جست‌وجوی استاد و پژوهشگر

• Insect Behavior
• Ecology
• Entomology
• +۵ مورد دیگر

Associate Professor Tanya Latty is an entomologist at the University of Sydney's School of Life and Environmental Sciences. She holds a BSc in Biology and Environmental Science from Trent University (Canada) and a PhD in Insect Ecology from the University of Calgary (Canada). Her research focuses on insect behavior and ecology, with interdisciplinary collaborations spanning mathematics, computer science, and operations research. She is a member of the Sydney Institute of Agriculture and leads studies on pollination systems, swarm intelligence, and sustainable insect management. Her current projects include a systems approach to optimizing crop pollination via companion flowers (funded by ARC Future Fellowship) and assessing impacts of prescribed burning on honeybees (AgriFutures Australia grant). She has published extensively on topics like ant transportation networks, slime mould decision-making, and urban bee ecology. Media engagements include features on Quirks & Quarks discussing slime mould cognition and ant navigation. Research themes include bio-inspired technology development, pollination ecology, and invertebrate conservation. Her lab emphasizes Indigenous land acknowledgments, recognizing Gadigal traditional custodianship. Grants total over $2M in recent years, supporting both fundamental and applied ecological research.

Kevin Wangمشاهده پروفایل

پژوهشگر

• Precision Medicine
• Bioinformatics
• Biostatistics
• +۳ مورد دیگر

Kevin Wang is an academic affiliated with the University of Sydney's School of Mathematics and Statistics and Sydney Precision Bioinformatics Group. He holds a PhD in Statistics and Bioinformatics and has worked as a Postgraduate Teaching Fellow. Currently, he is a Senior Data Scientist at Illumina, focusing on bioinformatics for diagnostic technologies and R/Python package development. Education: PhD in Statistics and Bioinformatics (University of Sydney, 2016-2020), Bachelor of Science (Advanced Maths, First Class Honors, 2012-2015). Research Interests: Statistical tools for complex diseases, precision medicine, bioinformatics, and data science applications in genomics. Professional Contributions: Developed packages like mcvis (collinearity visualization), scMerge (single-cell RNA-Seq merging), and learningtower (PISA data access). His work bridges statistical methodology and real-world challenges, with a focus on translational research in healthcare and diagnostic technologies. He actively contributes to open-source tools and collaborates with clinicians and biologists.

• Nonstationary time series econometrics
• Nonparametric statistics
• Econometric Theory
• +۲ مورد دیگر

Professor Qiying Wang is a faculty member in the School of Mathematics and Statistics at the University of Sydney, holding the rank of Professor. His research focuses on advanced statistical theory and econometrics, particularly in nonstationary time series analysis, cointegrating regression, and asymptotic methods. He has published extensively in top journals such as Econometric Theory and Journal of Econometrics . Research Interests: Nonstationary time series econometrics, nonparametric statistics, econometric theory, local time theory, and self-normalized limit theory. He is a leading expert in nonlinear cointegrating regression, developing methodologies for handling endogeneity and nonstationarity in economic and financial data. Selected Grants: 2016: Nonlinear cointegrating regression with endogeneity (Australian Research Council DP) 2012: Asymptotics in nonlinear cointegrating regression (Australian Research Council DP) Key Contributions: Authored the monograph Limit Theorems for Nonlinear Cointegrating Regression (2015) and pioneered techniques for optimal bandwidth selection in cointegrating models. His work bridges theoretical advancements with practical econometric applications.

• Bioinformatics
• Precision Medicine
• Computational Biology
• +۳ مورد دیگر

Professor Jean Yang is a leading academic in bioinformatics and computational biology at the University of Sydney's Faculty of Science. As a member of the Charles Perkins Centre and Sydney Precision Data Science Centre, her research focuses on integrating multi-omics data, single-cell genomics, and machine learning to advance precision medicine and healthcare decision-making. She has pioneered methodologies in kidney transplant outcome prediction, spatial transcriptomics analysis, and cancer genomics. Her work spans computational tools like scMerge2 for single-cell data integration and scSTAR for identifying cell heterogeneity, alongside clinical applications such as predictive models for allograft survival. Yang has secured major grants including the Chan Zuckerberg Initiative funding for biomedical data analysis and NHMRC support for translational research. She collaborates across disciplines, linking statistical methods with clinical challenges in cardiovascular disease, oncology, and transplant medicine. Yang’s lab develops open-source frameworks (e.g., scFeatures, SurvBenchmark) to democratize access to advanced analytical tools. Her recent projects include benchmarking spatial gene expression prediction and optimizing kidney allocation systems. She maintains affiliations with the Sydney-Melbourne Precision Health initiative and the Laboratory of Data Discovery for Health (InnoHK).

