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Professor Ben Goldys is a distinguished academic at The University of Sydney's School of Mathematics and Statistics, where he conducts research at the intersection of pure mathematics and applied sciences. His work spans multiple disciplines including stochastic analysis, partial differential equations, and financial mathematics, with significant contributions to both theoretical frameworks and practical applications in science and finance. Goldys' research interests center on stochastic (ordinary and partial) differential equations and their applications. His specific focus areas include stochastic partial differential equations, stochastic geometric PDEs, stochastic boundary value problems, stochastic fluid dynamics, ergodic theory of infinite-dimensional diffusions, and applications in financial mathematics such as interest rate derivatives, credit risk, and stochastic volatility. His work bridges pure mathematical theory (Functional Analysis, PDEs, Ergodic Theory) with complex real-world problems across multiple domains. His research aligns with the University of Sydney Faculty of Science Research Strengths including Understanding the Universe, Fundamental Laws of Nature, Complex Systems, and Next Generation Materials. Professor Goldys has secured multiple significant research grants from the Australian Research Council, including recent projects such as 'Mathematics for future magnetic devices' (2024), 'Mathematics for breaking limits of speed and density in magnetic memories' (2019), and 'Novel Approaches for Problems with Uncertainties' (2015). His current research projects focus on geometric stochastic partial differential equations and applications in micromagnetism, mean field games in finance, stochastic boundary value problems, and stochastic Navier-Stokes equations on the rotating sphere. He maintains extensive international collaborations with institutions in Germany (University of Tuebingen), Italy (LUISS University), Poland (Institute of Mathematics Polish Academy of Sciences), and the United Kingdom (University of York), working on projects involving optimal control, stochastic systems with memory, and geometric stochastic PDEs. Goldys is an active member of the Applied Mathematics Research Group and The University of Sydney Nano Institute, contributing to interdisciplinary research initiatives that connect mathematical theory with cutting-edge technological applications.

• Stochastic Differential Equations
• Financial Mathematics
• Partial Differential Equations
• +5 more

Scientia Professor Gary Froyland is a Professor at the University of New South Wales (UNSW), affiliated with the School of Mathematics & Statistics. He leads the ARC Laureate Centre for Dynamical Systems and Data and holds an Einstein Visiting Fellowship from the Einstein Foundation Berlin. His academic credentials include a BSc (Hons 1, Medal) in Pure and Applied Mathematics from the University of Queensland and a PhD in Mathematics from the University of Western Australia. Professor Froyland's research spans two primary domains: dynamical systems and optimization. In dynamical systems, he investigates the interplay of probability and geometry in nonlinear and chaotic systems, employing tools from ergodic theory, functional analysis, and differential geometry. His work extends to applications in oceanography, atmospheric science, and granular flows. In optimization, he focuses on decision-making in complex systems with uncertain information, developing novel approaches in mathematical programming that have been applied to mining, logistics, and medical treatment planning. His recent publications demonstrate a strong focus on coherent structures in dynamical systems, linear response theory, and applications to geophysical phenomena. The research shows increasing interdisciplinary collaboration, particularly with climate scientists and data analysts, reflecting a trend toward applying advanced mathematical techniques to real-world problems in environmental science and engineering. J.D. Crawford Prize (2025) Elected Member of the Academy of Europe / Academia Europaea (2024) ARC Laureate Fellow (2024-2029) Fellow of the Society for Industrial and Applied Mathematics (SIAM) (2021) Fellow of the Australian Academy of Science (2020) Vice-Chancellor's Award for Teaching Excellence - Postgraduate Research Supervision (2015) Professor Froyland actively supervises PhD and honors students, with current advisees including Kevin Felipe Kühl Oliveira, Nicholas Peters, and Kathrin Völkner. His research is supported by multiple grants, including an ARC Laureate Fellowship (2024-2029) for "Breakthrough mathematics for dynamical systems and data," an Einstein Visiting Fellowship (2022-2026), and several ARC Discovery Projects. His work has practical applications in climate science, mining optimization, and medical treatment planning, particularly in radiotherapy. He leads the ARC Laureate Centre for Dynamical Systems and Data, which brings together researchers to develop new mathematical approaches for analyzing complex dynamical systems. The center focuses on creating methods to identify coherent structures in spatiotemporal data, with applications spanning environmental science, social science, health science, and engineering.

