جست‌وجوی استاد و پژوهشگر

• Oral and Maxillofacial Surgery
• Telehealth
• Dental Radiology
• +۳ مورد دیگر

Dieter Gebauer is a Clinical Associate Professor at the School of Human Sciences, The University of Western Australia. His research focuses on oral and maxillofacial surgery, telehealth applications in healthcare, and innovative uses of deep learning in dental diagnostics. He has contributed to studies on surgical simulation techniques, post-pandemic telehealth sustainability, and automated dental imaging analysis. His work aligns with UN Sustainable Development Goals related to health and well-being. Research Interests: Advanced surgical planning using computer simulations Telehealth adoption in specialist care AI-driven dental diagnostics Maxillofacial surgical outcomes analysis COVID-19 impact on healthcare delivery Key Projects: "Mouth Guard Design & Facial Skeletal Profile Effects on Respiratory Function" (2010) Grant Activity: Australian & NZ Association of Oral & Maxillofacial Surgeons-funded research (2010) Lab & Teams: Collaborates with multidisciplinary teams in dental radiology and surgical innovation, though specific lab affiliations are not detailed.

Max Wardمشاهده پروفایل

مدرس

• Algorithms
• Data Structures
• Computational Biology
• +۳ مورد دیگر

Max Ward is a Lecturer at The University of Western Australia (UWA), affiliated with the School of Physics, Maths and Computing and the Australian Centre for RNA Therapeutics in Cancer. His roles include teaching in Computer Science and Software Engineering while conducting interdisciplinary research in algorithms, computational biology, and AI/ML. He holds a PhD from UWA (2019) and has held postdoctoral positions at the University of Adelaide and Harvard University. Education: PhD in Computer Science, UWA (2019) Postdoctoral Researcher at Harvard University (until Dec 2022) Research interests focus on algorithms, graph theory, RNA structure prediction, and machine learning applications in healthcare and cybersecurity. Key projects include developing RNA folding algorithms (e.g., JAX-RNAfold) and cybersecurity frameworks for network hardening. Grants: "Computational Creativity to Cross Cultural Frontiers" funded by Australia's Department of Foreign Affairs and Trade (2022–2024) Labs/Teams: Collaborates with the Australian Centre for RNA Therapeutics in Cancer and contributes to UWA's interdisciplinary research initiatives.

Subhas Chandra Mukhopadhyayمشاهده پروفایل

استاد

• Sensors and Sensing Technology
• Wireless sensor networks
• Internet of Things
• +۳ مورد دیگر

Professor Subhas Chandra Mukhopadhyay is a Professor of Mechanical/Electronics Engineering at the School of Engineering, Macquarie University, Australia. He serves as the Discipline Leader of the Mechatronics Engineering Programme and Director of International Engagement for the School of Engineering. Professor Mukhopadhyay is also the Founding Chair of the IEEE Instrumentation and Measurement Society New South Wales Chapter and the IEEE Sensors Council New South Wales Chapter. His research interests focus on: Sensors and Sensing Technology Wireless sensor networks Internet of Things applications Instrumentation systems Mechatronics and Robotics Drone technology Professor Mukhopadhyay's recent publications demonstrate a strong focus on sensor technology and IoT applications, with significant contributions in RFID systems, environmental monitoring, biomedical applications, and agricultural technology. His work bridges theoretical advances with practical implementations across multiple domains including healthcare, environmental monitoring, and smart city infrastructure, showing particular innovation in flexible electronics, neuromorphic computing, and wireless communication systems for diverse applications. His scientific achievements have been recognized with several prestigious awards: Best Performing Topical Editor 2016, 2017, and 2018 Certificate of Distinction Distinguished Lecturer of the IEEE Sensors Council (2017-2022) Professor Mukhopadhyay has authored/co-authored 14 patents, 10 books, and over 450 papers in international journals. He has organized over 20 international conferences including serving as General Chair for the IEEE Sensors Conference 2009 and 2021. His research is supported by multiple active projects including 'Affordable Imaging for Identification of Grass Seed Infestation in Australian Sheep' and 'Embedded sensing system for continuous crack monitoring in concrete pavements.' He leads research initiatives through the Smart Green Cities Research Centre and Advanced Drone Systems Research Centre at Macquarie University, fostering interdisciplinary collaboration across engineering disciplines and maintaining strong industry partnerships for practical implementation of research outcomes.

