Dr. Liyi Zhou is a Lecturer in the School of Computer Science at the University of Sydney, specializing in systems security, blockchain, and AI. His research focuses on developing automated and adaptive security tools using machine learning and reinforcement learning. He co-founded D23E.ch, a platform addressing blockchain security and privacy challenges. Research interests include AI-driven vulnerability detection, large security models, real-time intrusion prevention, advanced program analysis (fuzzing/symbolic execution), and privacy-preserving systems. He actively recruits PhD students for projects advancing AI in cybersecurity. Notable achievements include pioneering 'sandwich attacks' discovery in DeFi protocols, contributing to Ethereum Foundation grants, and receiving bug bounties from Flashbots and Ethereum Foundation for vulnerability disclosures. His work has been published in venues like IEEE S&P, USENIX Security, and SIGMETRICS. Teaching includes the course INFO2222. He seeks collaborations and funding to bridge academic research with real-world industry problems, emphasizing practical impact.
Christopher Ferrie is an Associate Professor at the University of Technology Sydney (UTS), where he is affiliated with the Faculty of Engineering and Information Technology and the Centre for Quantum Software and Information (QSI). His academic career spans quantum information science, machine learning, and scientific education, with a strong emphasis on both theoretical research and public engagement through science communication. Full-time faculty member at UTS Active researcher in quantum information science Director of the Centre for Quantum Software and Information Author of numerous scientific publications and popular science books Dr. Ferrie earned his PhD in Applied Mathematics from the Institute for Quantum Computing and University of Waterloo in Canada in 2012. His doctoral work focused on quantum information and laid the foundation for his subsequent research career in quantum computing and related fields. Dr. Ferrie's research interests span several interconnected domains within quantum information science. His primary focus is on quantum estimation and control, with particular emphasis on applying machine learning techniques to solve statistical problems in quantum information science. He investigates how quantum systems can be characterized, controlled, and optimized for practical applications. His work bridges theoretical quantum physics with practical implementations, exploring how quantum phenomena can be harnessed for computational advantage. Recent research directions include quantum machine learning, quantum neural networks, and quantum optimization algorithms, with applications ranging from quantum state tomography to solving combinatorial optimization problems. Analysis of Dr. Ferrie's recent publications reveals a strong focus on practical quantum computing challenges. His work consistently addresses the intersection of quantum information theory and machine learning, with particular emphasis on making quantum algorithms more efficient, interpretable, and robust against noise. A significant portion of his recent research explores variational quantum algorithms and their optimization, reflecting the current priorities in near-term quantum computing. His publications also demonstrate growing interest in quantum machine learning applications and the development of techniques for quantum error mitigation and characterization. Dr. Ferrie has secured multiple research grants supporting his work in quantum computing and related fields. His funded projects span quantum control, quantum probability, quantum machine learning, and statistical decision theory, reflecting the breadth of his research program. While specific major awards aren't detailed in the available information, his sustained funding and publication record indicate significant recognition within the quantum information science community. Dr. Ferrie is actively involved in research supervision and teaching, with current funding supporting multiple PhD students and postdoctoral researchers. His teaching responsibilities include courses on quantum computing, where he introduces students to the fundamentals of quantum information processing. His research group at the Centre for Quantum Software and Information focuses on developing novel quantum algorithms and exploring the practical implementation challenges of quantum computing. The Centre for Quantum Software and Information at UTS serves as the primary research environment for Dr. Ferrie's work. This center brings together researchers working on various aspects of quantum computing, from hardware development to algorithm design and applications. Dr. Ferrie's team within the center focuses specifically on quantum software development, quantum algorithm design, and the application of machine learning techniques to quantum information problems. The collaborative environment enables interdisciplinary research that bridges theoretical quantum physics with practical computing applications.
