Dr. Matt Skerritt is a Lecturer in Applied Mathematics at the School of Science, RMIT University, located at City Campus, Australia. His research focuses on Applied Mathematics, Pure Mathematics, and Numerical and Computational Mathematics. He specializes in optimization algorithms, number theory, and computational methods, with notable contributions to the Douglas-Rachford method, Giuga’s primality conjecture, and algorithm extensions like the PSLQ algorithm. He also explores educational tools using software such as Mathematica and Maple, emphasizing computational learning and pedagogy. His work bridges theoretical mathematics with practical applications in computational science and education. Research interests include the dynamics of iterative methods, integer relations, and primality testing, alongside the development of educational resources for computational mathematics. His publications span topics like geometric algorithms, numerical analysis, and symbolic computation, reflecting a commitment to advancing both theoretical and applied mathematical research.
Dr. Heba El-Fiqi is a Lecturer at the School of Engineering and Information Technology (SEIT), UNSW Canberra. Her research focuses on artificial intelligence, swarm intelligence, machine learning, and computational linguistics. Notable contributions include a novel AI-based solution for air traffic control using swarm robotics and the development of the Weighted Gate Layer Autoencoders (WGLAE) for EEG signal recovery. She holds an IEEE active membership, co-chaired Women in Artificial Intelligence (WAI) activities, and served on conference program committees (AAAI, IJCAI, ECAI). Education: PhD in Computer Science (2013): UNSW, Thesis: "Detection of Translator Stylometry using Pair-wise Comparative Classification and Network Motif Mining" Master of Computer Science (2009): Cairo University, Thesis: "An Intelligent System for Tracking Network Attacks" Research Interests: Swarm robotics, autonomous systems, and AI for air traffic management Machine learning applications in signal recovery and medical diagnostics Computational linguistics and translator stylometry Awards: Dell EMC Award of Distinction (2017) IBM Big Data Developer - Instructor Award for Educators (2017) Teaching & Supervision: Course Coordinator for ZEIT4150 (Artificial Intelligence) and ZEIT4151 (Machine Learning) Supervised over 10 undergraduate engineering projects, including work on deep reinforcement learning for autonomous combat and humanoid robot navigation Labs & Teams: Active in UNSW's AI research community, contributing to initiatives like Canberra AI Week and Women in Engineering (WIE) leadership roles.
Professor Ian Manchester is a faculty member in the Department of Mechatronic Engineering at the University of Sydney. He holds a B.Eng (Electrical) Honours and a PhD from the University of New South Wales. His academic roles include Director of the Australian Centre for Robotics and Director of the Australian Robotic Inspection & Asset Management Hub (ARIAM). He has held leadership positions such as Director of Research at the Australian Centre for Field Robotics and co-Director of the Sydney Institute for Robotics and Intelligent Systems. His research focuses on robotics, nonlinear control, system identification, and machine learning, with applications in biomedical engineering, forestry, mining automation, and aviation. He has supervised numerous PhD students working on projects like acrobatic legged robots, surgical robotics, and robotic asset management. Recent publications emphasize robust control methodologies, nonlinear observer design, and stable machine learning models. His work often bridges theoretical advances with practical applications, such as SLAM algorithms and dynamics of walking robots. Prof Manchester has received the Sydney Research Accelerator Fellowship (SOAR) in 2019. He serves on editorial boards for IEEE journals and international conferences. His labs and collaborations include the Australian Centre for Robotics and the ARIAM Hub, focusing on robotic inspection and asset management solutions.
Dr. Masato Kawabata is an Associate Professor at the School of Human Movement and Nutrition Sciences at the University of Queensland . His research integrates sport psychology , exercise science , and nutritional health , focusing on optimizing cognitive, physical, and social outcomes across diverse populations. PhD in Human Movement Studies from the University of Queensland (2008) Kawabata explores the psychological mechanisms of physical activity, including flow theory , motivation , and time perception . His work spans sedentary populations , adolescents , and older adults , with a focus on nonlinear pedagogy and behavioral interventions . Recent publications highlight his expertise in exercise-cognition interactions , sport nutrition ergonomics , and motivational frameworks in physical education. He employs systematic reviews , hybrid trials , and cross-cultural comparisons to advance understanding of optimal human functioning through movement and nutrition. His methodological contributions include refining mental toughness measures , flow state assessments , and dietary-behavior models for athletes and schools. Kawabata's work bridges positive psychology , biomechanics , and public health interventions .
