جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Image Analysis
• Computer Vision
• +۷ مورد دیگر

Dr. Wenjing Jia is an Associate Professor at the University of Technology Sydney (UTS), affiliated with the School of Electrical and Data Engineering within the Faculty of Engineering and IT. She holds a PhD in Computing Sciences (UTS, 2007), Master's in Communications and Information Systems (Fuzhou University, 2002), and a Bachelor's in Communications Engineering (Jilin University, 1999). Her research focuses on image analysis, computer vision, and AI applications in healthcare, transport, and defense. Key areas include text detection in challenging environments, medical image super-resolution, and crowd surveillance systems. She leads projects with industry partnerships, securing over $900K in funding. Dr. Jia is also a recognized educator with 12+ years of teaching experience, specializing in internetworking subjects. She organizes international conferences (e.g., ICDAR2019, TrustCom-2017) and serves as a Cisco Certified Instructor Trainer. Awards include the Science and Technology Award and a finalist spot in the Cisco Women in IT Academia Award. Education: PhD in Computing Sciences, UTS (2007) MSc in Communications and Information Systems, Fuzhou University (2002) BEng in Communications Engineering, Jilin University (1999) Research Highlights: Developed algorithms for low-light text detection and medical image enhancement Advanced crowd counting and violence detection in surveillance systems Contributions to OCT image super-resolution and LiDAR point cloud analysis Teaching & Leadership: Lead CI of Teaching & Learning grants Legal Main Contact for UTS Cisco Networking Academy Deputy Head - Teaching and Learning (secondee) Awards: Excellent Thesis Award, Science and Technology Award (2019), and recognition in Women in IT Academia. Her work bridges academia and industry, with over 130 publications and active roles in conference organization and technology transfer.

• Precision Agriculture
• Remote Sensing
• Soil Science
• +۳ مورد دیگر

Dr. Patrick Filippi is a Lecturer in Precision Crop Management at the School of Life and Environmental Sciences, University of Sydney. He is affiliated with the Precision Agriculture Laboratory and the Sydney Institute of Agriculture. His work focuses on integrating remote sensing, machine learning, and geostatistics to address challenges in precision agriculture, particularly in crop yield modeling, soil mapping, and environmental monitoring. Research interests include precision agriculture technologies, soil science applications, data-driven crop management, and the use of satellite and proximal sensing for agricultural decision-making. He has contributed to projects funded by the Grains Research and Development Corporation (GRDC) and the University of Sydney, focusing on spatial variability in crop production, soil constraints, and machine learning interpretability. Key achievements include developing the LimeSoDa dataset for soil mapping and winning the 2016 CSIRO AgData Challenge Hackathon. His grants span topics like nitrogen fixation mapping in legumes and frost/heat management analytics. Filippi collaborates closely with industry to translate research into practical tools for farmers. Awards: 2nd Place CSIRO AgData Challenge Hackathon (2016) Labs: Precision Agriculture Laboratory (https://precision-agriculture.sydney.edu.au/) Grants: Includes Strategic Partnership Seeding Grants (2024), GRDC-funded projects (2022–2024), and Start-Up Research Funding (2024).

Chuan Khooمشاهده پروفایل

مدرس

• Interaction Design
• Physical Computing
• Tangible Embodied Interaction
• +۳ مورد دیگر

Dr. Chuan Khoo is a Lecturer in the Department of Design at Monash University, specializing in interaction design, digital media, and physical computing. He holds a PhD from RMIT University and an MFA from the Rhode Island School of Design. His work explores the dual edges of technology through projects like Touchstone (interactive public art) and Lumogram , which interrogate the relationship between humans and digital systems. Khoo’s research focuses on 'slow data'—design perspectives that critically engage with digital augmentation. He has exhibited internationally and developed tools like the mote mini , an IoT microcontroller for design students. His academic roles include teaching at RMIT and heading the Interaction Design program at Nanyang Polytechnic, Singapore. Key projects include When Echoes Find Light (2019), an interactive public bench installation, and Slow Data in the Age of Digital Things , his PhD work critiquing tech velocity. He co-designed the Alfred Health Universal Design Principles project (2024) and received a 2024 DIA Award shortlist for Lumogram . Khoo maintains Technologies for Interactivity , an open-source resource for physical computing, and collaborates globally on projects blending art, tech, and critical design.

