جست‌وجوی استاد و پژوهشگر

Ashantha Goonetillekeمشاهده پروفایل

استاد

• Water Quality
• Climate Change Adaptation
• Stormwater Management
• +۳ مورد دیگر

Professor Ashantha Goonetilleke is a leading academic in Water/Environmental Engineering at the Queensland University of Technology (QUT) , School of Civil & Environmental Engineering. With over 300 publications and $14M+ in research funding, his work focuses on climate change adaptation, integrated water resources management (IWRM), and sustainable urban water systems. Key roles: Technical Advisor to Brisbane Airport Corporation (10 years), Professorial Chair in Airport Innovation (5 years), Director for Infrastructure Research (QUT, 2005–2010), Discipline Leader for Civil Engineering (2017–2019) Research pillars: Water Quality Protection: Microplastics, PFAS, and urban pollutant dynamics Risk-Based Water Recycling: Decentralized systems and life-cycle analysis Infrastructure Resilience: Climate change impacts on water supply systems WASH Innovations: Decentralized sanitation and SDG6 implementation His 15 most recent articles (2023–2025) highlight expertise in nanotechnology for water purification, flood resilience strategies, and microplastics-heavy metal interactions. Awards include QUT's Vice-Chancellor's recognition for research-industry partnerships (2007, 2009). Supervised over 40 PhD students, with notable works on stormwater pollutant modeling and climate adaptation frameworks.

Nic Badcockمشاهده پروفایل

دانشیار

• Developmental Cognitive Neuroscience
• Reading and Reading Disabilities
• Dyslexia
• +۵ مورد دیگر

Nic Badcock is an Associate Professor in the School of Psychological Science at The University of Western Australia. His research focuses on developmental cognitive neuroscience, investigating how perceptual and attentional capacities underpin complex behaviors such as reading development and cognitive control. He employs neuroimaging techniques like functional transcranial Doppler ultrasound (fTCD), EEG, and fMRI to study learning difficulties, exceptional development, and neurophysiological mechanisms. Education: PhD (Applied Developmental Psychology) from The University of Western Australia (2008), BSc (Honours First Class) in Psychology (2003). Previous roles include Senior Researcher at Macquarie University (2018–2019), and postdoctoral positions at the ARC Centre of Excellence in Cognition and its Disorders (2011–2017) and the University of Oxford (2008–2011). Research Interests: Reading disabilities (dyslexia), cerebral lateralization, attention mechanisms, neuroimaging methodologies, and translational research for educational interventions. His work contributes to UN Sustainable Development Goals related to quality education and improved mental health. Recent research highlights include studies on cerebral lateralization during language tasks, neurotechnology applications (e.g., consumer EEG devices), and cultural responsiveness in university curricula. He has secured grants such as the ARC-funded 'Listen & Learn' project (2017–2021), exploring audio-based learning in education. Labs/Teams: Collaborates with multidisciplinary teams in cognitive neuroscience, including the ARC Centre of Excellence and international networks. Active in developing novel methods for assessing neurovascular coupling and lateralization in children and clinical populations.

Chow Ming Faiمشاهده پروفایل

دانشیار

• Sustainable Stormwater Management
• Hydrological Modeling
• Flood Forecasting
• +۳ مورد دیگر

Dr. Chow Ming Fai is an Associate Professor in Civil Engineering at Monash University Malaysia's School of Engineering. He holds a PhD in Civil Engineering from Universiti Teknologi Malaysia (2012) and has previously worked at Academia Sinica Taiwan and Universiti Tenaga Nasional. His research focuses on sustainable stormwater management, hydrological and water quality modeling, flood forecasting, and hydropower systems. Dr. Chow has received multiple awards including the Green Talent Award from the German Federal Ministry of Education and Research (2015), Outstanding Young Academician Award (2016), Excellent Teaching Award (2019), and most recently the Certificate of Merit for MWA Malaysia Water Award for Research (2024). He is recognized as a Professional Engineer (Ir.), Chartered Engineer (CEng.), Professional Technologist (Ts), and Professional Geospatialist. His research addresses urban water challenges through innovative modeling approaches and nature-based solutions. His recent publications demonstrate increasing focus on climate change adaptation, sustainable mining practices, and circular economy applications in water resources management.

