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Dr. Kirsten Winter is an Honorary Senior Fellow at the University of Queensland's School of Electrical Engineering and Computer Science. Her research focuses on formal verification, concurrent programming, and weak memory models. She has contributed significantly to areas such as model checking, railway interlocking systems, and behavior trees. Her work spans theoretical foundations (e.g., linearizability, concurrency semantics) and practical applications in security and embedded systems. Recent projects include the Program Analysis Cell and BASIL: Boogie Analysis for Secure Information-Flow Logics. Winter has collaborated extensively with researchers like Graeme Smith and Robert Colvin. Her most recent publications address speculative execution vulnerabilities and compositional reasoning in weak memory architectures.

• Formal Verification
• Concurrent Programming
• Computer Security
• +3 more

Dr. Nina Maadad is a Senior Lecturer in the School of Education at the University of Adelaide, affiliated with the Faculty of Arts, Business, Law and Economics. She holds a strong focus on global educational challenges, particularly refugee education, multiculturalism, and academic mobility. Her research spans multiple countries including Australia, Indonesia, Lebanon, Turkey, and Sweden. Key research interests include refugee integration, language acquisition in diverse contexts, and policy analysis in cross-cultural education systems. Dr. Maadad’s work often addresses the interplay between education systems and societal structures, with recent emphases on online learning dynamics post-2020 and multilevel factors affecting student outcomes in secular vs. religious schools. Her publications from 2020-2025 consistently analyze refugee education across geopolitical contexts, emphasizing systemic barriers faced by displaced populations. This includes studies on child marriage dynamics among refugee girls, comparative education policies for Arabic-speaking refugees, and the role of first language attrition in multilingual settings. No specific scientific awards or grants are explicitly mentioned in the provided materials, though her extensive publication record indicates significant academic contribution. Advising activities are not detailed here, but her research often collaborates with international teams addressing global educational inequities.

• Refugee Education
• Multiculturalism
• Academic Mobility
• +3 more

Rakotonirainy Andry is a Professor at Queensland University of Technology (QUT), affiliated with the Centre for Accident Research & Road Safety - Queensland (CARRS-Q). His research focuses on transportation safety, automated vehicles, human factors, and intelligent transportation systems (ITS). He leads interdisciplinary projects exploring driver behavior, connected vehicle technologies, and the societal impacts of automation. Key areas include accident prevention, human-vehicle interaction, and equity in transport systems. His work integrates machine learning, simulation studies, and behavioral analysis to address challenges in road safety. Notable contributions include studies on driver stress detection, automated vehicle acceptance, and the Australian Naturalistic Driving Study (ANDS). He collaborates with institutions globally, advancing innovations like connected vehicle pilots and multimodal AI for traffic safety. Research interests span automated driving systems, vulnerable road user protection, and policy implications of emerging technologies. His findings contribute to safer transportation policies and technologies, emphasizing both technical and human-centric perspectives.

• Transportation Safety
• Automated Vehicles
• Human Factors in Transportation
• +3 more

Niloufer Selvadurai is Professor and Director of Research & Innovation at Macquarie Law School, where she also co-directs the Data Horizons Research Centre and co-chairs the Australian Law Associate Deans Research Network. A technology law scholar focusing on AI regulation, she examines how laws can calibrate technological innovation benefits and risks. Her interdisciplinary research collaborates with computing, engineering, finance, and health fields. Key leadership roles and recognitions include: Co-Director, Data Horizons Research Centre Program Leader for 'AI and Law' at Centre for Applied AI 2022 Australian Legal Education Award for Excellence in Graduate Research Supervision 2023 Higher Degree Research Supervisor of the Year Her publications extensively cover AI governance, digital finance, copyright, and smart contracts law, with recent work examining AI inventorship and regulatory frameworks for central bank digital currencies.

• Artificial Intelligence Regulation
• Digital Finance Law
• Intellectual Property Law
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Natasha Fernandes is a Senior Lecturer in the School of Computing at Macquarie University. She holds a PhD in Computing from Macquarie University and École Polytechnique (France), and an undergraduate degree in Pure Mathematics and Computer Science from the University of Sydney. Her roles include involvement in the Data Horizons Research Centre and Future Communications Research Centre, alongside professional casual appointments in academic computing. Her research focuses on the mathematical foundations of data privacy, particularly differential privacy and its applications in natural language processing and machine learning. She develops privacy-preserving systems and tools using quantitative information flow techniques rooted in information theory. Key areas include privacy analyses for financial systems (e.g., Open Banking), API privacy, and optimizing utility in privacy pipelines. Fernandes has led or contributed to five research projects, including work on privacy analyses for financial transaction protocols and UAV-based machine learning systems. She received the 2021 John Makpeace Bennett Award for her doctoral research on differential privacy in metric spaces. Her academic journey combines industry experience as a backend software engineer with rigorous academic contributions, spanning over 21 peer-reviewed publications and collaborations across cybersecurity and privacy engineering domains.