Feng Chenمشاهده پروفایل

دانشیار

• Nonparametric and semiparametric statistics
• Point processes and self-exciting processes
• Statistical computing
• +۳ مورد دیگر

Associate Professor Feng Chen is a faculty member at the School of Mathematics & Statistics, University of New South Wales, specializing in statistical methodology development and applications. His research bridges theoretical statistics and practical implementations across financial modeling, spatiotemporal processes, and public health analysis. PhD in Statistics from University of Hong Kong (2008) MSc in Applied Probability & Statistics from Lanzhou University (2004) BSc in Mathematics from Lanzhou University (2001) Research focuses include: Nonparametric and semiparametric statistical methods Point process modeling with emphasis on Hawkes processes Statistical computing and algorithm development Applications to financial data, earthquake analysis, and public health Recent publications demonstrate methodological advances in: Hawkes process estimation with complex data structures Renewal process applications in seismology GARCH modeling with missing data Spatiotemporal clustering analysis Scientific recognition includes: UNSW Science Staff Impact Award (2023) Professional roles: Director of Research Postgraduate Studies (2023--) Associate Editor for multiple journals Statistics Honours Coordinator (2013-2018) Active participant in statistical societies

• Construction Automation
• Workforce Management
• Digital Technologies in Construction
• +۳ مورد دیگر

Dr. Alireza Ahmadian Fard Fini is an Associate Professor at the University of Technology Sydney within the Faculty of Design and Society. With over 23 years of experience in the construction industry, his work bridges professional practice, teaching, and research, focusing on construction automation and workforce management . His research aims to enhance construction productivity through digital technologies and personalized workforce solutions. Education: PhD, University of New South Wales, Australia MEng, University of Calgary, Canada MSc, Iran University of Science and Technology, Iran BSc, Shiraz University, Iran Dr. Fini’s research spans construction automation (off-site processes, digital integration) and workforce management (skill development, safety). His recent publications highlight deep learning applications for progress monitoring, drone technology in material handling, and sustainable practices in timber construction. Collaborative projects with industry partners emphasize data analytics and cloud-based deployment for practical outcomes. Scientific grants include the CRC-P Industrialization of Nail-Laminated Timber , Beverly Homes’ Industrialization of Dowel Laminated Timber , and Edwards Scholarship for prefabricated timber systems . His teaching portfolio includes Design Team Management , Site Establishment , and Time Management at UTS. Future work will focus on standardizing timber panel stability , expanding UAV applications , and aligning mental health research with policy frameworks.

Sahani Pathirajaمشاهده پروفایل

مدرس

• Data Science
• Bayesian Inference
• Stochastic Analysis
• +۷ مورد دیگر

Dr. Sahani Pathiraja is a Lecturer (tenure track assistant professor) at UNSW Sydney , specializing in Data Science . Her research bridges mathematical and statistical foundations with practical applications in environmental and biomedical sciences. Research Focus : Sequential Bayesian inference, Monte Carlo methods, stochastic analysis of non-linear filtering, uncertainty quantification, and real-time parameter estimation. Current Projects : Co-investigator in the ARC Industrial Transformation Training Centre: Data Analytics for Resources and Environment (DARE) and the Next Generation Graduate Program (NGGP) in Sports Data Science and AI . Research Supervision : Dr. Pathiraja supervises PhD students in areas including: Bayesian inference Stochastic differential equations Data assimilation Non-linear filtering Scientific Collaborations : Her work intersects with environmental science, biomedical applications, and machine learning. Projects include stochastic hydrology, SDEs, and operator learning for environmental systems. Contact Information : Email: s.pathiraja@unsw.edu.au Phone: +61 2 8065 0836 Office: Room 2070, Level 2, The Red Centre, UNSW Sydney

• Surveying
• Spatial Science
• Built Environment
• +۷ مورد دیگر

Dr. Armin Agha Karimi is a Lecturer in the School of Surveying and Built Environment at the University of Southern Queensland. He holds a BSc in Civil Engineering from Tabriz University, an MSc from Middle East Technical University (METU), and a PhD from the University of Newcastle. His research focuses on spatial data integration, cadastral systems modernization, environmental monitoring using remote sensing, and sea level variability analysis. Key research interests include 3D cadastral boundaries in BIM environments, digital twin applications in built environments, and the impact of hydrological loading on land motion. He has contributed to studies on erosion hotspot mapping in Queensland and the implications of coal seam gas activities on land subsidence. His work on Baltic Sea sea level dynamics and Australian coastal projections has advanced understanding of climate-driven environmental changes. Dr. Karimi is affiliated with the Centre for Sustainable Agricultural Systems and actively publishes on geomatics, climate science, and legal aspects of digital surveying. His recent articles highlight innovations in VR-ready survey data transformation and the legal challenges of electronic cadastral plans.