• Structural Health Monitoring
• Machine Learning
• Data Science
• +۷ مورد دیگر

Dr. Ali Anaissi is a Lecturer in Data Science at the School of Computer Science, University of Sydney. His research focuses on structural health monitoring (SHM) using machine learning and sensor networks to detect damage in infrastructure such as bridges and roads. He has applied these techniques to the Sydney Harbour Bridge and developed a vehicle-mounted sensor system for road condition assessment. His work emphasizes condition-based maintenance over traditional time-based approaches. He teaches courses including Principles of Data Science (COMP5310), Machine Learning and Data Mining (COMP5318), and Software Development in Java (COMP9103). His research spans structural damage detection, federated learning, tensor decomposition, and IoT applications in smart homes and healthcare. Key projects include developing a smart pothole detection system and exploring adversarial attacks in UAV services. He has authored numerous publications in journals like IEEE Transactions on Cybernetics and conferences such as IJCNN and ICDMW. His work integrates machine learning with domain knowledge to improve infrastructure safety and efficiency. Dr. Anaissi's contributions include pioneering the use of adaptive one-class SVMs in SHM and developing frameworks for privacy-preserving fitness systems. His team's sensor-driven approaches aim to transform infrastructure maintenance through real-time health scoring and automated anomaly detection.

• Sociology of Quantification
• Public Statistics
• Evidence & Public Policy
• +۳ مورد دیگر

Samantha Vilkins is a PhD candidate in science communication at the Australian National Centre for the Public Awareness of Science (CPAS) at the Australian National University (ANU). She holds a BSc in Computational Science and Mathematics from Queensland and an MSciComm from ANU. As a Sessional Academic, she has tutored the 'Science Communication and the Web' course since 2017. Her research focuses on quantified evidence's role in politics, the societal implications of statistical metrics, and new media's impact on public discourse. Education: BSc (Computational Science and Mathematics), Queensland MSciComm, Australian National University Research interests include the sociology of quantification, rhetoric of public statistics, and civic epistemologies. Her work explores how metrics shape policy decisions and what societal insights are marginalized by numerical frameworks. She also investigates digital media dynamics, including polarization in online spaces and the evolving role of influencers in local politics. Her visual design work has been exhibited at the National Museum of Australia, National Library of Australia, and Science Gallery Melbourne's 2018 PERFECTION exhibit. Publications span peer-reviewed journals (e.g., Scientometrics , Foodborne Pathogens and Disease ) and popular platforms like The Conversation and Lateral Magazine . Key themes in her recent articles include analyzing political polarization in digital contexts, trust in public data post-pandemic, and the interplay between technology hype and societal adoption (e.g., quantum computing). Awards: None explicitly listed. Teaching: Extensive tutoring experience in science communication courses. Visual practice: Integrates design into research communication through exhibitions and digital media projects.

• Data Privacy
• Evolutionary Computing
• Recommendation Systems
• +۵ مورد دیگر

Dr. Jinli Cao is a full-time Associate Professor in the Department of Computer Science and Information Technology at La Trobe University. She holds a BSc from Hebei University, China, and a PhD from the University of Southern Queensland, Australia (1997). Her research focuses on evolutionary computing, data privacy, deep learning for vulnerability assessment, and decision support systems. She has published over 150 papers in top venues such as VLDB and IEEE Transactions series. Dr. Cao leads an ARC-funded project on software vulnerability risk discovery and has secured three ARC grants. She has supervised 11 PhD, 2 Master’s, and 57 Honours students, many of whom work in academia and industries like Oracle and Commonwealth Bank. Teaching contributions include developing courses in databases, data warehouses, and artificial intelligence. Research Interests: Privacy-preserving data publishing and optimization Evolutionary algorithms for dynamic data partitioning Deep learning applications in cybersecurity and healthcare Graph-based machine learning for access control and anomaly detection Decision support systems and top-k query processing Her recent articles explore cutting-edge topics like privacy-preserving spatial crowdsourcing tasks, graph neural networks for traffic prediction, and cybersecurity frameworks for vulnerability prioritization. Awards include competitive ARC grants totaling $450,000 (2023-2025). She actively serves as an Associate Editor for Health Information Science and Systems and has examined over 100 PhD theses across Australian universities. Teaching highlights: Developed 20+ courses including Database Management Systems, Data Warehousing, and Artificial Intelligence. Coordinates units like Decision Support Systems and Intermediate Programming in Java.

