Find Academic Supervisors

Regina FabryView profile

Lecturer

• Philosophy of Mind
• Cognitive Science
• Narrative Practices
• +5 more

Regina Fabry is a Lecturer in the Department of Philosophy at Macquarie University, Australia, affiliated with the School of Humanities Ethics and Agency Research Centre. Previously, she held positions at Ruhr University Bochum (Lecturer, 2018–2021) and Justus Liebig University Giessen (Postdoctoral Researcher, 2016–2018). Her research focuses on situated cognition, affectivity, and the socio-cultural influences on self-narration and grief, particularly in the context of emerging technologies like deathbots. She holds a PhD in Philosophy (summa cum laude) from Johannes Gutenberg University Mainz (2015), awarded the Barbara Wengeler Prize for her work on enculturated predictive processing. Fabry’s research is funded by grants including an ARC DECRA (2021–2024) and explores interdisciplinary themes in AI ethics, cognitive science, and literary studies. **Education**: PhD in Philosophy, Johannes Gutenberg University Mainz (2012–2015) MA in Comparative Literary Studies, Philosophy, and Theatre Studies, Johannes Gutenberg University Mainz (2007–2012) **Research Interests**: Combines empirical cognitive science with feminist theory to study narrative practices, grief, and AI ethics. Current projects include analyzing deathbots’ impact on grief dynamics and the socio-cultural situatedness of self-narration as tools of oppression or resistance. Her work bridges philosophy, psychology, and technology studies. **Articles Trends**: Recent publications address grief in digital contexts (deathbots), narrative ethics (e.g., gaslighting), and cognitive frameworks like predictive processing. Her work frequently intersects with technology’s role in shaping human experiences. **Awards**: Barbara Wengeler Prize 2016 for doctoral dissertation on enculturated cognition. **Teaching & Grants**: Teaches courses on AI ethics, including PHIL8400 (Rights, Responsibilities, and AI). Supervises postgraduate research in philosophy of mind and AI. Leads projects like “Living to tell, telling to live” (2021–present) and co-leads “A lone or lonely life?” (2025–2028) on autism and loneliness. **Labs/Teams**: Engaged in interdisciplinary collaborations on grief, narrative theory, and AI ethics, leveraging her background in philosophy, psychology, and literary studies.

Kok Sheik WongView profile

Professor

• Multimedia Signal Processing
• Cybersecurity
• Data Hiding
• +9 more

Kok Sheik Wong is a Professor and Deputy Head (Research) at the School of Information Technology, Monash University Malaysia. He holds a Doctor of Engineering from Shinshu University, Japan, and Master’s and Bachelor’s degrees in Computer Science and Mathematics from Utah State University, USA. His academic leadership and research excellence are central to his role at Monash. B.S. Computational Mathematics, Utah State University (2002) M.S. Computer Science, Utah State University (2006) M.S. Mathematics, Utah State University (2004) Doctor of Engineering, Shinshu University, Japan (2009) His research focuses on multimedia signal processing and cybersecurity , particularly in data hiding , reversible data hiding , coverless steganography , and multimedia encryption . He is also expanding into digital health , applying AI to mental health in workplace environments. His work aligns with UN SDGs, particularly in health and education. The recent publication trends show a strong emphasis on reversible data hiding , image watermarking , and AI-driven health applications . His interdisciplinary work spans computer science, engineering, and public health, with increasing focus on real-world impact through EU and national grants. He has received several honors, including: Academic of Science Malaysia - Young Scientist Network (2020) Best Paper Award, IWDW 2019 ITEX 2021 Gold Medal for BAITRADAR School of IT Excellence in Research Award (2022) Dr. Wong actively supervises PhD students and leads major research projects, including the EU-funded WAge project. He has served as an associate editor for IEEE Signal Processing Letters and the Journal of Information Security and Applications, and is a member of IEEE IFS and APSIPA technical committees. His grants reflect strong external collaboration and funding in cybersecurity and digital health. He is involved in key research labs and teams through Monash University and international consortia, particularly in the areas of multimedia security and digital health innovation. His leadership in the WAge project connects him with European and Asia-Pacific research networks, enhancing global impact.

