Dr. Jessica Korte is an Honorary Senior Research Fellow at the University of Queensland's School of Electrical Engineering and Computer Science. Her research focuses on inclusive technology design, particularly involving marginalized groups like Deaf communities. She leads the Auslan Communication Technologies Pipeline project, an AI-based system for Auslan signing, supported by a TAS DCRC Fellowship. Her work emphasizes participatory design with children and minority groups, including international workshops and distributed design methodologies. Her academic background includes a PhD in Human-Centered Computing (2017) and an Honours thesis on requirements prototyping with Deaf children (2012). Key research areas span Human-Computer Interaction, Machine Learning, and accessibility technologies. Recent projects include Zelda Smart Home prototypes and collaborative efforts like the World's Most Inclusive Distributed Participatory Design Project. Dr. Korte actively recruits research students interested in Auslan context technologies, such as machine learning, video GANs, and procedural animation. She has published extensively in venues like the International Journal of Child-Computer Interaction and CHI Conference series, addressing topics ranging from sign language recognition to ethical design considerations. Key Achievements: 2024 TAS DCRC Fellowship, global participatory design leadership, over 30 conference publications Grants & Awards: TAS DCRC Fellowship, ARC CoEDL funding Labs/Teams: Auslan Communication Technologies Pipeline, Zelda Smart Home Project, Distributed Participatory Design Network
Dr. Yun Kuen Cheung serves as a Tenure Track Lecturer in the School of Computing at the Australian National University (ANU), where his interdisciplinary research bridges computer science, mathematics, and economics to analyze modern economic systems. He holds a PhD from the Courant Institute of Mathematical Sciences at New York University. His research focuses on computational approaches to economic dynamics, particularly examining stability, efficiency, and fairness in attention markets (e.g., recommender systems), gig economies (e.g., ride-sharing platforms), and prediction markets using algorithmic and mathematical techniques. Key research areas include: Algorithmic Game Theory Computational Economics General Equilibrium Theory Dynamical Systems and Chaos Theory Discrete Mathematics applications in economic modeling Dr. Cheung currently serves as Co-Investigator on the active ARC-funded project 'Interactions of Human and Machine Intelligence in Modern Economic Systems' (2024-2026), which examines gig economies, stock markets, and prediction markets. He recently taught 'Algorithmic Game Theory And Economics' at the Australian Mathematical Sciences Institute (AMSI) 2024 summer school, with course materials publicly available at comp-math-econ.academy. He actively recruits PhD students with strong foundations in computer science (algorithms, optimization), mathematics (dynamical systems, graph theory), or economics (game theory, general equilibrium theory), emphasizing interdisciplinary excellence in research.
Dr. Yunzhong Hou is a Research Fellow at the School of Computing, The Australian National University (ANU), where he collaborates with Prof. Tom Gedeon and Dr. Liang Zheng. He holds a PhD in Computer Science from ANU (2019–2023) and a Bachelor's in Electronic Engineering from Tsinghua University (2014–2018). His research focuses on computer vision and deep learning, particularly in multiview detection, sensor optimization, and efficient AI systems. Education: PhD in Computer Science, ANU (2019–2023) Bachelor of Electronic Engineering, Tsinghua University (2014–2018) Research Interests: Multi-view detection and tracking Active vision and sensor optimization Efficient AI systems His work spans topics such as camera configuration optimization for pedestrian detection, deep learning for color quantization, and multi-camera systems. He has contributed to projects like the socioeconomic impact analysis of water reforms and privacy-preserving perception for robotics. Hou serves as a reviewer for top conferences (CVPR, ICCV) and journals (TPAMI, TIP). His research emphasizes scalable solutions for real-world applications, including drone vision control and edge computing optimizations. Current projects include machine learning for socio-economic analysis and privacy-aware robotic perception.
