Vice Chancellor Teaching and Learning Citation Award (2019) Alumni Fellowship for Ph.D. (2014) Golden Bamboo NCTU Fellowship (2010) Professional Members: IEEE (2011), ACM (2019)

• Brain-Computer Interface
• Stroke Rehabilitation
• Robotic Engineering
• +۳ مورد دیگر

Dr. Khairul Azlan A Rahman serves as Executive – Engineering at University of Wollongong Malaysia while maintaining active research roles as a part-time project researcher at GIRA and MENTARI research departments. His career bridges academic research and practical engineering applications in biomedical technology. His educational foundation includes a PhD in Electrical & Electronic Engineering from Universiti Tun Hussein Onn Malaysia (2020), Master in Engineering (Robotic) from UTHM (2011), Bachelor in Engineering (Power) from Universiti Teknologi Malaysia (2008), and Diploma in Electrical Engineering (Mechatronic) from UTM (2005). Dr. Rahman's research centers on Brain-Computer Interface (BCI) and Functional Electrical Stimulation (FES) systems for stroke and paraplegic rehabilitation. His work develops innovative control mechanisms that translate brain signals into physical movement assistance, creating pathways for patients to regain mobility through neurotechnology. This research sits at the critical intersection of biomedical engineering, robotics, and clinical rehabilitation, with strong emphasis on practical implementation of assistive devices. His scientific contributions have been recognized through multiple international awards: Special Award and Silver Medal from Saudi Arabia at IPITEx 2020 Silver Medal at Bangkok International Intellectual Property Exposition (IPITEx 2020) Gold Medals at NIICe2019 and iMIT 2019 Gold Medal at International Research and Innovation Symposium (RiSE 2018) Dr. Rahman actively contributes to academic development through postgraduate supervision, having served as Co-Supervisor for Medina exchange students at UTHM. His consultancy projects, including the Mechanical Robot Development for Ducting Cleaning initiative, demonstrate his ability to translate research into industrial applications. Current research activities continue through his part-time roles at GIRA and MENTARI where he explores next-generation rehabilitation technologies while maintaining freelance work in robotics and programming.