Tim LynarView profile

Senior Lecturer

• Cyber Security
• Computer Science
• Machine Learning
• +6 more

Dr. Tim Lynar serves as a Senior Lecturer at the University of New South Wales Canberra within the School of Systems & Computing. With a strong background in both academic research and industry practice, he has established himself as a leading figure in cyber security and computer science. His work bridges theoretical research with practical applications, focusing on innovative solutions for complex computing challenges across multiple domains including IoT security, machine learning applications in cyber defense, and high-performance distributed systems. Dr. Lynar's research interests span a wide spectrum of cyber security applications, with particular emphasis on the application of machine learning techniques to security challenges and the innovative use of epidemiological approaches to understand and combat cyber threats. His work in modeling & simulation, statistical & data analysis, network & systems administration, and high-performance distributed computing demonstrates his commitment to developing comprehensive security frameworks that address evolving threats in digital environments. The interdisciplinary nature of his research connects computer science with biological modeling approaches, creating novel methodologies for understanding security vulnerabilities. Analysis of Dr. Lynar's recent publications reveals a strong trend toward applying advanced machine learning techniques to cyber security challenges, particularly in IoT environments. His work increasingly integrates epidemiological models with security frameworks, creating a unique approach to threat detection and mitigation. The research spans practical applications in network security, drone systems, and AI security, demonstrating both theoretical depth and real-world applicability. A notable pattern is the consistent application of cutting-edge deep learning architectures like Vision Transformers and Variational Autoencoders to solve specific security problems across diverse domains. IBM Master Inventor (2016) Multiple IBM Innovation Awards (2011-2018) Client Value Outstanding Technical Achievement Awards (2015-2016) High Value Patent Awards (2014-2016) Best Article Award – International Journal of Information Systems & Social Change (2010) Multiple research scholarships from 2007-2010 Dr. Lynar's extensive patent portfolio demonstrates significant industry impact, with numerous issued US patents spanning diverse applications from energy efficient supercomputing to vehicle collision avoidance and drone-based microbial analysis. His research has attracted substantial industry collaboration, particularly with IBM, where he received multiple prestigious awards including the IBM Master Inventor designation. The practical applications of his work are evident in the wide range of patented technologies addressing real-world security and optimization challenges across multiple industries. Dr. Lynar's work spans multiple research domains simultaneously, with active projects in cyber security, drone systems, AI safety, and maritime traffic analysis. His research methodology consistently combines theoretical modeling with practical implementation, often leveraging simulation environments to test and validate approaches before real-world deployment. The interdisciplinary nature of his work creates connections between traditionally separate fields, enabling innovative solutions to complex problems.

• Arithmetic Algebraic Geometry
• Algebraic Number Theory
• Modular Forms
• +3 more

John Voight is a Professor in the School of Mathematics and Statistics at the University of Sydney, where he is also a member of the Algebra and Computational Algebra groups. His research focuses on arithmetic algebraic geometry, modular forms, and computational number theory. He collaborates with the Magma computational algebra system development team and contributes to databases like the LMFDB. Affiliations: University of Sydney (2024–present), Dartmouth College (2007–2024), University of Vermont (2007–2013). Key research interests include modular curves, Shimura varieties, elliptic curves, and abelian varieties. He explores algorithmic methods for computing with algebraic structures, such as quaternion algebras and ideal class groups. Publications span over 90 articles, including works on Hilbert modular forms, Belyi maps, and paramodular varieties. Notable achievements include the Selfridge Prize (2010 and 2018) and Simons Foundation grants. He advises numerous PhD students and has contributed to major projects like the LMFDB, advancing computational tools for number theory.

• Cryptography
• Elliptic Curves
• Post-Quantum Cryptography
• +1 more

Dr. Huseyin Hisil is a Lecturer in Cryptography at the University of Wollongong's School of Computing and Information Technology. His research focuses on asymmetric cryptosystems, including elliptic curve cryptography, hyperelliptic curves, and post-quantum cryptographic solutions. He develops optimized algorithms for multiprecision arithmetic and finite field operations. Recent publications address efficient elliptic curve arithmetic using Karatsuba-friendly primes and Jacobian coordinate systems for genus 2 curves. His work bridges computational number theory with practical cryptographic implementations, enhancing security and performance in next-generation systems. He teaches undergraduate courses including Introduction to Web Technology (CSIT128) and Web Development (CSIT884), while coordinating Professional Capstone Projects (CSIT998). His research group explores cryptographic pairings and algebraic structures relevant to quantum-resistant protocols.