Dr. Alan Huang is a Senior Lecturer at the School of Mathematics and Physics, University of Queensland. He holds a PhD in Statistics from the University of Chicago (McCormick Fellowship) and an Honours degree in Science (Advanced Mathematics) from the University of Sydney. His academic career includes lecturing roles at the University of Wisconsin-Madison and the University of Technology Sydney before joining UQ. Research Focus: Biostatistics, nonparametric methods, and statistical modeling for dispersed counts. Key Projects: Bayesian methods for agricultural data, trend analysis of pesticide concentrations in the Great Barrier Reef, spectral water quality analysis. Article Trends: His work spans generalized linear models, count data analysis, and environmental statistics, with recent emphasis on Conway-Maxwell-Poisson regression and time-series modeling. Collaborations include environmental science applications. Awards: McCormick Fellowship (University of Chicago). Supervision: Currently advising PhD research on count data methods. Past supervision includes topics in geotechnical uncertainty and rock mechanics. Collaborates with Queensland Department of Environment and Science on water quality projects.
Andy McLennan is a Professor in the School of Economics at the University of Queensland since 2007, following roles at the University of Minnesota (1987–2005) and the University of Sydney. His research focuses on mathematical economics and game theory, with contributions to computational game theory, fixed point theory, and algebraic geometry. Notable collaborations include work with Richard McKelvey on the Gambit software package for game analysis. Education: B.A. in Mathematics from the University of Chicago (undergraduate), PhD in Economics from Princeton University (1982). Prior faculty positions included the University of Toronto and Cornell University. Research Interests: Explores intersections between pure mathematics and economics, including applications of topology (Vietoris-Begle theorem), differential geometry (Morse-Sard theorem), and computational complexity in markets. Recent work includes the 'Index +1 Principle' for equilibrium stability and fixed point index theory. Software & Tools: Co-developed Gambit , a widely used open-source toolkit for analyzing finite games. Authored technical software for solving systems of equations and 3D visualization tools for academic use. Books: Authored Advanced Fixed Point Theory for Economics (Springer, 2018), The Algebra of Coherent Algebraic Sheaves , and The Nature and Origins of Modern Mathematics . Personal: Lives in Brisbane with his partner Shino Takayama (also an economist) and their son Sean. Enjoys Japanese language, classical music, and strategic games like Go and chess.
Associate Professor Tongliang Liu is affiliated with the School of Computer Science at the University of Sydney, serving as Director of the Sydney Artificial Intelligence Centre and Trustworthy Machine Learning Lab. He holds a BEng and PhD, and is an ARC Future Fellow. His research focuses on trustworthy machine learning, including adversarial defense, causal representation learning, and robust AI systems. He has authored over 200 papers in top venues like NeurIPS and ICML, and serves as co-Editor-in-Chief of Neural Networks. Research Interests: Developing reliable algorithms for machine learning, emphasizing generalizability and safety. Specific areas include learning with noisy labels, causal inference, and foundational model ethics. He aims to bridge theoretical guarantees and practical applications in computer vision and data mining. Awards: 2024 CORE Award, 2023 IEEE AI's 10 to Watch, 2022 ARC Future Fellowship. Notable recognitions include Eureka Prize shortlist and DECRA. Advising & Grants: Supervises 12 PhD/Master’s students on topics like trustworthy AI, causal discovery, and quantum machine learning. Leads grants on robust learning and AI safety. Labs: Sydney AI Centre and Trustworthy Machine Learning Lab.
Associate Professor Judy Hart is a materials scientist at the School of Materials Science & Engineering, UNSW Sydney , specializing in the development of semiconducting materials for renewable energy applications. Her work integrates computational (DFT) and experimental approaches to understand composition-property relationships in systems like solid solutions , heterostructures , and doped materials for photocatalysis and solar cells . She leads projects funded by ARC Discovery and Linkage grants , including work on photo-electro-catalysis systems and stabilizing ceramic materials . Education: PhD in Materials Engineering (Monash University, 2007), BEng (Materials) (Monash, 2002) Professional Experience: Senior Lecturer (UNSW, 2017–), Lecturer (UNSW, 2013–2017), University of Bristol (2007–2012) Research Interests Her research focuses on designing materials for renewable energy , particularly photoelectrochemical water splitting and organic oxidation reactions . Key areas include Density Functional Theory (DFT) , defect engineering , band gap tuning , and nanostructured materials . She investigates ferroelectric polarization effects , metal oxide heterostructures , and stability of battery components , with applications in hydrogen production , CO2 conversion , and advanced battery materials . Scientific Awards Ramsay Memorial Fellowship (University of Bristol, 2007–2009) Teaching Contributions She is co-author of the 1st Australian & New Zealand edition of "Materials Science and Engineering: An Introduction" , and teaches courses on computational materials science , corrosion-resistant surfaces , mechanical behavior of metals , and materials design .