Associate Professor Hui Tian serves as the Discipline Head of Computer Science in the School of Information and Communication Technology at Griffith University, Australia. She holds a PhD in Computer Science from Japan Advanced Institute of Science and Technology and maintains an active research profile with over 80 publications and leadership in multiple international research projects. Her work spans networking, security, and data analysis domains. PhD in Computer Science, Japan Advanced Institute of Science and Technology Professor Tian's research focuses on Network Routing and Tomography, Privacy-preserving Computing, and Knowledge Discovery. Her work addresses critical challenges in data privacy protection, cybersecurity, and wireless communications and networking. She actively explores applications in medical image analysis, IoT security, and distributed energy systems, with a strong emphasis on developing practical solutions for real-world security and privacy challenges. Her recent publications reveal a strong trend toward privacy-preserving technologies, particularly in healthcare applications and wireless networks. There's significant focus on UAV-enhanced mobile edge computing, structural analysis of complex networks, and addressing security challenges like DoS attacks in multi-agent systems. Her work demonstrates interdisciplinary approaches combining machine learning, network theory, and security principles to solve contemporary computing challenges. Best Paper Award (2021) Outstanding Teacher Award from Beijing Jiaotong University (2012) Outstanding Junior Researcher (2005) Professor Tian actively supervises multiple doctoral students across diverse research areas including network security, energy management systems, and point-of-interest recommendation systems. She has secured significant research funding from various sources including the Department of Education, APNIC Foundation, and industry partners like Redx Technology Australia. Her current projects focus on privacy-preserving authentication, adversarial machine learning in wireless networks, and AI-powered solutions for sustainable agriculture in Vietnam. As a senior member of IEEE and active participant in professional activities, Professor Tian serves as associate editor for several SCI-indexed journals and frequently contributes to international conference program committees. Her leadership extends to directing academic programs including the Bachelor of Advanced Computer Science (Honours) and the Graduate Certificate in Data Science at Griffith University.
Dr. Jessica Eastman serves as a Postdoctoral Fellow in the Department of Fundamental & Theoretical Physics at the Australian National University, where she conducts research within the Quantum Optics Group. Her work bridges theoretical quantum physics and practical quantum technology development, focusing on measurement-driven control of complex quantum systems. Her research program centers on quantum chaos and measurement theory, investigating how adaptive observation strategies can stabilize inherently unstable quantum dynamics. This work has significant implications for quantum computing error correction and ultra-precise quantum sensing applications, where controlling decoherence remains a fundamental challenge. Analysis of her publication record reveals consistent contributions to quantum control methodologies, with increasing emphasis on real-time feedback systems. Her 2019 Physical Review A paper established foundational principles for adaptive chaos suppression, while subsequent work expanded into semiclassical analysis of energy fluctuation amplification. Dr. Eastman operates within ANU's vibrant quantum research ecosystem, collaborating closely with senior theorists in the Quantum Optics Group. Her position provides access to the group's computational resources, including the XMDS software package used for high-dimensional quantum simulations across 71 countries.