• Data Privacy
• Differential Privacy
• Privacy-Preserving Machine Learning
• +3 more

Professor Moe Thandar Wynn is a Co-Director of QUT's Centre for Data Science and holds a Professorship in the School of Information Systems at Queensland University of Technology (QUT). She leads the Process Science Academic Program and serves as the Academic Lead of Research for the School of Information Systems. Her expertise spans Process Mining, Data Quality, and Robotic Process Automation (RPA). Prof Wynn has attracted over AUD 6 million in research funding and holds an h-index of 41 with 8700+ citations. She is a member of the Australian Research Council College of Experts (2023–2025) and has received prestigious awards including the QLD Women in Technology Excellence Award (2024). Her research focuses on formal foundations of process modeling, verification, and automation. She has contributed to international conferences as a co-chair and program committee member, and co-edited special issues on RPA and process dynamics. Prof Wynn collaborates with industries like healthcare, insurance, and agriculture to optimize business processes through data-driven insights. Current research includes privacy-preserving process mining and quality-driven event log enhancement. Education: PhD (QUT, 2006), M. Information Technology (Research, QUT) Key Projects: Hospital Capacity Optimization, Liquid Process Model Collections, Risk-Aware BPM Supervision: Over 10 completed PhD/MSc students in process mining and analytics Awards: Multiple QUT Excellence Awards, ARC College Membership Her lab focuses on advancing process intelligence and RPA, with ongoing efforts in data quality frameworks and process mining standards (e.g., IEEE XES). She actively participates in industry partnerships, such as the CRC Food Agility project, to bridge research and real-world applications.

• Process Mining
• Data Quality
• Business Process Management
• +3 more

Ko, Jonghyeon is a researcher affiliated with the Ulsan National Institute of Science and Technology (UNIST) , specifically the Department of Materials Science and Engineering within the College of Natural Science and Engineering. His work spans multiple disciplines including process mining, anomaly detection, blockchain technology, AI computing, and environmental engineering. His research interests include: Anomaly detection in business process event logs Blockchain-based systems for nuclear/radioactive waste management AI computing using neuromorphic devices Statistical leverage and information-theoretic approaches to process mining Optimization of autonomous vehicle safety systems Recent publications demonstrate expertise in developing formal languages for data quality simulation, probabilistic trace alignment methods, and practical tools for anomaly detection like AIR-BAGEL. While no explicit scientific awards are mentioned in the text, his work has been published in venues such as Information Systems , npj Unconventional Computing , and Expert Systems with Applications .

• Process Mining
• Anomaly Detection
• Blockchain
• +3 more

Dr. Jonathan Kummerfeld is a Senior Lecturer at the University of Sydney's School of Computer Science, specializing in Natural Language Processing (NLP) and AI collaboration. He holds a PhD from UC Berkeley and a B.Sc. from the University of Sydney, with postdoctoral research at the University of Michigan. His work focuses on enabling computers to collaborate effectively with humans through NLP, including interactive systems, dialogue, and crowdsourcing. Education: PhD in Computer Science, UC Berkeley (advised by Dan Klein), 2016 B.Sc. in Computer Science, University of Sydney (advised by James Curran), 2010 Postdoctoral Researcher at University of Michigan (2016–2021) Research Interests: Interactive Executable Semantic Parsing NLP Data Science for Messy Real-World Data AI Collaboration in Games and Dialogue His recent work explores empathetic AI systems, alignment algorithms, and AI-resilient interfaces. Over 50 publications span venues like ACL, NAACL, and ICML. Grants & Advising: CHIRON (DARPA): AI for recognizing opponent narratives Google/Amazon grants for annotation tools and dialogue systems Advising PhD student Kent O'Sullivan His lab develops tools like SLATE and contributes to dialogue corpora. Labs/Teams: Leads the Sydney NLP Lab, focusing on human-AI collaboration and scalable NLP systems.