Professor John Piggott AO FASSA is Scientia Professor of Economics at the University of New South Wales, where he serves as Director of the Australian Research Council Centre of Excellence in Population Ageing Research (CEPAR). He has held significant leadership roles at UNSW including three terms as Head of School of Economics, Associate Dean Research for the Business Faculty for 7 years, and Interim Dean of the Faculty. His expertise spans retirement economics, pension systems, and population ageing issues, with particular focus on Asia-Pacific region. His educational background includes: BA from University of Sydney MSc from London School of Economics PhD from University of London Professor Piggott's research focuses on retirement and pension economics, population ageing, and public finance. His work examines pension system designs across different countries, with particular emphasis on emerging Asian economies. He has conducted extensive research on retirement income systems, long-term care financing, and the economic implications of demographic change. His research has significant policy relevance, having informed government reviews and international organizations' work on ageing populations. He has published widely in leading international economics and actuarial academic journals, with recent work analyzing pension reforms in Indonesia, Thailand, and China. His recent publications demonstrate a strong focus on population ageing in the Asia-Pacific region, particularly examining pension systems and long-term care in emerging economies. His work bridges economics, public policy, and health services research, with increasing attention to the interconnections between demographic change, economic development, and social policy in aging societies. His research has directly influenced policy discussions through participation in the Henry Tax Review and Australian Ministerial Superannuation Advisory Committee. Professor Piggott has received numerous prestigious awards and honors: Fellow of the Academy of the Social Sciences in Australia (1992) Scientia Professor at UNSW (2011-present) ARC Australian Professorial Fellow (2011-2015) UNSW Business School's Staff Excellence Global Impact Award (2020) Officer of the Order of Australia (AO) (2020) Professor Piggott has supervised numerous PhD students including Rafal Chomik, Hoang Hoyen, and T Le Trang. He has secured substantial research funding including multiple ARC grants totaling over $27 million for the CEPAR Centre, Japan Economic and Social Research Institute projects, and Rockefeller Foundation support. His research has directly informed policy discussions through participation in the Henry Tax Review and Australian Ministerial Superannuation Advisory Committee, and he was appointed co-chair of the Think20 Task Force on Aging Population during Japan's G20 Presidency. As Director of CEPAR, Professor Piggott leads a major research center focused on population ageing research, bringing together interdisciplinary expertise to address the challenges of aging societies. The center collaborates with international partners including the US National Academy of Medicine and OECD, and has played a key role in establishing the International Pension Research Association. His work has significant real-world impact, with his research on JobKeeper transition proposals during the COVID-19 pandemic receiving widespread media attention.
SangHyung Ahn is a Lecturer at the School of Civil Engineering , University of Queensland (UQ), since 2017. He joined UQ as a postdoctoral research fellow in 2015 after earning his PhD in Civil Engineering (Construction Engineering and Management) from Purdue University, USA. Prior to his academic career, he worked as an assistant manager at Hyundai Engineering and Construction Co., Ltd. (2003-2007) and holds an MBA in international business from Hanyang University and a B.Sc in Civil Engineering from Korea University. Research Focus: Construction process modelling with virtual reality, decision support systems for construction, automation of data-driven simulation modelling, sensor-based operations analysis, and integration of Building Information Modelling (BIM). Teaching: Coordinates undergraduate courses Introduction to Project Management (CIVL3510) and Construction Engineering Management (CIVL4522) . Research Trends: His recent publications highlight interdisciplinary work in transportation engineering, structural design, and AI-driven simulation tools. Key themes include application of machine learning to car-following models, drone-based vehicle identification, and optimization of public transport systems using agent-based simulations. Supervision: Available for supervision, with completed supervision of PhD and Master’s theses on topics such as BIM-LCA integration, pedestrian trajectory analysis, and AI-driven driving behavior models.