• Spatial Data Science
• Database Management
• Big Data
• +۳ مورد دیگر

Dr. Kiki Adhinugraha is a Lecturer in the Department of Computer Science and Information Technology at La Trobe University, Melbourne, Australia. He holds a PhD in Information Technology from Monash University and is certified as an Oracle 11g OCA DBA. His research focuses on Spatial Data Science, Database Management, and Big Data applications, particularly in GIS, spatial query processing, and spatial crowdsourcing. He teaches courses such as Programming Environment, Cloud-based Web Applications, and Database Fundamentals. His academic contributions span geospatial accessibility analysis, machine learning applications in public health (e.g., tracking pandemic impacts), and optimizing video compression and network scheduling. He has published widely on spatial data structures, including Voronoi diagrams for IoT networks and trajectory analysis. Notable works include studies on education accessibility in Melbourne and AI-driven approaches for analyzing ALS comorbidity trajectories. Teaching responsibilities include programming, web development, and database management courses. His research often bridges theoretical computing with practical applications in urban planning, transportation systems, and healthcare analytics. He collaborates on interdisciplinary projects combining GIS, machine learning, and data-driven methodologies.

• Computer Science
• Information Security
• Wireless Sensor Networks
• +۵ مورد دیگر

Dr. Jarrod Trevathan is a researcher at James Cook University, with a career spanning computer science, environmental monitoring, and information security. His work focuses on wireless sensor networks, virtual research environments, and online auction systems. He has collaborated extensively with colleagues like Trina Myers and Wayne Read. Research Highlights: Developed auction-based protocols for sensor network resource allocation Created middleware platforms for heterogeneous sensor integration Built Web2.0 disaster response systems (Riskr) Contributed to semantic enablement of virtual research environments Explored behavioral aspects of online auction fraud Teaching Innovations: Applied process-oriented guided inquiry learning to large IT courses Integrated active learning techniques for online ICT education

Senuri Wijenayakeمشاهده پروفایل

مدرس

• Human-Computer Interaction
• Social Computing
• Online User Behaviors
• +۵ مورد دیگر

Senuri Wijenayake is a Lecturer and Researcher in Human-Computer Interaction (HCI) and Social Computing at RMIT University's School of Computing Technologies, Australia. She holds a PhD from the University of Melbourne and a BSc (Hons) from the University of Moratuwa, Sri Lanka. Her research focuses on online social conformity, user behaviors in social platforms, and designing interfaces for ethical interactions. She has supervised PhD and postgraduate students, taught courses like Design Programming and Interaction Design, and led projects on autonomous vehicle-pedestrian interaction and online safety mechanisms. Awards include the Best Paper Award at INTERACT'21 and the 2021 Graduate Research Student of the Year. Education: PhD in Human-Computer Interaction, University of Melbourne (2018–2021) BSc (Hons) in Information Technology, University of Moratuwa (2013–2017) Secondary Education: GCE Advanced/Ordinary Levels, Sri Lanka Research Interests: Social Computing, Online Conformity, HCI, Autonomous Systems, Crowdsourcing, and Ethical AI. Current projects explore technology-facilitated abuse prevention and mitigating cyberbullying on social media platforms. Grants & Awards: Australian Communications Consumer Action Network Grant (AUD 78,045) for online safety strategies Instagram Research Awards Grant (AUD 75,000) for cyberbullying studies Recipient of multiple best paper awards and academic scholarships Teaching & Mentoring: Unit coordinator for over 450 students in Design Programming and Interaction Design, academic mentor for PhD/Masters researchers, and motivational speaker in Sri Lanka. Certifications include Melbourne Teaching Certificate and Modular Professional Learning Framework. Professional Activities: Organizing committee member for ACM UbiComp 2024, conference reviewer for CHI, CSCW, and WWW, and volunteer with Sri Lankan graduate societies.

