Danielle Butler is a Visiting Fellow at the National Centre for Epidemiology and Population Health, Australian National University, and a part-time General Practitioner/Researcher at the Institute of Urban Indigenous Health. With 20+ years clinical experience and a PhD (2018), her work focuses on healthcare access equity for underserved populations through linked data analysis, mixed-methods research, and telehealth evaluation. Current projects: Enhancing Safe Telehealth , Patient-Centered Medical Homes , Primary Care Data Linkage Key collaborations: ANU, IUIH, Australian Institute of Health and Welfare Her research combines multilevel modeling of administrative data with participatory action research to evaluate primary care innovations. Recent work examines telehealth impacts , out-of-pocket costs , and Aboriginal health service models . Publications span BMJ Open , BMC Health Services Research , and Health Policy , with emphasis on systematic reviews , linked data methodology , and health equity metrics . Research fingerprint shows dominant themes: Primary Health Care (100%), Aboriginal and Torres Strait Islander Health (66%), Health Services Research (49%), and Telehealth (100%).
Associate Professor Seojeong Lee is a faculty member at the University of New South Wales (UNSW) Business School, School of Economics, specializing in advanced econometric theory. She joined UNSW in 2012 after completing her PhD at the University of Wisconsin-Madison and has established herself as a leading researcher in robust inference methods under complex data conditions. Her educational background includes: Ph.D. in Economics, University of Wisconsin-Madison (2008-2012) M.A. in Economics, Seoul National University (2006-2008) B.A. in Economics and Political Science (dual major), Seoul National University, summa cum laude (2000-2006, with military service 2002-2004) Professor Lee's research centers on developing theoretically rigorous methods for econometric inference, with primary focus on generalized method of moments (GMM), instrumental variables (IV), and two-stage least squares (2SLS) under model misspecification. Her work addresses critical challenges including invalid/many/weak instruments, heterogeneous treatment effects, and clustered sampling, contributing foundational advances to statistical inference in economics. Analysis of her recent publications reveals a strong trajectory in refining methods for many-instrument settings and misspecified models, with increasing emphasis on computational implementations (e.g., Stata packages) and applications to causal inference. Her work bridges theoretical econometrics with practical policy-relevant analysis. Her scientific achievements include: Australian Research Council DECRA Fellowship (2017-2019) UNSW Dean's Research Fellowship (2020-2022) Zellner Thesis Award Honorable Mention from American Statistical Association (2014) Multiple competitive UNSW research awards Professor Lee actively supervises PhD candidates Wei Tian and Fangzhou Yu, and has secured over AUD 700,000 in research funding including ARC Discovery Projects. She teaches undergraduate and postgraduate econometrics courses, integrating her research into pedagogy. Her ongoing work continues to push boundaries in robust econometric methodology for modern data challenges.
Dr. Sasha Rubin is a Senior Lecturer and leader of the Computational Logic for AI (LOGIC-AI) group at the School of Computer Science, The University of Sydney. He holds a PhD in Mathematics and Computer Science from the University of Auckland and previously worked at the University of Naples Federico II. His research focuses on logic foundations of AI, including synthesis, planning, formal methods, and multi-agent systems. He teaches courses like Models of Computation and supervises students in topics like probabilistic systems and reinforcement learning. Research Interests: Mathematical Logic, Formal Verification, Temporal Logic Synthesis, Automated Reasoning, and Multi-Agent Systems. He has published extensively in top venues like IJCAI, AAAI, and ACM Transactions. His work includes verification of agent navigation, strategy logic, and planning under uncertain environments. Awards: Recognized as an Australian Research Field Leader in Theoretical Computer Science (2020). He serves on editorial boards for JAIR and conferences like KR, and organizes events such as the Australasian Association for Logic Conference (2024). Supervision and Grants: Current students include Ethan HIRSCHOWITZ and Kunal OSTWAL. Past supervision spans MPhil/PhD projects on probabilistic systems, ML classifier fairness, and symbolic automata. His grants include studies on logic and robots in anonymous graphs. Professional Activities: Member of EATCS, ACM, and mentor for the Sydney Summer Innovation Programme. He leads the LOGIC-AI lab and collaborates internationally, notably with Giuseppe De Giacomo at Sapienza University of Rome.