• STEM Education
• Mathematics Education
• Interdisciplinary Learning
• +۴ مورد دیگر

Professor Lyn English is a leading academic in STEM and mathematics education at Queensland University of Technology's College of Education, Department of Curriculum. Her research focuses on interdisciplinary approaches, particularly integrating engineering and data science into early years education. She has authored or co-edited numerous books and journal articles, emphasizing the role of design-based problem solving and mathematical modeling in fostering critical thinking. English has contributed extensively to curriculum frameworks, including the 'Pattern and Structure Mathematics Awareness Program' (PASMAP), and has explored gender dynamics in mathematics achievement. She collaborates with institutions globally, such as Routledge, Springer, and the Australian Council for Educational Research, to advance educational methodologies. Her work highlights the importance of bridging theory and practice in STEM education. English’s research spans cognitive development in statistical and probabilistic reasoning, foundational mathematical concepts in primary education, and teacher professional development. She advocates for accelerating students' learning through innovative curricula like the RAMR framework and has conducted studies on pedagogical practices in diverse educational settings. Her edited volumes, including Handbook of International Research in Mathematics Education and Ways of Thinking in STEM-based Problem Solving , consolidate cutting-edge perspectives in the field. English’s contributions to conferences and symposia underscore her commitment to advancing STEM integration and addressing challenges in mathematics education research.

• Large-scale nonparametric and kernel methods
• Robust and trustworthy machine learning
• Multiresolution data and data fusion
• +۳ مورد دیگر

Professor Dino Sejdinovic is a faculty member in the School of Computer and Mathematical Sciences at the University of Adelaide, part of the Faculty of Sciences, Engineering and Technology. Previously, he held positions as Lecturer and Associate Professor at the University of Oxford's Department of Statistics (2014–2022). His academic qualifications include a PhD in Electrical and Electronic Engineering from the University of Bristol (2009) and a Diplom in Mathematics and Theoretical Computer Science from the University of Sarajevo (2006). His research focuses on the intersection of statistical methodology and machine learning, encompassing large-scale nonparametric methods, robust machine learning, multiresolution data fusion, and measures of dependence. He has contributed to kernel methods, Bayesian inference, causal discovery, and applications in climate science, quantum computing, and social science data analysis. Education: PhD in Electrical and Electronic Engineering, University of Bristol (2009) Diplom in Mathematics and Theoretical Computer Science, University of Sarajevo (2006) Sejdinovic's work emphasizes bridging theoretical foundations with practical applications, such as cloud type classification using vision transformers and machine learning-driven quantum device optimization. His recent publications explore topics like kernel-based causal inference, Bayesian neural networks, and uncertainty quantification in statistical models. Advising and grants: Eligible to supervise Masters and PhD students in machine learning and statistics, though specific grants or student advisees are not explicitly listed in the provided texts.

Noel Cressieمشاهده پروفایل

استاد

• Spatial Statistics
• Environmental Informatics
• Bayesian Statistics
• +۳ مورد دیگر

Noel Cressie is a Distinguished Professor of Statistics at the University of Wollongong (UOW), Australia, affiliated with the School of Mathematics and Applied Statistics and the National Institute for Applied Statistics Research Australia (NIASRA). He is also the Director of the Centre for Environmental Informatics (CEI). His academic journey includes a PhD from Princeton University (1975) and a B.Sc. with First Class Honours from the University of Western Australia (1972). His research focuses on spatial and spatio-temporal statistics, Bayesian methods, environmental informatics, and applications in climate science. Notable projects include work on atmospheric CO2 flux inversion (WOMBAT framework), Antarctic environmental research (SAEF initiative), and statistical remote sensing for NASA. He has secured over $20 million in research funding and authored four influential books, including Statistics for Spatial Data . Cressie has received prestigious awards such as the COPSS R.A. Fisher Award (2009), Pitman Medal (2014), and Fellowship of the Australian Academy of Science (2018). He leads interdisciplinary teams addressing global challenges like carbon cycle dynamics and biodiversity modeling. His contributions to statistical methodology and environmental science have been recognized through international collaborations and advisory roles.