Sri AravindaKrishnan Thyagarajan is a Lecturer at The University of Sydney's School of Computer Science, specializing in cryptography. He focuses on enhancing security and fairness in distributed systems, blockchains, and multi-party computations with applications in post-quantum cryptography. His work spans top-tier conferences like ACM CCS and IEEE SP. Education: B.Tech, Computer Science & Engineering, National Institute of Technology Trichy, India (2011–2015) M.Sc., Computer Science, Saarland University, Germany (2015–2016) Ph.D., Applied Cryptography, Friedrich Alexander Universität Erlangen-Nürnberg, Germany (2016–2021) Research Interests: Cryptography (classical and post-quantum), blockchain security, cryptocurrencies, fairness in multi-party computations, privacy-preserving protocols, and decentralized systems. Recent Articles: Focus on cryptographic protocols for blockchains, threshold cryptography, verifiable randomness, and secure atomic swaps. Recent work includes advancements in post-quantum signatures, distributed randomness generation, and privacy-preserving payment systems. Awards: Nominated for GI Dissertationspreis 2021 Advising & Grants: Advising Ankit Kapoor. Active in program committees for CCS, IEEE SP, and FC. Currently Program Chair for Crypto Valley Conference 2025. Labs/Teams: Part of the Sydney Blockchain Centre and cybersecurity cluster at the University of Sydney. Collaborates globally with institutions like NTT Research, Carnegie Mellon University, and Bocconi University.
Associate Professor Myra Hamilton is a Principal Research Fellow at the University of Sydney Business School, specializing in gender, ageing, and care. She holds a BA (Hons 1) and PhD from the University of Sydney. Her research focuses on work/care reconciliation, policy needs of carers, and retirement income inequalities. She is a member of the Sydney Centre for Healthy Societies and Sydney Policy Lab, and serves on the Board of COTANSW. Education: BA (Hons 1), University of Sydney PhD, University of Sydney Research Interests: Myra’s work examines how policies and services can improve wellbeing in work and care across lifecourses. Key areas include unpaid care responsibilities, retirement income disparities, and intergenerational relationships. She combines academic research with applied policy projects for governments and NGOs. Articles Trends: Recent publications emphasize multigenerational workforce policies, grandparent childcare dynamics, and barriers to formal aged care access. Her 2024 book The Multigenerational Workforce explores age and gender in workplaces. Grants & Advising: Current grants include 'New models of replacement care for working carers' (ARC) and 'Women in Construction Industry Innovation Program'. She has supervised students on topics like aged care services and mature-age labor markets. Labs/Teams: Active in the ARC Centre of Excellence in Population Ageing Research and collaborates with organizations like the Social Policy Research Centre (UNSW).
Dr. Sam Ferguson is a Senior Lecturer at the School of Computer Science, University of Technology Sydney (UTS), with a multidisciplinary background in music performance, cognitive science, and psycho-acoustics. His research explores the intersection of sound, music, and human experience through creative coding, machine learning, and interactive systems. Key Research Areas: Sound and Music Computing, Human-Computer Interaction, Creative Coding, Cognitive Science, Installation Art, and Acoustics. Current Projects: ARC Linkage project on creative coding and multiplicitous media; industry collaborations on IoT-based audiovisual systems. Recent Publications: Focus on spatial audio complexity, gestural interaction with networked sound, music emotion recognition frameworks, and robotic performance through genre-based cultural platforms. Leadership Roles: Director of Teaching & Learning Engagement; former Deputy Head of School (Teaching and Learning); active in ACM Creativity and Cognition Steering Committee. Teaching: Courses like Digital Media Studio , Prototyping Physical Interaction , and Data Processing using R within UTS's interdisciplinary Software Development Studio.
Kwan-Wu Chin is a Professor in the School of Electrical, Computer and Telecommunications Engineering at the University of Wollongong, where he also serves as Head of Postgraduate Studies (HPS) and co-directs the Wireless Technologies Lab (WTL). His research focuses on resource allocation problems in Internet of Things (IoT) systems, maritime networks, edge computing platforms, and integrated sensing-communication systems. Chin leads an active research group currently supervising five PhD students working on UAV networks, edge computing, maritime systems, and metaverse resource allocation. He has graduated over 20 PhD students who now hold positions in academia and industry. Chin serves as editor for Elsevier Computer Communications and IEEE Internet of Things Journal. His work develops optimization techniques using graph theory, stochastic processes, and machine learning for next-generation wireless systems.