Associate Professor Dirk H.R. Spennemann is a leading cultural-heritage scholar at Charles Sturt University , Australia, holding an appointment within the School of Agricultural, Environmental and Veterinary Sciences . He lectures and supervises in Cultural Heritage Management and Historic Ecology at the Albury-Wodonga campus. Education: Doctor of Philosophy (Prehistory), Australian National University, 1990 Master of Arts (Prehistory), Johann Wolfgang Goethe-Universität Frankfurt, 1982 Research Interests: Dirk’s work straddles two major domains. First, as a foremost authority on Micronesian history and heritage , he has conducted extensive fieldwork across the Indo-Pacific, producing over 400 peer-reviewed outputs. Second, he spearheads the emerging field of heritage futures , applying strategic foresight to anticipate how contemporary and emergent heritages—ranging from modernist architecture to space exploration and generative AI—will be valued and managed by future societies. Complementary strands include digital heritage, technological and space heritage, heritage policy, rural vernacular architecture, and the interplay between heritage and community mental health. His recent publications reveal a methodological expansion into sensory ethnography of tourism sites, citizen-science approaches to ecological monitoring, and digital-forensic techniques for born-digital heritage, reflecting a commitment to innovative, cross-disciplinary inquiry. Awards & Recognition: Partnership Stewardship Award for Cultural Resources, US National Park Service (2001) Governor’s Humanities Award for Excellence in Research and Publication, CNMI (2004) CSU Vice-Chancellor’s Award for Teaching Excellence (1995) CSU Vice-Chancellor’s Award for Research Excellence (1996) Supervision & Grants: Dirk is a registered principal supervisor for higher-degree research candidates in cultural heritage and environmental history. While specific grant amounts are not disclosed, his sustained productivity (334+ research outputs and 18 datasets since 2020) indicates robust ongoing funding and institutional support. Laboratories & Teams: He is affiliated with the Gulbali Research Institute and participates in cross-faculty research groups focusing on heritage futures and sustainable environments. Editorial roles include Associate Editor for Campus-wide Information Systems and Editorial Board member for Disaster Advances .
Ricardo Ruiz Baier is a Professor of Computational Mathematics at Monash University in Melbourne, Australia, where he also holds an ARC Future Fellowship. He is affiliated with the Victorian Heart Institute and the Monash Data Futures Institute, highlighting his interdisciplinary research bridging mathematical theory with biomedical applications. His research focuses on the design and analysis of numerical methods for partial differential equations, particularly those that preserve the physical properties of natural phenomena. His expertise includes fundamental topics in numerical analysis and scientific computing such as analysis of finite volume and finite element methods using mixed and augmented formulations, space-time adaptivity and error estimation, perturbed saddle-point problems, multiphase flow and transport in porous media, cardiac electrophysiology and electromechanics, and interface problems. His recent publications reveal a strong emphasis on virtual element methods, poroelasticity models, and cardiac mechanics applications. His work spans theoretical numerical analysis, computational methods development, and practical biomedical applications, particularly in cardiac modeling. The research demonstrates a consistent focus on multiphysics problems and the development of robust numerical schemes for complex coupled systems. Scientific Awards: ARC Future Fellowship FT22 for 'Next-generation methods for transport in poroelastic media with interfaces' Australian Research Council Discovery Project DP21 for 'Towards predictive 4D computational models for the heart' Ruiz Baier actively supervises a large research group with numerous PhD students and postdoctoral researchers working on diverse aspects of computational mathematics. His group has secured funding from multiple sources including Monash Mathematics, the Australian Research Council, IITB-Monash Doctoral Programme, and international government scholarships. He frequently organizes major conferences and workshops, including the Computational Techniques and Applications Conference (CTAC 2024) and MATRIX workshops on numerical analysis. His research group operates at the intersection of mathematics, computational science, and biomedical engineering, with particular focus on developing computational models for cardiac function and mechanics. The group collaborates with international institutions including the University of Oxford and University of Oslo.
John Anthony Kanis is a Researcher (past) affiliated with the Mary MacKillop Institute for Health Research within the Faculty of Health Sciences . His work focuses on osteoporosis, bone health, and fracture risk assessment, particularly through the development and application of the FRAX tool. He has contributed extensively to understanding sarcopenia, geriatric medicine, and the intersection of chronic diseases like dementia and cancer with bone health. His research emphasizes translational studies, including clinical trials evaluating vitamin D, omega-3 supplements, and exercise programs. He collaborates globally to refine intervention thresholds and promote equitable osteoporosis management in diverse populations, including conflict zones. Key contributions include calibrating FRAX models for race-specific populations and assessing cost-effectiveness of therapies like romosozumab. Recent studies highlight the role of sarcopenia in fracture risk, the predictive value of clinical and biochemical markers, and strategies to mitigate falls in aging populations. His work bridges epidemiology, clinical practice, and public health policy to improve bone health outcomes worldwide.