David HarveyView profile

Professor

• Computational Number Theory
• Arithmetic Geometry
• Fast Polynomial Arithmetic
• +3 more

Professor David Harvey is a faculty member at the School of Mathematics and Statistics within the University of New South Wales (UNSW), where he has held positions ranging from Courant Instructor to his current professorship. He is also a Fellow of the Australian Mathematical Society . Ph.D. in Mathematics (Harvard University, 2008) B.Sc. in Mathematics with First Class Honours and University Medal (UNSW, 2002) Harvey's research focuses on computational number theory and arithmetic geometry , with emphasis on fast polynomial and integer arithmetic algorithms. His work includes groundbreaking advancements in O(n log n) complexity for integer multiplication, leveraging techniques such as Fast Fourier Transforms , lattice reduction , and p-adic cohomology for zeta function computations. His publications from 2018–2024 demonstrate expertise in algorithm design for problems in number theory , algebraic geometry , and cryptography , with recurring themes of computational efficiency , finite field arithmetic , and polynomial operations . 2022 N.G. de Bruijn Medal (shared) 2019 Australian Mathematical Society Medal 2016 Journal of Complexity Best Paper Award Harvey has led significant research grants including the ARC Future Fellowship (2017–2021) and the ARC Discovery Project , focusing on zeta function algorithms and point-counting on algebraic surfaces . He co-organizes the UNSW Number Theory Seminar.

Warwick TuckerView profile

Professor

• Dynamical Systems
• Chaos Theory
• Computer-Assisted Proofs
• +3 more

Warwick Tucker is a Professor in the School of Mathematics at Monash University. He holds a PhD in Mathematics from Uppsala University (1998) and a Docent qualification (2004). His research focuses on dynamical systems, chaos theory, and computer-assisted proofs with applications to complex systems and artificial intelligence. Key contributions include rigorous analysis of the Lorenz attractor, validation of numerical methods for differential equations, and studies on Julia sets and celestial mechanics. He leads a major project on non-hyperbolic dynamics funded until 2026. Notable awards include the EMS Prize (2004) and Moore Prize (2002). Collaborations span global institutions including École Normale Supérieure de Lyon. His work bridges pure mathematics with computational tools, emphasizing algorithmic proof techniques and validated numerical analysis.

John A G RobertsView profile

Professor

• Nonlinear dynamical systems
• Integrable dynamical systems
• Symmetry and Time-reversal symmetry
• +3 more

John A G Roberts is a Professor and Deputy Head of the School of Mathematics and Statistics at the University of New South Wales (UNSW), Sydney. He serves as Chief Investigator of the ARC Centre of Excellence MASCOS and is Vice-President of the Australian Mathematical Society. His academic career spans several decades with significant contributions to nonlinear dynamical systems research. Roberts' research primarily focuses on nonlinear dynamical systems, with particular expertise in integrable dynamical systems, symmetry and time-reversal properties, and algebraic dynamics. His work bridges pure mathematics with applications in mathematical physics, exploring the deep connections between arithmetic properties and dynamical behavior. He has developed novel approaches to understanding integrability through algebraic and arithmetic methods, particularly in the context of discrete systems. Analysis of his recent publications reveals a strong emphasis on algebraic entropy, lattice equations, and the arithmetic structure of dynamical systems over finite fields. His work demonstrates consistent innovation in applying number-theoretic methods to dynamical problems, with a particular focus on symmetry properties and integrability criteria for discrete systems. The interdisciplinary nature of his research connects mathematical physics, algebraic geometry, and computational mathematics. Chief Investigator of the ARC Centre of Excellence MASCOS Vice-President of the Australian Mathematical Society Roberts actively supervises PhD students and has collaborated with numerous research associates including Dinh Tran, Alina Ostafe, Natascha Neumaerker, and Danesh Jogia. He has organized several major conferences including the Workshop on Algebraic, Number Theoretic and Graph Theoretic Aspects of Dynamical Systems (Sydney, 2015) and Dynamics Days Asia Pacific 6 (Sydney, 2010), demonstrating his leadership in the international dynamical systems community. His research program maintains strong connections with institutions worldwide, particularly with collaborators in Europe and North America.