• Natural Language Processing
• Artificial Intelligence
• Human-Computer Interaction
• +4 more

Professor Mikhail Prokopenko is a leading academic in complex systems research at the University of Sydney's School of Computer Science. He holds a PhD in Computer Science (Macquarie University, 2002), MA in Economics (USA), and MSc in Applied Mathematics (USSR). As Director of the Centre for Complex Systems and Theme Co-Leader for Pathogen Emergence and Spread at the Institute for Infectious Diseases, his work focuses on modeling self-organizing systems, computational epidemiology, and AI applications in pandemic control. Roles: Director of Centre for Complex Systems, Theme Co-Leader (Pathogen Emergence), Theme Leader (Complex Systems) Education: PhD Computer Science (2002), MA Economics (USA), MSc Applied Mathematics (USSR) Affiliations: Fellow of Royal Society of NSW, Specialty Editor for Frontiers in Robotics and AI His research addresses challenges in complex systems like power grids, communication networks, and epidemiological models. Notable contributions include: RoboCup World Champion teams (2016, 2019) in Simulation League COVID-19 modeling featured in Nature's Top 50 SARS-CoV-2 articles (2020) Development of AMTraC-19 agent-based pandemic model Key research areas include: Guided self-organization principles Information dynamics in collective systems Thermodynamic efficiency of complex processes He has supervised over 200 publications and patents, with recent focus on pandemic response optimization and urban system resilience.

• Complex Systems
• Computational Epidemiology
• Artificial Intelligence
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Dr. Paulo Santos is a Senior Lecturer at Flinders University's College of Science and Engineering, specializing in Artificial Intelligence with a focus on explainable AI systems. He holds a PhD from Imperial College London (2003) and has over 20 years of research experience in spatial reasoning, machine learning, and robotics. His work bridges knowledge representation with deep learning to enhance transparency in AI decision-making. Dr. Santos has led research groups in Brazil, collaborated internationally, and secured funding from organizations like the British Council and EU. His expertise spans robotics, computer vision, and cognitive science. Notable achievements include the British Computer Science Machine Intelligence Prize (2004) and the Santander Prize for Science and Innovation (2006). Research interests include reinforcement learning for autonomous underwater vehicles (AUVs), scene graph generation in computer vision, and spatial reasoning for multi-robot systems. Recent work emphasizes sim-to-real transfer learning and fault recovery in underwater robotics.

• Artificial Intelligence
• Machine Learning
• Spatial Reasoning
• +3 more

Lim Jit Yan is a Lecturer at the School of Information Technology, Monash University Malaysia. He holds a PhD in Information Technology (2023) from Multimedia University, specializing in self-supervised metric-based meta-learning for few-shot image classification, and a B.IT (Hons) in Artificial Intelligence (2019) from the same institution. His research focuses on few-shot learning, computer vision, and deep learning, with contributions to medical image analysis (e.g., Covid-19 detection), transfer learning applications, and generative models. He has published extensively since 2021, with notable work on self-supervised feature fusion and prototypical networks for few-shot learning. Research interests include few-shot learning techniques, neural architecture design for image classification, and real-world applications like healthcare diagnostics and autonomous systems. Recent work emphasizes self-supervised learning and transformer-based models to address data scarcity challenges in AI. No formal scientific awards are listed. Advising details are not provided in the text, though his publications suggest collaborative research with colleagues like Lim K.M. and Lee C.P. His research spans theoretical advancements and applied projects, including work on pill image recognition, traffic sign detection, and brain tumor classification.

• Few-Shot Learning
• Computer Vision
• Deep Learning
• +3 more

Phil Edwards is a Lecturer in the School of Art at RMIT University, specializing in interdisciplinary art practices that explore hybridity, cultural critique, and contemporary artistic expression. His research spans children’s art, outsider art, and the intersection of fine art with everyday aesthetics. He holds a Master’s degree examining innate aesthetic tendencies in everyday object assemblages and a PhD analyzing the role of audio CDs in fine art culture. Research Interests: Edwards focuses on six core themes: children’s art/outsider art’s relationship to formal painting, fake poetry integration in visual art, alchemy as metaphor, music brut, temporality in hybrid art forms, and abstract landscape painting. His creative works often blend digital media (e.g., Instagram-based projects) with traditional techniques. Teaching & Supervision: Edwards supervises Masters and PhD students in research topics like border identity visualizations (Maria Penne’s DFA project). He actively mentors projects such as An Exploration of Zen-inspired Poetic Nature Painting and Museum of Emotion . Exhibitions & Projects: His works include installations like Museum of Platitudes AND Aphorisms and digital projects such as Continual Instagram Painting . He frequently exhibits in venues like the c3 Art Gallery and George Paton Gallery, emphasizing public engagement and conceptual depth.