Dr. Nour Moustafa is an Associate Professor and ARC DECRA Fellow at the School of Systems & Computing (SysCom) , University of New South Wales (UNSW) Canberra , Australia. He leads the Intelligent Security Group and focuses on developing AI/ML-driven cybersecurity frameworks for smart systems. Educated at Helwan University (BSc/MSc in Information Systems) and UNSW (PhD in Cybersecurity). Research Interests include intrusion detection, threat intelligence, privacy preservation, digital forensics, and cyber resilience, with methodologies spanning statistical analysis , machine learning , and deep learning applied to IoT , Edge/Cloud , and Industrial IoT environments. His work emphasizes federated learning for privacy preservation, blockchain for secure AI, and digital twins for network self-healing. Notable contributions include the TON-IoT , Bot-IoT , and UNSW-NB15 datasets for cybersecurity evaluation. Scientific Awards : 2020 Spitfire Memorial Defence Fellowship ACM Distinguished Speaker IEEE Senior Member He has served as guest associate editor for IEEE Transactions journals and held leadership roles in conferences like IEEE TrustCom . His research bridges academia and industry, with over 75 publications in top-tier venues.
Adjunct Professor Evgeny Osipov is affiliated with La Trobe University's Business Analytics department. His research spans artificial intelligence, hyperdimensional computing, and neural network architectures. Academic Rank: Adjunct Professor Department: Business Analytics Email: E.Osipov@latrobe.edu.au Research interests include: Hyperdimensional computing and vector symbolic architectures Spiking neural networks and reservoir computing Hardware-efficient AI implementations Causal reasoning in large language models Self-organizing maps and spatiotemporal sequence learning Applications in smart cities and robotic navigation Recent research outputs demonstrate expertise in: Developing unsupervised learning frameworks using hypervectors Optimizing reservoir computing with cellular automata Creating memory-efficient neural network models Advancing hyperdimensional classification techniques Exploring causal graph integration in language models
Harald Van Heerde is a Research Professor of Marketing at the University of New South Wales, Sydney, within the UNSW Business School's Department of Marketing. He holds roles as Editor of the Journal of Marketing and Executive Vice-Chairman/Program Director of the Marketing Science Hub at AiMark. His academic career includes positions at Maastricht University, the University of Waikato, Tilburg University, and Massey University. Education: Ph.D. in Economics (Cum Laude), University of Groningen, the Netherlands (1999) M.Sc. in Econometrics (Cum Laude), University of Groningen, the Netherlands (1995) Research Interests: Harald focuses on applying econometric models and large datasets to address critical marketing challenges. His work explores marketing mix effectiveness , brand equity , digital marketing strategies , consumer behavior in crises , and cross-industry applications such as retailing, healthcare, and entertainment. Methodologically, he emphasizes dynamic models, endogeneity correction, optimization techniques, and text mining. Articles Trends: Recent publications highlight analysis of inflation's impact on consumer spending , mobile app engagement , brand recovery post-crisis , and econometric frameworks in marketing decision-making. His work bridges theoretical advancements with practical business implications, particularly in stochastic cost industries and global market dynamics. Awards & Fellowships: 2024: AMA Fellow & Shelby/Hunt Best Paper Award 2021: Churchill Award (Lifetime Contributions) 2004–2023: 10+ paper awards including MSI/Root, Paul Green, and multiple long-term impact recognitions Advising & Grants: Currently supervising doctoral candidates Ayesha Hossain (Human Branding) and Ada Choi (consumer financial decision-making). Supervised 12 completed theses across branding, retailing, and digital marketing. Secured over AU$2 million in grants including ARC Discovery, MSI, and the Marsden Fund. His grants examine topics like brand crisis management, price war dynamics, and mobile marketing ROI. Labs & Teams: Leads the Marketing Science Hub at AiMark, a nonprofit connecting academics with household panel data. Consults for global firms including Unilever, Edeka, and AZTEC. His work emphasizes collaborative data-driven research with industry partners.