• Number Theory
• Cryptography
• Finite Fields
• +4 more

Professor Igor Shparlinski is a faculty member at the University of New South Wales (UNSW) within the School of Mathematics & Statistics, holding the rank of Professor with an active research profile as evidenced by publications dated 2025. His work bridges pure number theory and cryptographic applications, maintaining international collaborations with institutions like the University of Sydney and Max Planck Institute. Research interests include: Analytic number theory (exponential/character sums) Cryptographic security (Diffie-Hellman, RSA, and pseudorandom generators) Finite field arithmetic and polynomial dynamics Arithmetic combinatorics and additive number theory Distribution of primes/smooth numbers modulo p Elliptic curve structures over finite fields His publications consistently address foundational problems with computational implications, particularly focusing on sum bounds and modular arithmetic. Recent trends (2023-2025) show intensified work on multilinear character sums, matrix statistics over finite fields, and dynamical system orbits. Key journals include Journal of Number Theory and Finite Fields and their Applications , with frequent co-authorship on exponential sum bounds and cryptographic vulnerabilities. Scientific awards: No awards, prizes, or fellowships are documented in the provided text. Advising and grants: No student listings or grant information appears in the source material. Research output suggests sustained funding but lacks explicit details.

• Mathematics Education
• Teacher Professional Development
• Student Learning Strategies
• +4 more

Anne Roche is a Casual Academic and past researcher associated with the School of Education within the Faculty of Education and Arts. Her work focuses on mathematics education, particularly in areas such as teacher professional development, student learning strategies, and pedagogical content knowledge. She has extensively studied topics like fractions, decimals, task-based learning, and teacher noticing across international contexts, including Australia, China, and Germany. Her research emphasizes the importance of contextualized tasks and challenging mathematical problems in fostering student engagement and conceptual understanding. She has contributed to projects aimed at improving teacher knowledge, such as the 'Early Numeracy Research Project' and studies on mathematics middle leaders' aspirations for classroom learning. Roche's work also explores teacher decision-making processes, the use of visual tools like decimats for decimal place value, and strategies to build student persistence in problem-solving. Her findings have been disseminated through peer-reviewed journals such as ZDM Mathematics Education, Mathematics Education Research Journal, and The Journal of Mathematical Behavior. While her articles highlight collaborative efforts with institutions worldwide, her academic contributions lack explicit mentions of awards or grants listed in the provided texts. Her publications span over two decades, reflecting sustained engagement with foundational and applied aspects of mathematics education.

• Energy-Efficient Computing
• Hardware Acceleration
• Machine Learning
• +3 more

Dr. David Boland is a Senior Lecturer at the School of Electrical and Computer Engineering, University of Sydney. He holds an MEng and PhD from Imperial College London. His research focuses on energy-efficient hardware acceleration, particularly using FPGAs and application-specific integrated circuits (ASICs), to optimize computational efficiency in domains like machine learning and optical communications. He has contributed to projects involving custom hardware accelerators, federated learning for edge computing, and real-time signal processing. Education: MEng, Imperial College London, 2007 PhD, Imperial College London, 2012 Research Interests: Dr. Boland’s work emphasizes reducing computational overhead through customized hardware solutions. He explores techniques for minimizing unnecessary computations while maintaining accuracy, leveraging FPGA-based designs for parallelism and energy efficiency. Key areas include: Hardware acceleration for machine learning FPGA optimization for neural networks Energy-efficient algorithms for edge computing Online arithmetic and latency-accuracy trade-offs Grants & Collaborations: 2022: On-Board Federated Learning in Orbital Edge Computing (NSW Department of Industry) 2017: Fast Automated Anomaly Detection in Communication Networks (Defence Science & Technology Group) Affiliations: Member of the Net Zero Institute, collaborating on sustainable computing solutions.

• Computer Vision
• Machine Learning
• Image Processing
• +4 more

Adjunct Professor Shuai Wan is affiliated with the School of Engineering at RMIT University (City Campus, Australia). His research focuses on computer vision, machine learning, 3D point cloud compression, neural video coding, and remote sensing . Key contributions include lightweight deep learning frameworks for image/video compression, spatio-temporal context models for point clouds, and adaptive quantization techniques. Research Outputs Insights : Wan’s work spans 2024–2025 , emphasizing end-to-end deep learning solutions for challenges in Exemplar-based colorization with semantic attention Rendering-oriented 3D point cloud compression Slimmable video codecs with variable bitrate G-PCC standard enhancements for quantization and entropy coding Adversarial example detection in remote sensing Technical Domains : His articles intersect artificial intelligence, signal processing, and computer graphics , with applications in cloud gaming, SAR systems, and industrial data compression. Methods include transformers, attention networks, and 3D convolutional architectures .