• Children’s Art
• Outsider Art
• Fake Poetry and Fine Art
• +5 more

Professor Sebastian Sardina is a Professor in Artificial Intelligence at RMIT University's School of Computing Technologies. He holds a Bachelor's from South National University (Argentina) and a PhD from the University of Toronto (Canada). His research focuses on AI for dynamic systems, including automated planning, knowledge representation, and agent-oriented programming. He has contributed to enhancing agent programming languages with learning capabilities and advanced AI planning techniques. His work frequently appears in top AI venues like IJCAI and AAAI, with notable best paper nominations. Teaching interests include foundational CS courses such as Theory of Computation and Intro to AI. He actively promotes computational thinking through workshops for youth and educators, including roles in Victorian curriculum development (VCE Algorithmics). Supervision projects span hand gesture recognition, autonomous vehicle safety, and goal recognition in path-planning. His research has been presented globally and applied across domains like aviation safety, manufacturing systems, and healthcare. Recent trends in his publications emphasize goal recognition techniques (e.g., process mining applications), agent behavior modeling, and interdisciplinary AI applications in healthcare and automotive engineering. He has collaborated with industry and academic partners internationally, contributing to both theoretical advancements and practical AI solutions. Scientific Recognition: Multiple best paper nominations in AI conferences. Community Engagement: MAV conference presenter, VCAA Algorithmics curriculum panel member (2023). Supervision: Active mentor for 4+ research projects in AI planning and recognition.

• Artificial Intelligence
• Automated Planning
• Knowledge Representation
• +4 more

Owen Bullock is a Senior Lecturer in Creative Writing and Literary Studies at the University of Canberra's Arts & Communication school. He holds a PhD in Semiotics and Poetic Practice from the University of Canberra (2017), focusing on New Zealand poets. His research explores creative arts and wellbeing, haikai literature, poetry processes, and collaboration. Bullock has published extensively, including poetry collections like Pancakes for Neptune , haiku works, and a novella. He has received awards such as the 2015 Canberra Critics’ Circle Poetry Award and the 2018 Donald Horne Creative Fellowship. Currently, he leads the Creative Writing discipline and advises PhD students in creative writing, poetry, and New Zealand literature. Education: PhD: Semiotics and Poetic Practice in Three New Zealand Poets (University of Canberra, 2017) Research Interests: Semiotics in poetry Haiku and brevity aesthetics Poetry's role in wellbeing Contemporary Australian and New Zealand literature Collaborative creative processes Projects & Engagement: Co-Investigator on Defence ARRTS projects (2021–2028), focusing on creative writing for resilience and teamwork Edited journals including Poetry New Zealand and Kokako Organized the 2023 Australasian Association of Writing Programs Conference Awards & Recognition: 2020 UC Teaching Excellence Award 2018 Donald Horne Creative Fellowship 2015 Canberra Critics’ Circle Poetry Award His work bridges academic research and creative practice, emphasizing poetry’s role in personal and collective healing through innovative forms and interdisciplinary approaches.

• Creative Writing
• Poetry
• Haikai Literature
• +5 more

Tim French is an Associate Professor in the Department of Computer Science and Software Engineering at the University of Western Australia's School of Physics, Maths and Computing. He is affiliated with the UWA Oceans Institute and serves as Regional Contest Director for the South Pacific Programming Contest and Programme Chair for the Australasian Conference on Artificial Intelligence 2022. His research focuses on logic, artificial intelligence, knowledge representation, and reasoning about uncertainty in multi-agent systems, probabilistic reasoning in games, and industrial applications like automated planning and machine learning for complex processes. French holds a PhD in Computer Science (2007) and BSc in Computer and Mathematical Sciences (1999), both from UWA. His expertise spans algorithms, automated reasoning, formal methods in software, and temporal logic verification systems. He has led or contributed to 6 major research projects including the ARC Research Hub for Transforming Energy Infrastructure and the ARC Training Centre for Transforming Maintenance through Data Science. His research outputs include 118 publications covering topics like aleatoric logic for probabilistic reasoning, semantic knowledge extraction from industrial maintenance systems, and deep learning applications in wastewater treatment. He has developed novel methods for knowledge graph construction, state estimation in complex systems, and user interface design informed by work characteristics models. Key grants: 6 active/finished projects totaling $M+ funding Leadership roles: Programming contest director, conference chair Interdisciplinary focus: Combines formal logic with industrial automation challenges French's work contributes to UN Sustainable Development Goals through education and innovation in sustainable industrial processes and environmental systems modeling. His team has developed practical solutions for maintenance procedure digitization, wastewater plant optimization, and robust agent-based systems for uncertain environments.

• Logic
• Artificial Intelligence
• Knowledge Representation and Reasoning
• +5 more