• Artificial Intelligence
• Natural Language Processing
• Network Security
• +۳ مورد دیگر

Pedro Arruda Faustini is a Postdoctoral Research Associate at the School of Computing at Macquarie University. His research focuses on artificial intelligence, natural language processing, and network security. Macquarie University, School of Computing His work spans adversarial machine learning, privacy-preserving AI, and voice assistant technologies. He has contributed to semantic reformulation in spoken QA systems and applied reinforcement learning to network security. Recent research includes differential privacy in language models and reconstruction attack analysis in federated learning. Key article trends include adversarial text analysis , privacy metrics , voice assistant design , and secure machine learning . Collaborations highlight interdisciplinary work in network function virtualization and speech interfaces . Pedro's work has been published in venues like Computational Linguistics , ACL , and INTERSPEECH , with notable contributions to fake news detection and non-functional requirements estimation . Advising and Collaborations : Collaborated with researchers like Dr. Mark Dras, Dr. Shaday Moshe Tonni, and Dr. Shlomo Berkovsky. Collaborations span computational linguistics, embedded systems, and network security domains.

• Photogrammetry
• Camera Calibration
• Optical Metrology
• +۴ مورد دیگر

Professor Mark Shortis is an Honorary Professor at RMIT University's STEM College and former Associate Professor in the School of Science. Specializing in photogrammetry, camera calibration, and optical metrology, he has contributed to aerospace model dynamics analysis with NASA, underwater marine ecology studies with the University of Western Australia, and solar energy research with the Australian National University. Retiring in 2020, he continues research in calibration algorithms for digital cameras. His career included roles as Associate Dean (Learning and Teaching) in RMIT's Faculty of Engineering and Dean (Academic Development) in the College of Science, Engineering, and Health. Research Interests: Close-range photogrammetry, underwater measurement systems, aerospace structural dynamics, solar concentrator characterization, and multi-camera calibration for industrial applications. His work bridges academic research with practical industrial and ecological challenges. Affiliations: RMIT University (Honorary Professor), former academic positions at University of Melbourne and RMIT across multiple faculties. Collaborations include NASA, CSIRO Marine Research, and Australian National University.

• Artificial Intelligence
• Image Processing
• Genetic Programming
• +۳ مورد دیگر

Gayan Wijesinghe is a Lecturer (Education Focused) at the School of Computing Technologies, RMIT University, Australia. His research interests include Artificial Intelligence, Image Processing, Genetic Programming, and Algorithmic Reasoning. He focuses on developing educational tools to enhance programming skills and cognitive development in students. His work spans algorithm design, evolutionary computation, and applications in computer vision and medical imaging. Research outputs include contributions to genetic programming, image classification, and optimization techniques. Notable projects explore trajectory creation for code writing and parameter optimization in object detection. Collaborations have involved institutions and researchers in evolutionary algorithms and software engineering. No scientific awards or grants are explicitly mentioned in the provided texts. His academic role emphasizes education-focused research and innovation in computing technologies.

• Mechanical Engineering
• Information and Computing Sciences
• Electrical and Electronic Engineering
• +۳ مورد دیگر

Dr. Chen Liu is a Research Fellow at the School of Engineering, RMIT University. His research focuses on energy systems, smart grids, optimization algorithms, and the integration of renewable energy technologies. He is particularly interested in battery energy storage systems, electric vehicle (EV) infrastructure, and machine learning applications in power systems. Dr. Liu has contributed to advancing SCADA alarm management, real-time grid monitoring, and multi-objective optimization techniques. He is open to supervising Masters and PhD students in areas such as accelerated learning for neural networks and big data applications. His work emphasizes practical solutions for sustainable energy challenges, including optimal placement of EV charging stations, solar-PV integration, and frequency control in grids with high renewable penetration. Dr. Liu's research also explores data-driven approaches for energy market forecasting and grid reliability enhancement. He has published extensively in top journals and conferences, addressing topics ranging from quantum genetic algorithms to distributed training of neural networks.

Roland Snooksمشاهده پروفایل

استاد

• Architectural Design
• Generative Design
• Robotic Fabrication
• +۵ مورد دیگر

Professor Roland Snooks is a leading academic in architectural design and computational methods, holding a Professorship at RMIT University's School of Architecture and Urban Design. He directs the RMIT Architecture Tectonic Formation Lab, focusing on algorithmic generative design and additive manufacturing. His work integrates swarm intelligence and multi-agent systems to explore new architectural possibilities. Snooks holds a PhD from RMIT and a Master in Advanced Architectural Design from Columbia University (Fulbright Scholar). He has taught at prestigious U.S. institutions including Columbia, University of Pennsylvania, and SCI-Arc. Co-founder of experimental practice Kokkugia (2004) and collaborator with Laura Harper in Snooks + Harper, his designs are in permanent collections at the Centre Pompidou, FRAC, and National Gallery of Victoria. Research interests include robotic fabrication, generative design systems, and material innovation. He actively supervises Masters and PhD students in architectural design synthesis, digital fabrication, and ecological aesthetics. Key projects include 'Vibrant Enmeshment: Aesthetics & Strategies for an Ecocentric Architecture' (2024) and 'Hybridised Metal Formation' (2023). His work bridges academic research with creative practice, emphasizing interdisciplinary collaboration and sustainable technologies.