• Dynamical Systems
• Machine Learning
• Optimisation
• +12 more

Dr Jordan Pitt is an academic affiliated with the University of Sydney's Faculty of Science. He holds the role of Associate Dean (Indigenous Strategy and Services) while also actively contributing as an applied mathematician. His work emphasizes interdisciplinary research and Indigenous inclusion in academia. Dr Pitt completed his PhD at the Australian National University in 2019, focusing on tsunami and storm surge modeling. He pursued post-doctoral research at the University of Adelaide, where his studies expanded into ocean wave-sea ice interactions. Current research investigates how wave dynamics influence sea ice growth/melt cycles, a critical factor in Earth's climate systems. Research Interests: Mathematical modeling of environmental systems Ocean wave mechanics Climate change impacts on sea ice Computational fluid dynamics While no specific scientific awards are explicitly listed, Jordan has been involved in initiatives like co-convening the Academy of Science’s 'Looking Back, Moving Forward' Public Lecture Series (2023) and organizing the ANZIAM 2024 Early Career Workshop. His efforts bridge Indigenous communities with STEM fields through programs like Science Pathways. As an educator and researcher, Jordan has not listed formal advisees or grants in the provided texts. His professional networks include roles in Indigenous strategy and academic service. Jordan’s work is associated with laboratories and teams focused on environmental fluid dynamics and climate modeling, though specific lab names are not mentioned.

• Applied Mathematics
• Climate Science
• Oceanography
• +3 more

Professor Khac Duc Do is a faculty member at Curtin University, holding a position in the School of Civil and Mechanical Engineering within the Faculty of Science and Engineering. He serves in the Office of the Provost and is based at Curtin Perth campus. His research focuses on advanced control systems, nonlinear dynamics, and robotics applications in marine, aerospace, and mechanical systems. He earned a PhD with distinction in 2003 and has held prestigious fellowships including ARC Postdoctoral Fellow (2004) and ARC Australian Research Fellow (2009). His teaching includes courses like Advanced Control and Mechatronics, Navigation and Marine Control Systems, and Advanced Control Engineering. Key research interests encompass control of nonlinear systems, stochastic systems, formation control of mobile agents, fluid-structure interaction, and boundary control of PDE-governed systems. His funded projects include wave-energy converter development (2023-2026), inerter-based damper research (2019-2021), and ocean vehicle control systems. Scientific awards include ARC grants totaling over AUD 2 million. Current opportunities include scholarships in control systems/fluid-structure interaction and a postdoc position in wave-energy conversion.

• Control of Nonlinear Systems
• Autonomous Marine Vehicles
• Partial Differential Equation Systems
• +3 more

Associate Professor Jiakun Liu (FAustMS) is affiliated with the School of Mathematics and Statistics, University of Sydney . He holds a BSc from Zhejiang University (2006) and a PhD from the Australian National University (2010). Following a Simons Postdoctoral Fellowship at Princeton (2010-2013), he served as Lecturer, Senior Lecturer, and Associate Professor at the University of Wollongong (2013-2024), securing an ARC DECRA in 2014 and an ARC Future Fellowship in 2024. Specializes in nonlinear elliptic/parabolic PDEs with applications in geometry and optimal transportation Research focuses on Monge-Ampère/Hessian equations , regularity theory, and geometric flows Contributions to convex geometry , minimal surfaces, and stochastic PDEs . His 2024-2023 publications in Communications on Pure and Applied Mathematics , Advanced Nonlinear Studies , and Archive for Rational Mechanics demonstrate expertise in free boundary regularity , noncompact Minkowski problems , and global geometric analysis . Recognized with ARC Future Fellowship and conferences organized across Australia-China collaborations.