• Artificial Intelligence
• Medical Imaging
• Structural Engineering
• +۵ مورد دیگر

Dr. Azadeh Alavi is a Lecturer at RMIT University's School of Computing Technologies in Melbourne, Australia. Her research focuses on interdisciplinary applications of artificial intelligence, particularly in medical imaging, structural engineering, quantum computing, and sustainability. She supervises PhD and master's projects in areas such as AI-driven medical image analysis, digital twin technology for infrastructure monitoring, and psychedelics-inspired therapeutics design. Her work spans diverse domains including healthcare analytics (e.g., diabetic foot ulcer classification, dementia prediction), civil infrastructure monitoring (e.g., bridge integrity assessment, real-time structural health systems), and theoretical AI (e.g., analyzing AI systems against consciousness definitions). Key contributions include developing PRIMITI for miRNA-mRNA interaction prediction and SellaMorph-Net for sella turcica segmentation in cephalometric imaging. Dr. Alavi’s recent publications highlight advancements in multimodal fusion learning for medical imaging, quantum-classical hybrid models for structural monitoring, and AI applications in fashion sustainability. She is an active collaborator in international research networks and maintains an ORCID profile (0000-0002-9565-217X). Her supervision portfolio includes projects on AI ethics, digital twin implementations, and health data mining. She teaches advanced computing modules and advises students on cutting-edge AI methodologies for real-world challenges across engineering and healthcare sectors.

Geoff Hinchcliffeمشاهده پروفایل

دانشیار

• Data Visualization
• Digital Cultural Collections
• Interactive Design
• +۵ مورد دیگر

Geoff Hinchcliffe is an Associate Professor and Associate Dean (Education) in the School of Art & Design at the Australian National University (ANU). He holds a Doctor of Philosophy in Communications and a Bachelor of Visual Arts from ANU. His research focuses on data visualization, computational design, and interaction design with an emphasis on cultural collections and climate science communication. He collaborates with institutions like the State Library of NSW, National Gallery of Australia, and Make Designed Objects to develop innovative interfaces for digital collections and public engagement. Key projects include "ANU Climate Coaster" – a physical-digital installation translating climate data "The Corley Explorer" – an interactive platform for Queensland's cultural heritage "My Climate 2050" – a web-based climate scenario visualization tool His work bridges theory and practice, exploring speculative design methodologies and the poetics of data representation. As an educator, he champions interdisciplinary approaches in design education and has contributed to curriculum development including the Bachelor of Design program at ANU. Recent research interests include dynamic design processes for computational contexts, materiality of digital data, and the role of playfulness in interactive systems. He has secured multiple research grants totaling over $100,000 for projects like "Compelling Collections" and "Tangible Data Representation".

• Data Science
• Artificial Intelligence
• Healthcare Analytics
• +۳ مورد دیگر

Dr. Andrew Peng is a Lecturer (Research) at the Australian Artificial Intelligence Institute (AAII) within the Faculty of Engineering and Information Technology at University of Technology Sydney (UTS), Australia. With dual PhDs from UTS (2015) and Beijing Institute of Technology (2013), he has published 45 peer-reviewed papers across top venues like IEEE ICDM, COLING, and Frontiers in Molecular Biosciences. Education: Dual PhD (2013-2015) from Beijing Institute of Technology and University of Technology Sydney His research focuses on Data Science , Artificial Intelligence , and Healthcare Analytics , addressing challenges in medical data analysis, unstructured clinical text processing, and federated learning frameworks. Recent publications explore: Deep graph clustering for community detection Privacy-preserving medicine shortage detection via social media Time-aware medication recommendation using dynamic treatment regimes Knowledge tracing enhancements for online education Contrastive learning approaches for ICD coding Hypergraph-based sequential diagnosis prediction Dr. Peng has secured over AUD $1M in external research grants and serves as Subject Coordinator for undergraduate/postgraduate courses. He contributes to professional leadership through roles as Web Chair at AJCAI 2021 and ADMA 2021, PC member for major conferences, and reviewer for journals like NeurIPS and AAAI. His work spans collaborations with universities, industry, and government agencies.