Dragomir Neshev serves as Professor in the Department of Electronic Materials Engineering at the Australian National University and Director of the ARC Centre of Excellence for Transformative Meta-Optical Systems (TMOS) from 2021 to 2027. His career spans over two decades in advanced optical research, with significant contributions to photonics and metamaterials development. He earned his PhD from Sofia University, Bulgaria in 1999, establishing the foundation for his expertise in optical physics and materials science. Neshev's research focuses on cutting-edge optics branches including periodic photonic structures, singular optics, plasmonics, and optical metasurfaces. His work particularly emphasizes dielectric materials, waveguide physics, harmonic generation, and solitary wave phenomena, driving innovation in nanophotonics and optical engineering. This research has positioned him at the forefront of meta-optical systems development. Recent publications demonstrate a clear trajectory toward practical meta-optical applications, particularly in infrared imaging, polarization control, and analog optical computing. His team consistently pioneers dispersion-engineered metamaterials and guided-mode resonance techniques in dielectric structures, enabling breakthroughs in compact optical systems for sensing and imaging. His distinguished recognition includes: Queen Elizabeth II Fellowship (ARC, 2010) Australian Research Fellowship (ARC, 2004) Marie-Curie Individual Fellowship (European Commission, 2001) Academic award for best young scientist (Sofia University, 1999) Highly Cited Researcher (Web of Science, 2021-2023) Fellow of the Optical Society (OSA) Neshev actively supervises graduate researchers while leading major collaborative projects including the National Facility for Performance Characterisation of Infrared Technologies and space-based meta-optical imaging systems. His current research portfolio features significant ARC funding for transformative optical technologies, with particular emphasis on multi-spectral imaging and polarization control through nanostructured materials. As Director of TMOS, he oversees Australia's premier meta-optics research hub, coordinating efforts across multiple institutions to advance meta-optical systems for real-world applications. His leadership extends to specialized teams focusing on tailored metasurfaces for light generation, programming, and detection, creating an integrated ecosystem for optical innovation from fundamental research to commercial implementation.
Professor Steven Sherwood is a leading climate scientist at the University of New South Wales , holding the rank of Professor in the Climate Change Research Centre. He contributes to the ARC Centre of Excellence for Climate Extremes through research programs on Attribution and Risk, and Weather and Climate Interactions. Education Bachelor of Science in Physics, Massachusetts Institute of Technology (1987) Master of Science in Engineering Physics, University of California (1991) PhD in Oceanography, Scripps Institution of Oceanography, University of California (1995) Research Interests focus on moisture-related atmospheric processes , climate sensitivity , convective feedback mechanisms , and human tolerance to heat stress . His work bridges observational analysis (e.g., weather balloon data), numerical modeling (cloud dynamics, wind gusts), and policy-relevant assessments (IPCC, World Climate Research Programme). Recent Research Trends highlight applications of artificial intelligence for climate downscaling, modeling tipping points in Earth systems, analyzing hail and wind hazards under climate change, and studying cloud albedo biases in high-latitude oceans. Scientific Awards National Science Foundation CAREER Award (2002) Clarence Leroy Meisinger Award, American Meteorological Society (2005) Eureka Prize Finalist (2014) ARC Laureate Fellowship (2015–2020) Leadership and Collaboration includes serving as a Lead Author for the IPCC 5th Assessment Report on Clouds and Aerosols, chairing the World Climate Research Programme’s Safe Landing Climates Lighthouse , and contributing to international climate sensitivity assessments. He also sits on the Science journal review board.
Dr. Quanying Liu serves as Associate Professor in the Department of Biomedical Engineering at Southern University of Science and Technology (SUSTech), where she leads the Neural Computing and Control Laboratory (NCC lab) as Principal Investigator and Doctoral Supervisor. Her academic journey includes a PhD from ETH Zurich in Biomedical Engineering, postdoctoral training at Caltech, and research positions at Huntington Medical Research Institute, KU Leuven, and Oxford University. PhD in Biomedical Engineering, ETH Zurich (2013-2017) Master in Computer Science, Lanzhou University (2010-2013) Bachelor in Electrical Engineering, Lanzhou University (2006-2010) Dr. Liu's research bridges neuroscience, machine learning, and control theory with focus on multi-modal neural signal processing (EEG, sEEG, fMRI, DTI), explainable AI for brain interpretation, and optimization frameworks for neuromodulation (tES, TMS). Her work develops high-density EEG source imaging algorithms, data-driven brain network modeling, and control-theoretic approaches for neural stimulation. The NCC lab specializes in machine learning algorithms, neural computation, multimodal data fusion, network control theory, and bidirectional brain-computer interfaces. Analysis of her recent publications reveals strong trends in EEG-based visual decoding, multimodal neural embeddings, and AI-driven brain network modeling. Her work increasingly integrates generative models for neural data synthesis, control theory for precise neuromodulation, and cross-modal approaches connecting neural signals with cognitive functions. The New Brain 30 (2023) AAIC travel award (2019) Estes Stars Award (2018) Shenzhen Peacock Talent Plan C Dr. Liu actively mentors students through SUSTech's doctoral program and leads multiple significant research initiatives including a National Natural Science Foundation Youth Project, a National Key R&D Program in Bio-Information Fusion, and several Shenzhen municipal projects. Her lab receives funding from Guangdong Provincial Basic Research Fund, Shenzhen Science and Technology Innovation Commission, and international fellowships including Boswell Postdoctoral Fellowship and Swiss National Science Foundation grants. The NCC lab maintains strong international collaborations with Caltech, ETH Zurich, and Oxford University while developing novel platforms like WheelCon for sensorimotor control studies. The Neural Computing and Control Laboratory operates as an interdisciplinary hub integrating computational neuroscience, machine learning, and control engineering. The lab develops specialized hardware-software systems for closed-loop neurostimulation, maintains the EEGdenoiseNET benchmark dataset, and pioneers methods like MOVEA for transcranial electrical stimulation optimization. Current research directions include generative models for neural decoding, network control theory applications, and AI-human cognitive interaction frameworks.