• Nonlinear Elliptic and Parabolic Partial Differential Equ.ations
• Regularity Theory of Monge-Ampère Equations
• Hessian Equations
• +6 more

Xiaoping Lu is an Associate Professor at the School of Mathematics and Applied Statistics, University of Wollongong, Australia. She has served as Academic Program Director for the Bachelor of Mathematics (Advanced) program since 2008 and holds an ORCID identifier (0000-0003-1090-8437). Her research focuses on applied mathematics and financial mathematics, particularly in option pricing, stochastic volatility models, and computational finance. Research Themes: Transaction cost modeling, regime-switching financial markets, numerical methods for PDEs, utility-indifference valuation, and stochastic optimization algorithms. Awards: 2024 AustMS-WIMSIG Anne Penfold Street Award 2024 Cheryl E. Praeger Travel Award Leadership: President of the Asia Pacific Consortium of Mathematics for Industry (APCMfI) since 2024; leadership roles in ANZIAM and WIMSIG committees. Teaching: Coordinated courses like MATH142, MATH141, and MATH283; currently available for PhD supervision in topics including financial derivatives and stochastic liquidity risk. Funding: Contributed to grants like 'The AI Tutor' (2024) and industry partnerships for advanced mathematics education.

• Applied Mathematics
• Financial Mathematics
• Numerical and Computational Mathematics
• +3 more

Assoc. Professor Mariano Rodrigo is affiliated with the University of Wollongong. His primary research focuses on Biological mathematics , Financial mathematics , Numerical solution of differential and integral equations , and Dynamical systems in applications . His work bridges applied mathematics with real-world problems in tourism economics and physical sciences. Research Funding: Weather, climate & geological risks: derivative pricing & risk management (2024–2026, ARC Discovery Project) Modelling the post-stagnation stage of a tourism area life cycle (2023, UOW Internal Grant) Teaching & Supervision: Current PhD supervision topics include Derivative Pricing for Geological Risks , Mathematical Models for Time of Death Estimation , and Weather/Climate Risk Modelling .

• Biological mathematics
• Financial mathematics
• Numerical solution of differential and integral equations
• +3 more

Dr. Emma Carberry is a Lecturer in the School of Mathematics and Statistics at the University of Sydney, within the Faculty of Science. Her research focuses on differential geometry and integrable systems, particularly harmonic maps, conformal surface theory, and constant mean curvature surfaces. She is a member of the Sydney Southeast Asia Centre. Her research interests include geometric applications of integrable systems, spectral curves, and the interplay between differential geometry and complex algebraic geometry. Notable contributions include studies on harmonic tori, Whitham deformations, and constant mean curvature surfaces in various spaces. Dr. Carberry has secured grants including the DVC Research/Brown Fellowship (2016) and DVC Research/Laffan Fellowship (2010). Her teaching includes advanced courses such as MATH3968 (Differential Geometry: Advanced), Honours Riemannian Geometry, and undergraduate modules like MATH1011 (Applications of Calculus). Her academic work spans over two decades, with publications in journals like the Journal of Geometry and Physics and the Journal of the London Mathematical Society. She collaborates internationally and maintains an active research profile in geometric analysis and integrable systems.

• Differential Geometry
• Integrable Systems
• Harmonic Maps
• +3 more

Haotian Wu is a Senior Lecturer in the School of Mathematics and Statistics at The University of Sydney, where he maintains an active research program in geometric analysis. His academic appointments include membership in the Geometry, Topology and Analysis Research Group, and he has been involved in organizing significant mathematical events including the AMSI Summer School 2025 and the Symposium on Geometric Analysis and Non-linear PDEs. Dr. Wu's educational background includes a PhD in Mathematics from The University of Texas at Austin (2013) and dual Bachelor's degrees in Mathematics and Physics from Lafayette College (2007). His research aligns with the University's Faculty of Science Research Strengths in Understanding the Universe, Fundamental Laws of Nature, and Complex Systems. Wu's research focuses on geometric evolution equations, particularly Ricci flow and mean curvature flow. His work investigates singularity formation, stability properties, and asymptotic behavior in these flows, with significant contributions to understanding Type-II singularities. His research bridges pure mathematics and mathematical physics, with applications to general relativity and geometric analysis. He has developed novel analytical techniques for studying nonlinear partial differential equations arising in geometric contexts. Analysis of Wu's publication record shows a consistent trajectory of high-impact research in geometric analysis, with increasing focus on numerical methods for studying geometric flows in recent years. His work demonstrates strong international collaboration, particularly with researchers in the United States, including notable collaborations with Garfinkle, Isenberg, Knopf, and Zhang. The publications reveal a progression from foundational work on Ricci flow to increasingly sophisticated analyses of mean curvature flow and related geometric evolution equations. Australian Research Council (ARC) Discovery Early Career Researcher Award (DECRA) 2018 for 'Singularity Analysis for Ricci Flow and Mean Curvature Flow' Faculty of Science Faculty Startup Scheme 2023 for 'Elliptic and parabolic problems in geometric analysis' Dr. Wu currently supervises research students including Alexander BEDNAREK (working on General Kahler Ricci Flow) and Tiernan CARTWRIGHT (working on Hölder regularity of solutions to degenerate complex Monge–Ampère equations). He has received multiple research grants supporting his work in geometric analysis. Wu has been actively involved in teaching undergraduate mathematics courses including MATH1021 Calculus of One Variable, MATH2061 Linear Mathematics and Vector Calculus, and specialized courses like MATH3968 Differential Geometry. As an active member of the mathematical community, Wu co-organizes significant research events including the AMSI Summer School 2025 and the International Conference on Nonlinear Partial Differential Equations honoring Professor Neil Trudinger's 80th birthday. His research group focuses on geometric analysis problems with connections to mathematical physics and differential geometry.