• Smart Technologies
• Computer Science
• Information Technology
• +۱۳ مورد دیگر

Professor May El Barachi is the Head of School of Computer Science at University of Wollongong in Dubai. An Egyptian Canadian Computer Scientist and Smart Technology Expert, she holds degrees in Telecom Engineering, Computer Engineering, and Computer Science. Professor El Barachi has established herself as a leader in smart technologies research with international standing. Her academic journey includes a B.Sc. in Electronics and Communication Engineering from the Arab Academy for Science and Technology, followed by an M.A.Sc. in Computer Engineering and a Ph.D. in Computer Science from Concordia University, Canada. As Head of School, she has spearheaded the design of an innovative master's program in digital transformation and revamped computer science majors to enhance student learning experiences. Professor El Barachi's research spans multiple domains including Smart Transportation, Smart Cities, BioTech, and Inclusion & Innovation. Her work focuses on developing practical solutions to real-world problems through the integration of legacy and emerging technologies. She has established collaborations with international universities in Canada, the UK, and Lebanon, as well as industry partners including Rogers Canada, Du, Cleveland Clinic Abu Dhabi, UAE Ministry of Health, and Talk5. She has raised more than 4 Million Dirhams in research funding over the past five years and has received the exemplary faculty award twice (2013 and 2015) for excellence in teaching, research, and service. Professor El Barachi is also a certified trainer in emerging technologies including Blockchain, Big Data, Data Science, Internet of Things, and Artificial Intelligence, holding numerous industry certifications from IBM, EC Council, and CISCO. Exemplary faculty award (2013, 2015) EC Council Certified Ethical Hacker CISCO CCNA Certified Instructor Multiple IBM certifications across Big Data, Blockchain, AI, and Cloud Computing As an educator, Professor El Barachi employs a student-centric, pragmatic teaching approach that emphasizes real-world relevance through examples, systems, and case studies. She has developed and taught courses in Distributed Systems, Information Security, Networking, Mobile Computing, and Emerging Technologies, fostering an interactive and engaging learning environment for her students.

Marian-Andrei Rizoiuمشاهده پروفایل

دانشیار

• Behavioral Data Science
• Misinformation and Disinformation Analysis
• Information Operations
• +۱۲ مورد دیگر

Marian-Andrei Rizoiu is an Associate Professor leading the Behavioral Data Science lab at the University of Technology Sydney's Data Science Institute, Faculty of Engineering and Information Technology. He holds concurrent appointments as an Honorary Lecturer at Australian National University and Honorary Research Scientist at Data61. Previously, he has held visiting professor positions at Imperial College London, Jean Monnet University, and Max Planck Institute for Software Systems. Associate Professor in Behavioral Data Science, UTS Data Science Institute (Jan 2024 - present) Senior Lecturer in Behavioral Data Science, UTS Data Science Institute (Jul 2021 - Jan 2024) Lecturer in Computer Science, UTS Faculty of Engineering and Information Technology (Feb 2019 - Jul 2021) Dr. Rizoiu's research focuses on interdisciplinary work crossing computer and social sciences, blending psycholinguistics, digital communication, and stochastic modeling to understand human attention dynamics online, the emergence of influence, and opinion polarization. His key contributions include developing theoretical models for online information diffusion that can account for complex social phenomena, and building skill-based real-time occupation transition recommender systems that link social media-predicted personality profiles with occupation skill requirements. His research outputs reveal strong trends in misinformation detection, social influence measurement, and online radicalization pathways. Recent publications demonstrate sophisticated modeling approaches including state space models for early misinformation prediction, multivariate Hawkes processes for analyzing partially interval-censored data, and ideology detection pipelines. His work spans computational social science, machine learning, and practical applications for countering harmful online content. Excellence Award and Academic of the Year at the 2023 Australian Defence Industry Awards ADMA'22 Best Application Paper Dr. Rizoiu has successfully secured over $2.9 million in research funding from selective funders including Meta Research, Defence Science and Technology Group, Department of Home Affairs, and Defence Innovation Network. He has supervised 3 PhD students to completion and more than 10 Honours students, most achieving High Distinction. His research has been applied in real-world contexts including serving as an expert for NSW government's Defamation Law Reform and providing evidence for Australian Federal Senate inquiry into media diversity. He leads the Behavioral Data Science lab which focuses on modeling human behavior in online environments, with particular emphasis on mis- and disinformation detection and labor market analysis. The lab has developed tools like TRACK, UTS OPEN's software for recommending personalized learning pathways, used by over 750 students and professionals.