Dr Rebecca Fisher is an Adjunct Research Fellow at the UWA Oceans Institute (The University of Western Australia). Her research spans marine biology, ecology, and environmental science, with a focus on coral reefs , marine protected areas , and Bayesian statistics applications . She contributes to global sustainable development goals through marine conservation research. Key affiliations: University of Western Australia, Australian Institute of Marine Science Research expertise: Coral reef ecology, marine monitoring, ecotoxicology, and Bayesian modeling Recent publications highlight her work on whale shark movement around artificial structures, seismic survey impacts on pearl oysters, and bayesnec software for toxicity modeling. Her collaborations extend across 94 institutions globally, with significant contributions to reef shark conservation and Indigenous sea Country monitoring frameworks. Dataset contributions include fish-habitat relationships , coral health monitoring , and soil bioturbation studies . Research trends emphasize nonlinear ecological modeling , disturbance impacts , and conservation data science .
William Edge serves as a Research Fellow at the School of Earth and Oceans, The University of Western Australia (UWA), where he investigates marine sediment dynamics and internal wave processes. His work directly supports UN Sustainable Development Goals 14 (Life Below Water) and 13 (Climate Action) through environmental modeling and offshore renewable energy research. His research expertise spans sediment transport mechanics, resuspension phenomena, and probabilistic modeling of coastal processes. Key methodologies include Bayesian inversion for erosion parameter estimation and Markov Chain Monte Carlo simulations applied to advection-diffusion systems. This work addresses critical challenges in continental shelf sedimentation, intertidal zone ecology, and seabed stability under nonlinear wave forcing. Recent publications reveal a strong trend toward integrating field observations with advanced computational models, particularly focusing on suspended sediment behavior beneath internal waves and seasonal emersion mortality risks. His research bridges theoretical fluid dynamics with practical environmental management applications. No scientific awards were documented in available sources. While specific grant details remain unreported, Edge collaborates extensively with national marine science initiatives including the National Environmental Science Program. His 2024 co-authored report establishes research standards for Australian offshore renewables, indicating active involvement in cross-institutional environmental policy development. No student supervision information was provided. Edge operates within UWA's marine research ecosystem, contributing to datasets on boundary-layer sediment dynamics and participating in multi-institutional projects with organizations including the Australian Institute of Marine Science.
Dr. Mareike Dressler is a Senior Lecturer (Assistant Professor, tenure-track) at the School of Mathematics and Statistics, UNSW Sydney. She holds a PhD in Mathematics from Goethe University Frankfurt (2018) and has held postdoctoral positions at Max Planck Institute for Mathematics in the Sciences (Leipzig) and University of California, San Diego. Education: PhD (Mathematics, 2018), M.Sc. (2013), B.Sc. (2010) from Goethe University Frankfurt Prior Affiliations: Postdoctoral researcher at MPI MiS (Leipzig), Stefan E. Warschawski Assistant Professor at UCSD, Semester Postdoctoral Fellow at Brown University (ICERM) Her research focuses on Real and Computational Algebraic Geometry, Polynomial and Convex Optimization, Matrix and Tensor Computation, and their applications in Data Science and Machine Learning. She has developed optimization techniques using sums of nonnegative circuit polynomials and explored connections between convex geometry and algebraic structures. Her recent publications span topics including multivariate Chebyshev polynomials, matrix completion ranks, SONC cone duality, and applications of semidefinite programming. Collaborations include work with Venkat Chandrasekaran, Bernd Sturmfels, and Roland Lasserre, with methodological contributions to polynomial optimization and tensor analysis. At UNSW Sydney, she teaches undergraduate and postgraduate courses including MATH 1131 (Mathematics 1A, Algebra) and MATH 5185 (Special Topic: Nonnegativity and Polynomial Optimization). Her research group engages with both theoretical and applied problems in optimization and algebraic methods.