• Geometric Analysis
• Differential Geometry
• Partial Differential Equations
• +3 more

Professor Dingxuan Zhou is a distinguished academic serving as Professor and Head of School of Mathematics and Statistics at The University of Sydney, joining the institution on August 29, 2022. He is also a member of The Net Zero Institute and has held significant editorial positions, including editor-in-chief of the journal "Analysis and Application" of "Mathematical Foundations of Computing" and serving on the editorial boards of over ten international journals. Educational Background: BSc in Mathematics from Zhejiang University, China (1988) PhD in Mathematics from Zhejiang University, China (1991) Professor Zhou's research spans learning theory, neural networks, wavelet analysis, and approximation theory, with his current focus on the theory of deep learning. His work aligns with the Faculty of Science Research Strengths in Complex Systems, Precision and Digital Health, Data and Decisions, and National Security. His research demonstrates a consistent progression from foundational mathematical theory to cutting-edge applications in machine learning and artificial intelligence, with particular emphasis on understanding the theoretical underpinnings of neural networks and deep learning systems. His extensive publication record reveals a strong trend toward distributed learning frameworks, approximation theory for neural networks, and the mathematical foundations of deep learning. Recent work focuses on federated learning, transformers, physics-informed neural networks, and the theoretical analysis of over-parameterized networks, reflecting the evolving landscape of machine learning research with increasing emphasis on theoretical guarantees and practical applications. Scientific Awards: Humboldt Research Fellowship (1993) Fund for Distinguished Young Scholars from the National Science Foundation of China (2005) Highly-cited Researcher by Thomson Reuters/Clarivate Analytics (2014-17) World's Top 2% Scientist by Stanford University (2021, 2022, 2023) Professor Zhou has demonstrated exceptional leadership in research and mentorship, having conducted over 40 research grants as Principal Investigator, supervised more than 20 PhD students, and co-organized over 20 international conferences. His collaborative approach is evident in his extensive co-authorship network across multiple institutions globally. He has also served in significant administrative roles including Head of Department of Mathematics (2006-12), Associate Dean of School of Data Science (2018-22), and Director of the Liu Bie Ju Centre for Mathematical Sciences (2019-22) at City University of Hong Kong.

• Learning Theory
• Neural Networks
• Deep Learning
• +6 more

Dr. Sahani Pathiraja is a Lecturer (tenure track assistant professor) at UNSW Sydney , specializing in Data Science . Her research bridges mathematical and statistical foundations with practical applications in environmental and biomedical sciences. Research Focus : Sequential Bayesian inference, Monte Carlo methods, stochastic analysis of non-linear filtering, uncertainty quantification, and real-time parameter estimation. Current Projects : Co-investigator in the ARC Industrial Transformation Training Centre: Data Analytics for Resources and Environment (DARE) and the Next Generation Graduate Program (NGGP) in Sports Data Science and AI . Research Supervision : Dr. Pathiraja supervises PhD students in areas including: Bayesian inference Stochastic differential equations Data assimilation Non-linear filtering Scientific Collaborations : Her work intersects with environmental science, biomedical applications, and machine learning. Projects include stochastic hydrology, SDEs, and operator learning for environmental systems. Contact Information : Email: s.pathiraja@unsw.edu.au Phone: +61 2 8065 0836 Office: Room 2070, Level 2, The Red Centre, UNSW Sydney