Dong Ngo Duyمشاهده پروفایل

دانشیار

• Connected and Autonomous Vehicles
• Traffic Flow Theory and Simulation
• Data Fusion
• +۷ مورد دیگر

Dong Ngo Duy is an Associate Professor in the Department of Civil & Environmental Engineering at Monash University, where he serves as the Head of the Transport Section. He holds a PhD in Traffic Flow Theory and Simulation from Delft University of Technology and has held academic positions at the University of Leeds (UK), University of Canterbury (NZ), and now Monash University (Australia). PhD, Traffic Flow Theory, Technische Universiteit Delft (2006) MSc, Traffic Engineering, Linköpings Universitet (2002) His research focuses on Connected and Autonomous Vehicles (CAVs) , Traffic Flow Theory , Data Fusion , and Urban Network Optimization . He applies AI and machine learning to model, predict, and control multi-modal traffic systems, aiming to develop smart city platforms for sustainable transport in mega-cities. The recent trend in his publications (2022–2025) reflects a strong focus on intelligent transportation, including trajectory planning, risk-aware control, car-following modeling using neural symbolic regression, and intercity mobility analysis. His work bridges theoretical modeling with practical applications in emerging connected environments. Scientific Awards: UK Research Council (EPSRC) Advanced Fellow Award (2011–2016) in Connected and Autonomous Vehicles Dong Ngo Duy actively supervises PhD students and contributes to major research initiatives in intelligent transport systems. His work aligns with UN Sustainable Development Goals, particularly in sustainable cities and transport. He previously chaired the Connected Traffic Systems Lab at the University of Canterbury and continues to lead impactful research in transport innovation.

Wendy Gunnمشاهده پروفایل

استاد مدعو

• Collaborative design in healthcare
• Sustainability in healthcare systems
• Medical device recycling/remufacturing
• +۵ مورد دیگر

Wendy Gunn is an Adjunct Professor (Research) in the Department of Design at Monash University. She holds a PhD in Social Anthropology from the University of Manchester (2003) and an MA in Social Anthropology from the same institution (1996). Her research focuses on collaborative design processes, sustainability in healthcare systems, and the integration of anthropological methods into engineering and architectural design. Gunn has extensive experience in interdisciplinary research, particularly in healthcare sustainability, medical device lifecycle management, and sustainable care pathway redesign. She has supervised numerous PhD theses across institutions including NTNU (Norway), University of Cape Town, and RMIT University. Notable collaborations include roles with the Healthcare Without Harm (HCWH) plastics working group, the UK Sustainable Healthcare Coalition (SHC), and the EU-funded GreenCare consortium. Her work contributes to UN Sustainable Development Goals related to environmental sustainability and healthcare innovation. Key research interests include design anthropology, emerging technologies, and the application of anthropological frameworks to collaborative design challenges. Recent work explores digitalization in healthcare, distributed care systems, and the environmental impact of medical packaging.

Ian Rennerمشاهده پروفایل

مدرس ارشد

• Ecological Statistics
• Species Distribution Models
• Statistical Theory
• +۳ مورد دیگر

Dr. Ian Renner is a Senior Lecturer in the School of Information and Physical Sciences at the University of Newcastle, specializing in Data Science and Statistics. He holds a PhD in Statistics from the University of New South Wales, complemented by a Master of Statistics from the University of Utah and a Bachelor of Science in Mathematics from Valparaiso University. His research focuses on species distribution models (SDMs), particularly leveraging presence-only data and point process models. He developed the PPM-LASSO approach and maintains the R package 'ppmlasso' for model implementation. Education: PhD (Statistics), University of New South Wales Master of Statistics, University of Utah Bachelor of Science (Mathematics), Valparaiso University Research Interests: Dr. Renner's work bridges statistics and ecology, emphasizing the development of robust SDMs. Key areas include: Unifying MAXENT and Poisson point process models Observer bias correction in ecological data Integration of regularization techniques (e.g., LASSO) for predictive accuracy Application of citizen science data in conservation His methodologies address challenges like taxonomy changes and sampling biases in species distribution studies. Publications: His recent work highlights advancements in SDM stability, citizen science applications, and regularization methods. Key themes include improving model reliability through penalized likelihoods and addressing ecological data complexities. Awards: JB Douglas Award (2011) Runner-up for Best Student Talk (2011) EJG Pitman Prize (2010) Grants & Supervision: He has secured $12,838 in internal grants, including a visiting fellowship at CNRS (France) and conference funding. He currently co-supervises a PhD on deep learning for speech depression recognition and has guided two other students in statistical ecology and methodology. Labs/Teams: Leads the development of the 'ppmlasso' R package, collaborating with researchers like Olivier Gimenez and Eric Beh to advance ecological statistics.