Professor Bradley Evans is a distinguished Earth observation and remote sensing specialist at the University of New England, where he holds a position in the Faculty of Science, Agriculture, Business and Law within the School of Environmental and Rural Science. His expertise spans environmental science, biodiversity conservation, and the application of hyperspectral imaging spectroscopy to solve real-world environmental challenges. Previously, he has held significant positions including Director of Australia's Terrestrial Ecosystem Research Network and Director of Sydney Informatics Hub at The University of Sydney. PhD in Environmental Science, Murdoch University, Western Australia, 2013 Bachelor of Science with Honours in Environmental Science, Murdoch University, Western Australia, 2009 Bachelor of Science in Energy Studies, Murdoch University, Western Australia, 2009 Advanced Diploma in Marketing Management, TAFE NSW, Bradfield College, 1999 CASA RPAS sub 25kg (Multirotor Drone) certification Professor Evans's research focuses on applying advanced remote sensing techniques to environmental monitoring and conservation. His work integrates hyperspectral imaging with ecological modeling to address critical issues such as koala habitat mapping, forest health assessment, and water quality monitoring. He has pioneered approaches using plant fluorescence to model growth patterns and has contributed significantly to NASA's OCO2 mission. His recent work emphasizes the development of open-source tools for hyperspectral imaging, making advanced remote sensing more accessible to researchers worldwide. Analysis of Professor Evans's recent publications reveals a strong trend toward practical applications of hyperspectral imaging across diverse environmental contexts. His work spans from precision agriculture applications for cotton farming to koala habitat conservation, demonstrating the versatility of remote sensing technologies. The research shows increasing integration of machine learning techniques with hyperspectral data, enhancing the accuracy and efficiency of environmental monitoring systems. There's also a notable emphasis on open-source solutions, reflecting his commitment to democratizing access to advanced remote sensing technologies. 2016 – Terrestrial Ecosystem Research Network NSW – NSW Chief Scientist Award Multiple travel scholarships from NCCARF, EUFAR, and Australian Research Council 2010 Centre of Excellence for Climate Change PhD top-up Scholarship 2008 Master class Scholarship from Wentworth Group of Concerned Scientists Professor Evans has successfully supervised numerous PhD and Master's students across multiple institutions, demonstrating strong mentorship capabilities. His research is supported by substantial grants including the $198K NSW Department of Environment Koala's in the Landscape project (2023), the University of Sydney's Koala's in the Air project ($70K), and significant funding for the OpenHSI initiative. He has been a Chief Investigator for the Australian Research Council Training Centre on CubeSats, UAVs and Their Applications, securing funding for innovative remote sensing projects. His work with NASA JPL's Surface Biology and Geology Study and collaborations with international space agencies demonstrates the global impact of his research. At the University of New England since 2023, Professor Evans has established the Earth Observation Laboratory with a special focus on water and wildlife habitat (particularly koalas) and riverine water quality. He serves as Vice President of Earth Observation Australia and participates in the AquaWatch Steering Committee for the Commonwealth Department of Defence. His laboratory actively collaborates with industry partners like HyVista Corporation and academic institutions including The University of Sydney. The lab emphasizes open-source approaches to remote sensing technology, exemplified by the OpenHSI project, which has created accessible hyperspectral imaging solutions for researchers worldwide.