• Data Science
• Bayesian Inference
• Stochastic Analysis
• +7 more

Professor Georg Gottwald is a distinguished academic in the School of Mathematics and Statistics at the University of Sydney, where he has been a faculty member since 2002, progressing from Lecturer to his current position as Professor since 2013. He also holds a Visiting Professor position at the University of Surrey in the UK since 2013. His extensive research career spans dynamical systems theory, geophysical fluid dynamics, and the intersection of machine learning with complex systems. Professor Gottwald's research focuses on dynamical systems theory as an abstract formalism for studying systems evolving in time and space. His work has significant applications across diverse fields including climate modeling, biological systems, and complex networks. He is particularly known for developing methods for model reduction of complex dynamical systems, stochastic modeling approaches, and the application of machine learning techniques to dynamical systems. His research aligns with the Faculty of Science Research Strengths in Understanding the Universe, Fundamental Laws of Nature, Complex Systems, Climate and Environmental Change, Data and Decisions, and National Security. His most recent publications demonstrate a strong trajectory toward integrating machine learning with dynamical systems theory, particularly in developing stable generative models, learning dynamical systems with random feature maps, and combining data assimilation with machine learning for forecasting. His work spans pure mathematical theory to practical applications in climate science, finance, and biological systems, showing remarkable breadth while maintaining deep mathematical rigor. Future Fellowship, 'Stochastic methods in mathematical geophysical fluid dynamics', Australian Research Council, 2010-2014 Australian Research Fellowship, 'Stochastic methods in mathematical geophysical fluid dynamics', Australian Research Council, 2010-2015 (declined) Australian Research Fellowship, 'Geometric methods in geophysical fluid dynamics', Australian Research Council, 2004-2009 Professor Gottwald has successfully supervised numerous PhD and Master's students who have gone on to academic and industry positions worldwide. His current research group includes postdocs and PhD students working on machine learning for dynamical systems, stochastic model reduction, physics-informed machine intelligence, and tensor methods for scientific machine learning. He has secured multiple ARC Discovery Project grants and has been involved in significant international collaborative research projects. He is actively involved with the Sydney Dynamics Group, which he co-founded in 2007, fostering collaboration between the University of Sydney and UNSW. Professor Gottwald maintains strong editorial commitments as Associate Editor for Geophysical and Astrophysical Fluid Dynamics, SIAM Journal of Applied Dynamical Systems, and Journal of Computational Dynamics, and serves on the Editorial Advisory Board for Chaos and the Editorial Board for Physical Review E. His professional activities demonstrate leadership in the dynamical systems community through organizing workshops, seminars, and special journal issues.

• Dynamical Systems
• Geophysical Fluid Dynamics
• Climate Modeling
• +5 more

Holger Dullin is a Professor of Applied Mathematics at the School of Mathematics and Statistics, University of Sydney. His research focuses on Hamiltonian dynamical systems, integrable systems, and their applications in mechanics, fluid dynamics, and biomechanics. He serves as a member of the Sydney Southeast Asia Centre and the Applied Mathematics Research Group. Member of Sydney Southeast Asia Centre Member of Applied Mathematics Research Group Research Interests include: Hamiltonian systems and integrability Quantum and classical monodromy Geometric phase phenomena N-body and rigid body dynamics Volume-preserving mappings His work spans from fundamental mathematical physics to interdisciplinary applications in biomechanics and space engineering , with recent studies on light sail stabilization and geometric phase optimization in diving. Publications cover 2024 to 2003, showing sustained contributions to nonlinear dynamics , stability analysis , and symplectic geometry . Teaching includes advanced courses in Hamiltonian dynamics and nonlinear ODEs. Current research students include Babak Attarha and Gleb Palshin , with past supervision of William Tong (PhD 2016) on geometric phases in diving.