Debaditya Acharyaمشاهده پروفایل

مدرس

• Computer Vision
• Machine Learning
• 3D Building Modelling
• +۳ مورد دیگر

Dr. Debaditya Acharya is a Lecturer in Geospatial Science at RMIT University's School of Science, where he teaches Remote Sensing and Photogrammetry. His research focuses on computer vision, machine learning, and 3D building modeling, with applications in indoor localization, augmented reality, and LiDAR technologies. He holds a PhD from the University of Melbourne (Australia), where his thesis addressed visual sensing for infrastructure-free indoor positioning using 3D models. Prior to his current role, he worked as a CSIRO Postdoctoral Fellow in the Machine Learning & AI Future Science Platform and as a postdoctoral researcher at RMIT, focusing on fisheries anomaly detection and food automation via deep learning. Key projects include developing the ISPRS benchmark for indoor modeling, 3D reconstruction of the Royal Exhibition Building using LiDAR, and pedestrian tracking frameworks for the Queen Victoria Market. His work emphasizes open-source solutions for spatial digital twins and geospatial data integration in data-scarce regions. Debaditya is actively involved in supervising research students at the Masters and PhD levels, particularly in smart city frameworks leveraging digital twins, IoT, and augmented reality applications.

• Digital Inclusion
• Automation and AI
• Media Policy
• +۳ مورد دیگر

Julian Thomas is a Distinguished Professor and Director of the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S) at RMIT University's School of Media and Communication. He also leads the Australian Internet Observatory. His academic focus spans digital inclusion, automation's societal impacts, and histories of communication technologies. Key projects include the Australian Digital Inclusion Index (ADII) and the Mapping the Digital Gap initiative in remote Indigenous communities. Research interests include automation's ethical implications, media policy, and the intersection of technology with cultural and social equity. He was elected to the Australian Academy of the Humanities in 2017 for his contributions to humanities research. Recent work emphasizes AI governance, automated decision-making systems in industries like retail logistics, and digital divides in rural/remote areas. His projects often combine quantitative metrics with qualitative community engagement to address systemic inequities. Current roles: Director ADM+S, Distinguished Professor, Australian Internet Observatory Lead Key achievements: ADII policy tool, multiple ARC grants, Academy of Humanities membership Research partnerships: Government agencies, tech firms, and Indigenous community organizations Teaching and supervision focus on digital policy, media regulation, and critical technology studies. Advises students on projects addressing automated systems' societal impacts and digital equity challenges.

Danula Hettiachchiمشاهده پروفایل

مدرس

• Crowdsourcing
• Social Computing
• Responsible AI
• +۳ مورد دیگر

Dr. Danula Hettiachchi is a Lecturer at RMIT University's School of Computing Technologies and an Associate Investigator at the ARC Centre of Excellence for Automated Decision-Making & Society (ADM+S). He holds a PhD from the University of Melbourne’s School of Computing and Information Systems, focusing on data quality in crowdsourcing. His research spans crowdsourcing, social computing, responsible AI, and human-computer interaction, with a focus on biases in automated systems and user interactions. Dr. Hettiachchi has authored over 30 publications in top venues like CHI, CSCW, and HCOMP, and secured grants including the Google Research Scholar Award and DAAD AInet Fellowship. Professional roles include Associate Chair at CHI 2022–2026, Program Committee member for The Web Conference, WSDM, and SIGIR, and Reviewer for PACMHCI, IMWUT, and others. Industry experience includes roles as a Full-Stack Engineer at Sysco Labs and Applied Scientist Intern at Amazon AWS. Teaching includes Usability Engineering and Programming Studio. He supervises PhD/Masters students in areas like fairness in recommendation systems and explainable AI. Collaborations span academia and industry, addressing ethical AI, micro-mobility systems (e-scooters), and bias mitigation in automated decision-making. Awards: Google Research Scholar Award, DAAD AInet Fellowship, ACCAN Grants Grants: Early Career Research Grant (ADM+S) Industry Projects: Collaboration with ACCAN on accessible tech, e-scooter mobility analysis Labs/Teams: Part of RMIT’s ADM+S Centre and previously led the User Experience Lab at the University of Melbourne.