• Control Systems
• Signal Processing
• Automation Engineering
• +1 more

Professor Minyue Fu is an Honorary Professor in the School of Engineering at the University of Newcastle, Australia, specializing in Electrical and Computer Engineering. With over 30 years of research experience, he has established himself as a leading expert in control systems and signal processing, having published over 500 research papers with an H-index of 55. His academic journey began with a Bachelor's degree from the University of Science and Technology of China, followed by M.S. and Ph.D. degrees from the University of Wisconsin-Madison. Prof. Fu's research interests span a broad range of topics in control theory and signal processing. His work consistently focuses on fundamental theoretical problems with practical applications in diverse fields including power systems, sensor networks, multi-agent systems, and cyber-physical systems. He has made significant contributions to distributed control algorithms, stochastic systems, quantization effects in control, and networked systems. His recent publications (2021-2024) demonstrate continued productivity and relevance in the field, with research spanning decentralized optimal control, anomaly detection in cyber-physical systems, cart-pole control systems, and mean-field games. These works reflect his ability to bridge theoretical control concepts with practical engineering challenges, particularly in the context of modern networked and distributed systems. Fellow of IEEE (2004) Fellow of IFAC (2022) Fellow of Engineers Australia Fellow of Chinese Association of Automation (2018) Throughout his career, Prof. Fu has held significant editorial positions including Editor of IEEE Transactions on Signal Processing (2010-2014) and Associate Editor for several prestigious journals. His research has been supported by numerous grants, though specific details aren't provided in the current text. His laboratory work has focused on practical implementations of control algorithms in various systems, demonstrating the real-world applicability of his theoretical contributions. Prof. Fu has also supervised numerous students throughout his career, though specific names aren't listed in the available information.

Peter BrownView profile

Senior Lecturer

• Number Theory
• History of Mathematics

Peter Brown serves as an Honorary Senior Lecturer at the School of Mathematics and Statistics, University of New South Wales (UNSW), Sydney. His academic role centers on undergraduate education as a casual tutor across first and second-year pure mathematics courses, while maintaining active research contributions in theoretical and historical mathematics. His research program bridges Number Theory and History of Mathematics, with significant work in Diophantine equations, arithmetic functions, and elliptic curves alongside cultural studies of Chinese mathematics and ancient Greek texts. This dual focus manifests in publications spanning rigorous theoretical proofs and contextual historical analysis, demonstrating consistent scholarly output from 1997-2015. Publication trends reveal evolving expertise: early work concentrated on classical number theory problems (Pell equations, Möbius functions), while later research incorporated historical dimensions (Chinese mathematics, cultural revolutions) and educational monitoring. The interdisciplinary nature connects abstract mathematical structures with socio-historical frameworks. Scientific Recognition Vice Chancellor's Teaching Award (2009) Science Faculty Lecturer of the Year (2016) Brown's teaching excellence has been formally acknowledged through university-wide awards, highlighting his effectiveness in foundational mathematics instruction. While specific grant funding and doctoral advising aren't documented, his sustained publication record and educational monitoring work indicate ongoing scholarly activity. The absence of laboratory facilities aligns with his theoretical research profile in pure mathematics.

Sarah HopkinsView profile

Associate Professor

• Mathematical Cognition
• Learning Difficulties
• Inclusive Education
• +6 more

Sarah Hopkins is an Associate Professor in the Faculty of Education at Monash University , dedicated to reducing educational inequalities through interdisciplinary research in Mathematical Cognition and inclusive education. Her work integrates cognitive psychology and mathematics education to address learning difficulties, particularly among students from disadvantaged backgrounds and those with intellectual disability. Developed the Keyboard , a visual-spatial tool to enhance arithmetic strategy development Coordinated the Keep on Learning (KoL) Program for adults with intellectual disability Current ARC Discovery Project examines classroom applications of the Keyboard for lower primary students Research Interests span mathematical cognition, retrieval strategies, procedural flexibility, and inclusive pedagogy. Her projects often involve collaborations with the Spencer Foundation , ARC , and Ecstra Foundation , focusing on tool development, assessment design, and teacher training. Methodological Expertise includes Rasch analysis, microgenetic approaches, and mixed-methods research. She works with interdisciplinary teams to validate measurement scales and analyze longitudinal learning outcomes, particularly for marginalized groups.