Ania Stasinska serves as a Senior Lecturer at The University of Western Australia's School of Population and Global Health within the Population and Public Health department. With over 16 years of continuous service since 2006, she holds significant teaching responsibilities across undergraduate and postgraduate programs. Bachelor of Health Science (2004, UWA) Graduate Certificate in Business (2008, Curtin University) Master of Public Health (Research) (2014, UWA) Her research centers on environmental epidemiology and maternal-child health , with expertise in chemical exposure assessment (particularly brominated flame retardants through the AMETS study) and environmental determinants of health outcomes. Her work aligns with UN Sustainable Development Goals related to environmental health and well-being. Recent publications demonstrate consistent focus on environmental exposures (air pollutants, persistent chemicals) and health outcomes across lifespan stages - from fetal development to aging populations. Key methodological strengths include prospective cohort designs and exposure mixture analysis in Western Australian populations. Her educational contributions include curriculum development in epidemiology and health systems, with peer-reviewed publications on service learning and communication pedagogy. Ania coordinates PUBH1101 (Health and Illness in Human Populations) and teaches in PUBH2203 (Foundations of Epidemiology) and PUBH5752 (Health Systems and Economics), having developed content for nine undergraduate and two postgraduate units throughout her career.
Valentina Wheeler is a Senior Research Fellow (DECRA Research Fellow) at the University of Wollongong's School of Mathematics and Applied Statistics. Her research focuses on geometric analysis, specializing in elliptic and parabolic partial differential equations with applications to bushfire modeling and biological membranes. She combines techniques from differential geometry, calculus of variations, and dynamical systems to develop novel mathematical frameworks for physical phenomena. Her work primarily explores: Curvature flows and geometric evolution equations Nonlinear PDEs in environmental science Conformal structures and geometric variational problems Mathematical modeling of biological and physical systems Dr. Wheeler maintains an active research program supported by major grants including: ARC Discovery Project: Non-local PDE approach to moving fronts and bushfires (2025-2027) DECRA Fellowship: Curvature flow of clusters (2019-2025) ARC Discovery Project: Parabolic methods for elliptic boundary value problems (2018-2024) She currently supervises PhD candidates in topics spanning nonlinear PDEs, free boundary problems, conformal structures, and curvature flows. Her completed students have researched Monge-Ampere equations, wound healing modeling, and ambient field interactions with geometric flows.
Long Vo is an Honorary Research Fellow at the UWA Business School and The Planning and Transport Research Centre (PATREC), focusing on international trade, finance, and macroeconomic policy. He holds a PhD in Economics from UWA and a Master of Commerce in Finance from Victoria University of Wellington. Education: PhD in Economics, UWA Business School (2016–2020) Master of Commerce in Finance, Victoria University of Wellington (2012–2014) Bachelor of Economics, National Economics University (2006–2010) Research Interests: Modelling global demand for energy and commodities, exchange rate economics, financial asset pricing, and the interplay of technology, intangible capital, and transport networks. He has contributed to projects like PATREC's study on working-from-home impacts and transport networks funded by Western Australia's Department of Transport. Awards: Board of the Graduate Research School Dean's List (2020) Research Training Program Scholarship (2016) New Zealand-ASEAN Scholar Award (2011) Grants & Activities: Participated in conferences like the Australasian Agricultural and Resource Economics Society Conference and peer-reviewed journals such as Energy Economics and Nature Communications . Active in editorial review roles. Labs/Teams: Collaborates with PATREC and the UWA Business School's transport and land-use research initiatives.