Tom Horrocksمشاهده پروفایل

عضو هیئت علمی

• Machine Learning
• Geostatistics
• Geoscientific Data Mining
• +۳ مورد دیگر

Tom Horrocks is a Senior Research Fellow at the School of Earth and Oceans, University of Western Australia (UWA). He holds a dual degree in Engineering (Software) and Science (Physics/Applied Mathematics) from UWA, complemented by a research-focused doctoral program supported by the Robert and Maude Gledden Scholarship. His work bridges machine learning with geoscience challenges, focusing on predictive modeling, data mining, and software engineering solutions for resource exploration. Key research areas include machine learning applications in geophysics (e.g., neural networks for potential field modeling), hyperspectral imaging for mineral identification, and automated geological logging using FTIR spectra. His interdisciplinary approach often results in deployable software tools addressing real-world problems, such as the Rio Tinto Data Fusion project. Education : Bachelor of Engineering (Hons) in Software, UWA Bachelor of Science in Physics & Applied Mathematics, UWA Awards : Nick Rock Memorial Prize (2018) ASEG WA Branch Student Award (2015) UWA Vice Chancellor’s Impact & Innovation Award (2015) Current projects include the ChatGEO initiative for semantic document retrieval and collaboration with the Geodata Algorithms Team on predictive logging techniques. His research outputs span geostatistics, mineral exploration, and AI-driven geoscience solutions. Tom has contributed to major grants totaling over 5 years, including partnerships with industry leaders like Fortescue Metals Group and the Geological Survey of Western Australia. His work is disseminated through high-impact journals like Scientific Reports and Ore Geology Reviews , reflecting a strong focus on both theoretical innovation and practical application.

Eun-Jung Holdenمشاهده پروفایل

استاد

• Data Science Applied to Geoscience
• Machine Learning
• Image Analysis
• +۴ مورد دیگر

Professor Eun-Jung Holden is a leading academic in data science applied to geoscience, holding dual roles as Professor at the UWA Data Institute and Adjunct Senior Research Fellow in the School of Earth and Oceans at The University of Western Australia (UWA). She transitioned from computer science to geoscience in 2006, establishing the Centre for Data-driven Geoscience (CDG) to bridge academia and industry through advanced machine learning and visualization tools. Her education includes a computer science background from UWA, with postgraduate and postdoctoral research in computer vision and visualization. Her research focuses on automating geoscientific data analysis, including drill hole data integration, spectral imagery, and geomechanical modeling. She has commercialized three geodata analytics algorithms and led major industry projects with Rio Tinto Iron Ore, resulting in patent applications. Professor Holden’s work emphasizes cross-disciplinary collaboration, fostering innovation in mineral exploration, geophysical surveys, and virtual reality geologic mapping. She has been recognized with awards such as the 2022 Women in AI Award and the UWA Vice Chancellor’s Impact & Innovation Award. Her grants include leadership in the ARC Training Centre for Critical Resources and the ChatGEO project on semantic document retrieval. She has supervised 8 research projects and actively promotes industry-academia partnerships through initiatives like the UWA Data Institute. Labs/Teams: Leads the Centre for Data-driven Geoscience (CDG), specializing in machine learning and geoscientific data integration.

Lingbo Chengمشاهده پروفایل

مدرس

• Control Engineering
• Medical Robotics
• Teleoperation Control
• +۵ مورد دیگر

Dr. Lingbo Cheng is a Lecturer at the School of Engineering, University of Newcastle, Australia, specializing in Control and Automation for Medical Robotics. Her research focuses on haptics, teleoperation control, non-linear systems, medical imaging, and multi-robot systems. Previously, she held positions as Assistant Professor at Zhejiang University and Postdoctoral Fellow at the University of Alberta. She received her PhD in Control Systems from the University of Alberta in 2019, with qualifications spanning machine learning, signal processing, and medical robotics. Her professional experience includes developing telerobotic systems for beating-heart surgery and haptics-enabled surgical training platforms. Dr. Cheng's research bridges control engineering and medical devices, emphasizing applications in surgical robotics, autonomous navigation, and human-machine interfaces. Her publications demonstrate consistent focus on reinforcement learning for autonomous systems, medical robotics control architectures, and computational methods for real-time applications. Analyzing her recent articles reveals strong trends in reinforcement learning applications for autonomous vehicles/vessels (5 papers), medical robotics innovation (4 papers), and control system optimization (4 papers), with emerging work in maritime navigation and air traffic management. Currently leading projects on teleoperation systems and multi-robot surgical training, Dr. Cheng collaborates internationally on magnetically actuated surgical tools and autonomous navigation systems. Her lab focuses on human-robot interaction for medical and transportation applications.

• Data-intensive astrophysics
• Astronomical sciences
• Space sciences
• +۷ مورد دیگر

Sarah Hegarty is a Data Scientist affiliated with the School of Business, Law and Entrepreneurship at Swinburne University of Technology , where she contributes to data analysis, software development, and research projects. Since 2017, she has been part of the Economics of Innovation research group , specializing in data-intensive astrophysics , economic databases , and data-driven agricultural economics .