• Resilience Ecology
• Marine Ecology
• Blue Carbon Ecosystems
• +۴ مورد دیگر

Dr Alice Jones is a Senior Lecturer in Resilience Ecology at the University of Adelaide's School of Biological Sciences, within the Faculty of Sciences, Engineering and Technology. She leads the Future Coasts Lab, focusing on coastal ecosystems' role in mitigating climate change through blue carbon storage and restoration. Her research emphasizes seagrass restoration, marine aquaculture sustainability, and interdisciplinary collaboration with governments and NGOs. Education: PhD from the National Oceanography Centre (UK), MSc in Aquatic Resource Management (King's College London), BSc Zoology (Manchester University). Research interests include blue carbon ecosystems (mangroves, seagrasses, saltmarshes), climate change mitigation, and policy frameworks. Key projects include a federally-funded seagrass restoration initiative in South Australia and collaborations on climate-smart aquaculture. Notable awards: 2020 Winnovation Award, 2021 South Australian Young Tall Poppy Science Award, and 2022-2024 Superstar of STEM. She is an Associate Editor for Remote Sensing in Ecology and Conservation . Grants include a $2.1M Commonwealth grant for Gulf St Vincent seagrass restoration and a $1M project measuring blue carbon benefits. She has mentored Honours and PhD students in coastal ecology and collaborates internationally on policy and restoration. Labs/Teams: Future Coasts Lab, part of interdisciplinary networks focused on coastal resilience and climate action.

Miriam Matamalesمشاهده پروفایل

دانشیار

• Neuroscience
• Cognitive Neuroscience
• Systems Neuroscience
• +۴ مورد دیگر

Dr. Miriam Matamales is a UNSW Scientia Fellow (Level C) in the School of Psychology at the University of New South Wales. She leads the Neuromodulatory Systems and Behaviour group within the Decision Neuroscience Laboratory, focusing on understanding how neuromodulatory systems support plasticity in subcortical brain networks for generating and modifying voluntary behaviors. Education: Ph.D. Neuroscience, Pierre and Marie Curie University, Paris, France (2009) Master in Biomedical Research, Pompeu Fabra University, Barcelona, Spain (2007) Bachelor of Human Biology, Pompeu Fabra University, Barcelona, Spain (2006) Dr. Matamales' research combines innovative high-throughput fluorescence microscopy and computational image analysis to understand how the functional architecture of the striatum encodes goal-directed learning and how its dysfunction impairs normal behavior. Her work primarily focuses on neuromodulatory systems (dopamine, acetylcholine, neuropeptides) supporting plasticity in subcortical brain networks, particularly the striatum and basal ganglia pathways. She uses mice as experimental models with approaches including instrumental conditioning, AAV-based circuit- and cell-specific tracing and manipulation in behaving animals, in vivo photometry and computational analysis of behavioral and neuronal data. Analysis of Dr. Matamales' recent publications shows a strong focus on striatal function, goal-directed learning mechanisms, and age-related changes in neural circuits. Her work spans from molecular neuroscience examining DARPP-32 signaling to systems-level investigations of basal ganglia circuits and their role in behavior. Scientific Awards: UNSW Dean of Science Early Career Excellence Award (2020) UNSW's Vice-Chancellor's Childcare Support Fund for Women Researchers (2019) Paxinos-Watson Award from the Australasian Neuroscience Society (2017) Dr. Matamales has successfully secured multiple competitive grants including NHMRC Ideas Grants as both Lead CI and CIB, an ARC Discovery Project as Lead Investigator, and a Tourette Association of America Young Investigator Award as sole CI. She currently supervises PhD student Jonathon Jacobs on research related to the molecular footprint of instrumental learning in the striatum. In addition to her research, she teaches in the UNSW NEUR2201 Neuroscience Fundamentals course and serves as invited faculty at the Australasian Course in Advanced Neuroscience. Her laboratory, the Neuromodulatory Systems and Behaviour group (www.neuromodulab.org), investigates how learning is encoded in brain circuits and how new behaviors imprint in neuronal circuits during generation, maturation, and adaptation to environmental rule changes.