• Dynamical Systems
• Hamiltonian Mechanics
• Biomechanics
• +4 more

Dr. Anna Cai is a Lecturer in the Department of Applied Mathematics within the School of Mathematics & Statistics at the University of New South Wales (UNSW), a position she has held since 2011. Prior to this, she served as a postdoctoral researcher and lecturer at the University of California, Irvine from 2007 to 2011. Her educational background: Ph.D., The University of Melbourne, 2008 B.Sc. (First Class Honours), The University of Melbourne, 2004 Dr. Cai's research centers on Mathematical Biology , with specialization in cell migration dynamics , developmental pattern formation , and robustness in biological systems . She employs multi-scale mathematical modeling and stochastic analysis to investigate phenomena ranging from wound healing to zebrafish hindbrain development. Her work bridges theoretical mathematics with experimental biology to decode fundamental mechanisms governing cellular behavior and morphogenesis. Analysis of her 11 publications (2006-2015) reveals an evolutionary trajectory from foundational work on cell migration mechanics to sophisticated studies of developmental robustness. Early research established mathematical frameworks for wound-healing assays and immune cell dynamics, while later work pioneered noise-driven pattern formation models in zebrafish. A unifying thread is her focus on how biological systems maintain precision despite environmental fluctuations. Administrative responsibilities include: Applied representative on the postgraduate review committee UNSW study abroad and exchange course authority Current teaching assignments: MATH2121: Theory and Applications of Differential Equations MATH2018: Engineering Mathematics 2D Prior courses taught: MATH3041: Mathematical Modeling for Real World Systems MATH6781: Biomathematics

• Mathematical Biology
• Biomathematics
• Mathematical Modeling
• +3 more

Dr. Jiakun Liu is an Associate Professor at the School of Mathematics and Applied Statistics, Faculty of Engineering and Information Sciences, University of Wollongong, Australia. He has held this position since January 2022 and maintains an active research program in nonlinear partial differential equations with applications in geometry and optimal transportation. His work has been published in top mathematical journals including Annals of Mathematics, Inventiones Mathematicae, and Communications on Pure and Applied Mathematics. Dr. Liu received his PhD from The Australian National University, Australia. His academic journey includes prestigious fellowships such as the Simons Postdoctoral Fellowship and the Australian Research Council's Discovery Early Career Researcher Award (DECRA). Dr. Liu's primary research focuses on nonlinear elliptic and parabolic partial differential equations, with special emphasis on the regularity theory of Monge-Ampère equations, Hessian equations, and other variational problems. His work extends to related areas of geometry and physics, including the geometry of convex bodies, minimal surfaces, surfaces of prescribed curvatures, and geometric flows. His research has significant applications in optimal transportation theory, which connects mathematical analysis with practical problems in economics, physics, and computer science. Analysis of Dr. Liu's recent publications reveals a strong focus on regularity theory for Monge-Ampère equations and optimal transportation problems. His work spans pure mathematical theory (regularity of solutions, singular sets, free boundaries) while maintaining connections to geometric applications and practical problems. A notable trend is the increasing interdisciplinary nature of his research, with recent work connecting optimal transport to statistical methods and computer science applications. Dr. Liu has received several prestigious awards and fellowships: UIC International Links Scheme (University of Wollongong, 2015) Discovery Early Career Researcher Award (DECRA) from Australian Research Council Discovery Project (DP170100929) from Australian Research Council Shiing-Shen Chern Mathematical Scholarship from Zhejiang University Simons Foundation Simons Postdoctoral Fellowship Dr. Liu is actively involved in mentoring the next generation of mathematicians, having supervised numerous PhD students including Siyuan Li, Jihang Zhang, Phung Trong Thuc, Yating Wu, and Meng Ji. He has also guided honours students such as Matthew Hughes, Luke McDonald, and Brad Rice. His research is supported by multiple grants, including "Singularity and regularity for Monge-Ampere type equations" (2023-2026), "Monge-Ampere type equations and their applications" (2023-2027), and "Monge-Ampere equations and applications" (2020-2024), demonstrating sustained funding for his research program. Dr. Liu is an active participant in the mathematical community, organizing conferences such as the International Conference on Nonlinear Partial Differential Equations (honoring Professor Neil Trudinger's 80th birthday) and the 4th Australia-China Joint Conference on Geometric Analysis. He maintains collaborative relationships with researchers across Australia, China, and internationally, contributing to a vibrant research environment in geometric analysis and PDEs.

• Partial differential equations
• Optimal transportation
• Geometry
• +5 more