Prof Scott Crowe is a leading academic and clinical researcher in radiation oncology medical physics, affiliated with the Royal Brisbane and Women’s Hospital and the Hudson Institute of Medical Research (HBI) Cancer Care Services. His work bridges clinical practice and advanced research in radiotherapy technologies. Clinical Role: Clinical Lead for Cancer Care Services at HBI, overseeing radiation oncology medical physics. Education: Post-doctoral fellowship at Queensland University of Technology (QUT). Research Interests focus on: 3D Printing: Developing patient-specific phantoms and devices for radiotherapy applications (e.g., lung, vaginal, and oral molds). Dosimetry: Advancing measurement techniques (ionization chambers, Monte Carlo simulations) and addressing challenges like small field dose corrections, skin dose enhancement, and secondary cancer risk assessment. Adaptive Radiotherapy: Real-time motion adaptation systems, including Radixact Synchrony and TomoTherapy, to improve treatment accuracy. Quality Assurance: Statistical process control for beam energy variations, gamma evaluation methods, and machine performance checks. Publication Trends highlight his expertise in integrating 3D printing with dosimetry, optimizing adaptive radiotherapy workflows, and improving quality assurance protocols. His work spans Monte Carlo simulations , proton therapy , and image-guided radiotherapy . Supervision: Mentors higher degree research students in radiation oncology physics. Conferences: Regular presenter at international scientific meetings. Labs & Collaborations: Manages the radiation oncology medical physics research portfolio at Royal Brisbane and Women’s Hospital, collaborating with Hudson Institute on clinical translation projects.
Corina Pasareanu is an ACM Fellow and IEEE ASE Fellow serving as a Principal Scientist at Carnegie Mellon University's CyLab Security and Privacy Institute and Technical Professional Leader for Data Science at NASA Ames Research Center through KBR. Her work bridges formal methods, software verification, and artificial intelligence to ensure the safety and security of complex systems, particularly autonomous systems and machine learning applications. Dr. Pasareanu received her academic training at: Ph.D. in Computer Science, Kansas State University (2001) M.S. in Computer Science, University Politehcnica of Bucharest (1995) B.S. in Computer Science, University Politehcnica of Bucharest (1994) Her research focuses on developing formal verification techniques that can provide mathematical guarantees about the behavior of complex software systems. She specializes in applying model checking, symbolic execution, and compositional verification methods to challenges in autonomy, security, and AI safety. Her recent work addresses the verification of systems incorporating machine learning components, particularly neural networks used in safety-critical applications like autonomous vehicles. She investigates how to ensure these systems behave correctly even when their perception components have uncertainties or are subject to adversarial attacks. Analysis of her recent publications shows a strong trend toward verifying AI and machine learning systems, particularly focusing on neural networks in autonomous systems. Her work increasingly addresses the challenges of Large Language Models, examining both their vulnerabilities to attacks and methods to defend against them. She also continues to advance traditional software verification techniques while adapting them to modern programming languages and paradigms. Dr. Pasareanu has received numerous prestigious awards recognizing her contributions to the field: ACM Fellow IEEE ASE Fellow ETAPS Test of Time Award (2021) ASE Most Influential Paper Award (2018) ESEC/FSE Test of Time Award (2018) ISSTA Retrospective Impact Paper Award (2018) ACM Impact Paper Award (2010) ICSE 2010 Most Influential Paper Award (2010) As an advisor, Dr. Pasareanu mentors several PhD students and postdoctoral researchers, often in collaboration with other faculty members at CMU. Her students focus on cutting-edge research at the intersection of formal methods and AI safety. Her research is supported by substantial funding from diverse sources including NSF, DARPA, NASA, AWS, and industry partnerships. She leads multiple projects focused on AI security, formal verification of neural networks, and software analysis techniques. Dr. Pasareanu also plays a significant role in the broader research community, serving as Program/General Chair for major conferences including ICSE 2025, and as an associate editor for IEEE TSE and STTT. Dr. Pasareanu leads research teams working on projects like "Trinity: Neurosymbolic Learning and Reasoning" (DARPA) and "HUGS: Human-Guided Software Testing and Analysis" (NSF). Her work often involves interdisciplinary collaboration between computer scientists, formal methods experts, and domain specialists to address complex safety challenges in autonomous systems.
Professor Ron Van der Meyden is a faculty member at the School of Computer Science and Engineering at the University of New South Wales, Sydney. His work focuses on the intersection of logic, security, and distributed systems, with particular expertise in blockchain technology and smart contracts. He leads the UNSW Interest Group in Blockchain, Smart Contracts and Cryptocurrency and organizes related seminar series. Professor Van der Meyden's research spans formal methods, computer security, and distributed systems. His work on epistemic logic has been influential in understanding knowledge-based systems and security protocols. He has made significant contributions to the formal verification of blockchain protocols and smart contracts, bringing rigorous mathematical approaches to these emerging technologies. His recent work explores the application of knowledge-based reasoning to consensus protocols and intersection management in autonomous systems. ACM Distinguished Scientist, 2009 As an advisor, Professor Van der Meyden has mentored numerous PhD and Masters students who have gone on to successful careers in academia and industry. His research is supported by grants including Australia's Economic Accelerator Grant for developing a commercial version of a software model checker and an AFOSR/DST Australia grant for verification and synthesis of fault-tolerant autonomous systems. He has received multiple ARC Discovery and Linkage grants over the years. Professor Van der Meyden leads the UNSW Interest Group in Blockchain, Smart Contracts and Cryptocurrency, fostering interdisciplinary research in this area. He has played key roles in major research centers including Smart Internet CRC and National ICT Australia (NICTA), where he established and led the Formal Methods program. His work on the formal verification of the seL4 microkernel and the Goanna static analysis tool has had significant practical impact.