Professor Ned Rossiter is a media theorist and Director of Research at the Institute for Culture and Society , Western Sydney University. He holds a professorship in Communication within the School of Humanities and Communication Arts, where he explores network cultures, data politics, and the geopolitics of automation. His research spans logistical media, cultural labor, and planetary infrastructures. Current HDR advising roles Active research projects on automation's geopolitics Rossiter's research integrates media theory , critical infrastructure studies , and geopolitical analysis to examine how digital infrastructures shape labor, territory, and governance. His recent work focuses on data centers, cloud topologies, and the environmental impacts of logistics networks. Current projects include The Logistical Episteme and Entropological Materialism: Infrastructure, Cybernetics, Environment , both analyzing the material and conceptual dimensions of global infrastructures. His projects with collaborators like Brian Neilson and Soenke Zehle emphasize cross-border logistics and ecological entanglements. Selected Research Outputs : Software, Infrastructure, Labor: A Media Theory of Logistical Nightmares (2016) Organization after Social Media (2018, with Geert Lovink) Co-directed research on data governance, blockchain, and migration logistics Qualifications : Doctor of Philosophy, Edith Cowan University Postgraduate Diploma in Arts Bachelor of Arts, Edith Cowan University
Ali Mirzaghorbanali is an Associate Professor of Geotechnical Engineering at the University of Southern Queensland, affiliated with the School of Engineering and the Centre for Future Materials. His career spans roles from Lecturer (2017) to Senior Lecturer (2019) before his current position since 2023. He holds a BEng from Isfahan University of Technology (2007), an MPWE from Curtin University (2009), and a PhD from the University of Wollongong (2014). His research focuses on geomechanics, mining sustainability, grouting technology, and rock bolt systems, with over 100 publications and significant industry collaboration. Notable contributions include advancing cable bolt performance evaluation, sustainable grout development using waste materials, and numerical modeling of geotechnical systems. His work aligns with industry needs, evidenced by $4.6M in grants, including ACARP projects and industry partnerships with companies like Jennmar Australia and BHP. Mirzaghorbanali has been honored with prestigious awards such as the UniSQ Excellence Award for Early Career Researcher (2020) and Wiley Better Future Award (2018). He supervises doctoral students in areas like sustainable grout development, rock bolt technology, and circular economy applications. His editorial roles include Geotechnical and Geological Engineering and the Resource Operators Conference proceedings. Key projects include the 'Carbolt™ Prototype' (ACARP) and 'Sustainable Amended Concrete' (OT Mine). His research bridges academia and industry, addressing challenges in mining safety, resource efficiency, and environmental sustainability.
Rajeev Gore is a Professor in the Department of Data Science & AI at Monash University. His research focuses on formal verification, automated theorem proving, and logic systems. He has contributed significantly to areas including modal logics, voting system verification, and cryptographic protocols. Gore has been actively involved in developing verified decision procedures for modal logics and exploring applications in electronic voting systems. His work bridges theoretical computer science and practical applications, with a particular emphasis on ensuring correctness through formal methods. Key contributions include the N-PAT nested model-checker and verified verifiability frameworks for voting systems like BeleniosVS and ElectionGuard. His research also addresses trust domains and cryptographic applications, reflecting a deep engagement with both foundational and applied aspects of logic and computation. Gore's publications span over two decades, demonstrating sustained contributions in formal systems, automated reasoning, and security-critical applications. His work often combines rigorous mathematical foundations with practical tool development, emphasizing trustworthiness and verifiability in complex systems.
Alexey Ignatiev is a Senior Lecturer in Monash University's Department of Data Science & AI. His research develops SAT/SMT-based methods for AI applications including explainable AI, automated software debugging, and neuro-symbolic systems. Key projects: Formal Explainability for Neuro-Symbolic AI (ARC-funded) Hierarchical Abstractions for Neuro-Symbolic Systems Recent publications focus on formal explanation techniques for machine learning models, including defect prediction systems and interpretable rule extraction.
Ben Duan is an Adjunct Lecturer at the Department of Data Science & AI, Faculty of Information Technology, Monash University. He holds a PhD in Big Data and Electronics from the University of Technology Sydney. Previously, he was a Research Fellow at the Hong Kong University of Science and Technology. His research focuses on reinforcement learning, graph neural networks, intelligent transportation systems (ITS), and fintech. He teaches courses such as FIT5221: Intelligent Image and Video Analysis, FIT5215: Deep Learning, and FIT5217: Statistical Data Modeling at Monash’s Suzhou campus. Dr. Duan’s work aligns with UN Sustainable Development Goals related to sustainable cities and communities (SDG 11) and industry innovation (SDG 9). His recent research explores AI-driven solutions for traffic congestion, stock trend prediction using graph neural networks, and spiking neural networks for neural activation control. He has contributed to over 28 publications and a patent with the Monash Suzhou Research Institute. He supervises PhD students interested in reinforcement learning, graph neural networks, or ITS, offering full scholarships at Monash Suzhou. Key collaborations span transportation systems, fintech, and data-driven industrial processes.
John Betts is a Senior Lecturer in the Department of Data Science & AI at Monash University's Faculty of Information Technology. He serves as Course Director for the Bachelor of Information Technology and previously held roles as Chief Examiner and Lecturer for multiple IT units. His research focuses on computational modelling, optimization, simulation, and data science, with applications in societal polarization, healthcare, and retail inventory systems. Education: Doctor of Philosophy (Operations Research), Monash University (2003) Graduate Diploma in Statistics/Operations Research, RMIT University (1996) Postgraduate Diploma in Mathematics and Mathematics Education, University of Melbourne (1992) Diploma in Education, Monash University (1984) Bachelor of Arts, Monash University (1983) Research Interests: Dr. Betts explores computational methods to address variability in complex systems, including agent-based modeling for societal polarization, optimization in healthcare (e.g., prostate brachytherapy), and simulation-driven decision-making in retail and transportation. His work contributes to UN SDGs related to education and sustainable cities. Projects: Leading the Optimising multi-item retail inventories project (2021–2026) focusing on inventory optimization algorithms. Contributing to the Biofocussed Prostate Cancer RadioTherapy (BiRT) project (2017–2021), developing personalized radiation therapy plans. Investigating Societal Polarization dynamics via agent-based models and hate crime measurement frameworks. Advising & Grants: Dr. Betts has secured $2.5M+ in research funding, including ARC grants for retail optimization and prostate cancer treatment planning. He advises on interdisciplinary projects spanning computer science, healthcare, and social sciences. Labs/Teams: Collaborates with Monash’s Data Science Institute and the Australian Research Data Commons, contributing to the Temporal Networks Security group and Health Informatics initiatives.
Maroš Servátka is a Professor of Economics at Macquarie Business School and Founding Director of the MQBS Experimental Economics Laboratory. He also serves as Deputy Director of the MBA Program. Previously, he held roles such as Economics Discipline Leader at Macquarie Graduate School of Management and Associate Professor at the University of Canterbury, where he directed the New Zealand Experimental Economics Laboratory. He is a former President of the Slovak Economic Association and holds editorial roles at the Journal of Behavioral and Experimental Economics and the Economic Science Association's Executive Committee. Maroš Servátka earned his MA in Quantitative Methods from the Warsaw School of Economics and a PhD in Economics from the University of Arizona. He held a postdoctoral position at the University of Mannheim. His research focuses on experimental and behavioral economics, with applications in charitable giving, business strategy (advertising, customer service, project planning), government policy (budget execution, public policy), stock exchange algorithms, and organizational governance. He employs experimental methods to explore topics such as honesty, trust, project management inefficiencies, and behavioral nudges to combat procrastination. He has received notable awards including the Excellence in Research Award (2021) for Prosperous Economies research and the Ronald Coase Institute Outstanding Achievement Award (2019). Maroš has advised various organizations, including government agencies and non-profits, on behavioral solutions. His funded projects include studies on windfall gains and natural resource governance. He teaches MBA students to apply experimental techniques in organizational problem-solving. He leads the MQBS Experimental Economics Laboratory and collaborates internationally, focusing on behavioral economics applications across disciplines.
Hassan Doosti is a Senior Lecturer at the School of Mathematical and Physical Sciences, Macquarie University. His research focuses on statistical methodologies, particularly in flexible modeling techniques for complex datasets, with applications in medical studies and business analytics. He has authored or edited books such as Flexible Nonparametric Curve Estimation and Ethics in Statistics: Opportunities and Challenges . Research Interests Nonparametric estimation including wavelet methods and density estimation Statistical modeling of health-related data (e.g., colorectal cancer, stroke) Development of novel statistical algorithms (e.g., censored regression, numerical dependency analysis) Ethical considerations in data analysis for medical sciences Recent Projects Outside Studies Program (2025) APRIntern: Disease Risk Modelling (2019) Key Contributions His work bridges theoretical statistics with practical applications, including: Development of adaptive wavelet quantile density estimation techniques Statistical analysis of neurological and oncological data Advancing methods for handling censored and zero-inflated datasets Awards Recipient of the Faculty of Science and Engineering Award for Inter-School Collaboration (2023) for collaborative research excellence. Professional Activities Editor of multiple peer-reviewed books and active contributor to interdisciplinary projects involving healthcare, data science, and biostatistics.