Professor Simon Devitt is Research Director of the Centre for Quantum Software and Information (QSI) at the University of Technology Sydney's Faculty of Engineering and Information Technology, School of Computer Science. He also holds several prestigious international appointments including InstituteQ Visiting Chair of Excellence in Quantum Technologies at Aalto University, Finland, and visiting positions at RIKEN in Japan. As a leading figure in quantum computing research, he directs the Australian Quantum Software Network and co-founded quantum education startup Eigensystems Pty Ltd. His educational background includes: PhD in Physics from University of Melbourne (2004-2007) BSc (Hons) in Physics from University of Melbourne (2000-2003) Professor Devitt's research spans quantum software, quantum architecture, and quantum error correction, with a focus on making quantum computing practical at scale. His work addresses fundamental challenges in quantum computing architecture when scaled to millions or billions of qubits. He has pioneered approaches to quantum error correction, resource estimation, and quantum network design, particularly through his leadership of the Quantum Technology at Scale (QTS) research group. His research bridges theoretical foundations with practical implementation challenges, aiming to shape the evolution of quantum technology over the coming decades. His recent publications demonstrate a strong focus on practical quantum computing challenges, with particular emphasis on error correction techniques, resource estimation, and quantum architecture. A significant portion of his work addresses the surface code and its variants, exploring ways to optimize qubit usage and error rates. He has also made important contributions to quantum networking, particularly through the concept of "quantum sneakernet," and to quantum education and standardization efforts that will be critical for the emerging quantum industry. His notable awards and recognitions include: Fellow of the Australian Institute of Physics Fellow of the Royal Society of New South Wales Warren Prize from the Royal Society of NSW InstituteQ Visiting Chair of Excellence in Quantum Technology Professor Devitt actively mentors numerous PhD students, postdocs, and researchers through his Quantum Technology at Scale group. His research is supported by significant funding from diverse sources including Google Academic Research Awards, Sydney Quantum Academy, DARPA, and the Japanese Society for the Promotion of Science. He has led projects on quantum sneakernet networks, quantum algorithm benchmarking frameworks, and quantum software tools that address critical challenges in the field. He leads the Quantum Technology at Scale (QTS) research group at UTS, which focuses on the design and architectural challenges of quantum computing and communications technology at scale. The group includes researchers working on quantum computing architectures, quantum networking (Rottnest Quantum Sneakernet project), and quantum software (Quokka project). The team collaborates extensively with international partners including Aalto University in Finland, University of New South Wales, Keio University in Japan, and industry leaders like Rigetti Computing.
Dr. Dominic Williamson is a theoretical quantum physicist and DECRA Research Fellow at the School of Physics, University of Sydney. He specializes in quantum phases of matter and their applications to quantum error correction and computing. His work bridges condensed matter theory and quantum information science, focusing on fracton topological phases and fault-tolerant quantum architectures. Education: PhD in Physics from the University of Vienna (2017); Postdoctoral research at Yale University, Stanford University, and IBM Quantum. Current roles include faculty membership at the University of Sydney’s Quantum Science Group and prior industry experience at IBM and PsiQuantum. Research interests: Topological phases of matter, quantum error correction codes (e.g., fracton codes, QLDPC systems), fault-tolerant quantum computing architectures, and non-Abelian anyon systems. Recent breakthroughs include low-overhead quantum architectures and novel approaches to parallelized logical measurements. Grants: 2022 ARC Discovery Early Career Researcher Award for topological phases in quantum computation. Collaborations include projects on gauging logical operators and quantum code surgery. Professional activities: Editor for Quantum , frequent speaker at international conferences, and mentor for students at all levels (undergraduate to postdoctoral). Active in open-source research and public engagement through platforms like arXiv and Google Scholar.
Zhe Hou is a Senior Lecturer at the School of Information and Communication Technology , Griffith University, Australia. His academic journey includes a PhD in automated reasoning for separation logic from the Australian National University (2015) and prior research roles at Nanyang Technological University, Singapore (2015-2017). He joined Griffith University in 2017 and became permanent faculty in late 2019. Research Interests : Formal methods for software verification Automated reasoning with logical frameworks Blockchain technology and security Quantum computing verification Integration of LLMs with rigorous reasoning Sports analytics via model checking Recent Publications demonstrate expertise in neural-symbolic reasoning, blockchain security, quantum SAT solvers, and runtime verification frameworks. His work combines formal logic with machine learning for applications in cybersecurity and AI trustworthiness. Scientific Awards : ACM SIGSOFT Distinguished Paper Award (2025) Supervision Roles : Principal/Associate Supervisor for 6+ doctoral projects in blockchain security, AI verification, and network security. Professional Activities : Editor for Springer-Nature and Formal Aspects of Computing special issues, conference chair for ICFEM, ICECCS, and ISACE symposia.
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.
Professor Asif Gill is Head of Discipline for Software Engineering at the School of Computer Science, University of Technology Sydney (UTS), where he was promoted to Professor of Computer Science in January 2024. He also serves as Director of the DigiSAS Research and Innovation Lab and is actively involved in the Global Big Data Technologies Centre at UTS. As a founder of both the DigiSAS Lab and the Future Generation Enterprise Architecture Community of Practice (FGEA CoP), he has established integrated teaching-research-engagement frameworks that translate academic research into practical applications while enhancing graduate employment opportunities. Professor Gill's research interests span Adaptive Enterprise Architecture , Agile Software Development , and Design Science Research & Innovation , with a particular focus on architecting large-scale data-intensive enterprise software systems. His work addresses challenges across academia, industry, government, and society, with significant contributions to AI systems architecture, digital identity management, and enterprise knowledge graphs. His applied research has resulted in numerous collaborations with organizations including the Reserve Bank of Australia, Revenue NSW, Capsifi, Data Zoo, and the NSW Department of Planning, Industry and Environment. His publication record includes 3 books and over 190 articles in major academic journals such as IEEE Transactions on Professional Communication, Information and Management, and Information Systems. His recent work demonstrates a consistent focus on cutting-edge topics in enterprise architecture, AI systems, and digital identity, with multiple publications appearing in 2024-2025. His research trajectory shows a clear evolution from foundational work in agile software development toward more sophisticated integration of AI, enterprise architecture, and data governance. Fellow of the Australian Computer Society (ACS) Fellow of DSE (ESCP Center for Design Science in Entrepreneurship) Senior Member IEEE Associate Editor, IEEE Transactions on Technology & Society Associate Editor, Springer Nature Discover Data journals Member, Data Sharing Committee, IFIP Technical Committee 8.1 Member, Standards Australia Software and Systems Engineering Committee IT-015 Professor Gill has successfully secured numerous research grants from 2019-2026, totaling significant funding for projects related to digital identity, enterprise architecture, and AI systems. His approach emphasizes industry-academia collaboration, with many projects involving direct partnerships with government agencies and industry organizations. He has supervised multiple PhD and Master's students through industry-sponsored scholarships and maintains active collaborations with researchers across multiple institutions. Leading the DigiSAS Research and Innovation Lab, Professor Gill has created an environment that bridges theoretical research with practical implementation. The lab focuses on developing frameworks and tools for adaptive enterprise architecture, with particular emphasis on AI-enabled systems, data governance, and digital identity solutions. His work on the Data Satellite Architecture represents a significant contribution to combating data pollution in federated digital ecosystems.
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.
Professor Lisa Waller serves as the Associate Dean of Communication at RMIT University's School of Media and Communication. Her expertise spans journalism, political communication, and media representation, with a focus on Indigenous media, fact-checking, and ethical reporting. Prior to RMIT, she held roles at Deakin University and worked in editorial positions at major news outlets like The Canberra Times and The Australian Financial Review. Her research explores the intersection of media and public policy, including election promise tracking and the role of journalism in democratic processes. She leads the Australian Research Council-funded project 'Democratic Promissory Representation,' examining political journalism's impact on public perceptions of governance. Her work also addresses media representation of First Nations peoples, rural communities, and issues of gender equality. Waller supervises PhD and Master’s students on topics such as fact-checking methodologies, foreign correspondence, and teenagers' engagement with news algorithms. She has authored books including Local Journalism in a Digital World and The Dynamics of News and Indigenous Policy in Australia , and her research emphasizes ethical practices in journalism, particularly regarding sensitive topics like child sexual abuse reporting and death knock procedures. Her grants and collaborations include five ARC projects, reflecting her commitment to advancing media studies and public interest journalism. She actively engages with industry through advisory roles and mentoring, bridging academic research with practical journalism challenges.
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.
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 .