• Biostatistics
• Medical Informatics
• Data Science
• +۴ مورد دیگر

Yunwei Zhang is a Lecturer in the School of Mathematics and Statistics at The University of Sydney. She specializes in biostatistics, medical informatics, and data science applications in healthcare, particularly kidney transplantation and precision medicine. Her research bridges statistical methodology with clinical decision-making, focusing on predictive modeling and translational research. She has also contributed to interdisciplinary plant science studies, examining molecular mechanisms in plant growth and stress tolerance. Teaching & Awards: Ms. Zhang has taught courses including Foundations of Data Science (DATA 1001/1901), Statistical Machine Learning (STAT 3888), and Experimental Design (SCIE 4002). She received the Post-graduate Teaching Fellow award from the University of Sydney and Early Career Researcher Awards from the Transplantation Society of Australia & New Zealand. Her Dean's International Postgraduate Research Scholarship supported her PhD work. Research Focus: Her work emphasizes multi-step precision pathways in organ transplantation outcomes, robust statistical methods for survival analysis, and computational tools for healthcare decision support systems. Recent publications highlight advancements in kidney allocation simulation frameworks and collaborative plant biology studies exploring drought tolerance and plant hormone signaling. Key Publications: Over the past five years, her research spans 15+ peer-reviewed articles in journals like Journal of Medical Systems , Briefings in Bioinformatics , and Plant Cell , reflecting her dual focus on medical data science and plant molecular biology. Grants & Honors: In addition to her teaching and research awards, she has secured funding including the Post-graduate Teaching Fellowship ($24k total) and Dean's Scholarship ($153k over three years).

• Sustainable Supply Chain Management
• Green Logistics
• Operations Research
• +۳ مورد دیگر

Ben Fahimnia is a Professor and Chair in Decision Sciences (Supply Chain Management) at the University of Sydney Business School. He holds a PhD, MEng, GradCert, and BEng. As the youngest Australian Full Professor in 2016, his expertise spans sustainable supply chain management, logistics optimization, and behavioral supply chain dynamics. He directs the Supply Chain & Logistics Association of Australia (SCLAA) and founded the Chance and Choice Lab and Sound of Silence Productions. His research focuses on green logistics, supply chain resilience, and the integration of behavioral economics into supply chain decision-making. Key publications include Green Logistics and Transportation (Springer, 2015) and Planning and Optimisation of Complex Supply Chains (2011). Recent work addresses perishable goods management, retail promotions, and intermodal transport sustainability. Dr. Fahimnia has secured grants from Innovative Manufacturing CRC, iMOVE CRC, and the Australian Research Council. He advises on supply chain resilience, AI applications, and global supply chain strategies. His media engagements include ABC Online, Sydney Morning Herald, and Ausbiz, discussing topics like vaccine distribution challenges and pandemic supply chain disruptions. Recipient of the 2020 Excellence in Research Award, he emphasizes interdisciplinary collaboration and education innovation. His labs and consultancies focus on transforming supply chain practices through science, creativity, and human-centric approaches.

• Transportation Logistics
• Computational Electromagnetism
• Operations Research
• +۳ مورد دیگر

Dr. Glenn Geers serves as an Adjunct Professor at the University of Sydney Business School. He is an independent consultant specializing in transport domains, with expertise in computational electromagnetism and transportation logistics. Holding honors degrees in electrical engineering and theoretical physics, and a PhD in computational electromagnetism, his academic contributions span interdisciplinary fields. Editorial Board Member: GeoInformatica journal Member: Transportation Research Board Simulation Sub-committee Society Memberships: Society of Industrial and Applied Mathematics, Association for Computing Machinery Research interests include transportation modeling, optimization algorithms, and the application of computational methods to logistics and infrastructure challenges. His recent work explores circular economy strategies in port management, stochastic models for delivery systems, and autonomous technologies in logistics.

• Financial Economics
• Accounting Theory
• Investment Strategies
• +۳ مورد دیگر

David Johnstone is a Professor in the Faculty of Business and Law at the University of Wollongong. He holds a PhD in Economics from the University of Sydney (1985) and undergraduate degrees in Arts (Econometrics) and Commerce (Accounting & Finance) from the University of Wollongong (1980). His career includes academic roles across Australia, New Zealand, and the US, including a Visiting Assistant Professorship at UC Berkeley (1987–1989) and the National Australia Bank Professor of Finance at Sydney (2007–2017). He currently advises the Australian Energy Regulator on electricity pricing and has served as a postdoctoral fellow at Lancaster University (1985–1986). His research focuses on financial markets, investment strategies, and behavioral finance. Notable works include integrating ESG factors into capital asset pricing models and analyzing the intersection of capital budgeting with Kelly betting strategies. Recent publications address methodological challenges in accounting research, particularly around statistical significance. Johnstone has secured grants including a 2019 study on gambling products' behavioral impacts (NSW Office of Responsible Gambling) and a 2012 global credit risk forecasting project (Australian Research Council). His consulting spans regulatory agencies, emphasizing energy market economics and financial policy. While no formal lab affiliations are listed, his work demonstrates cross-disciplinary engagement with economics, statistics, and public policy domains.

• Machine Learning
• Dynamical Systems
• Network Inference
• +۳ مورد دیگر

Eugene Tan is a casual teaching lecturer and PhD student in Multi-Discipline at The University of Western Australia. His primary affiliation is with UWA's research community, focusing on interdisciplinary studies. Research interests include dynamical systems, machine learning applications in network analysis, and model validation techniques. Notable areas involve network inference using recurrent neural networks, persistent homology for time series analysis, and cognitive dissonance effects in social dynamics. Recent work explores embedding methods for complex systems, attractor-based change detection, and fault diagnosis algorithms. His contributions bridge theoretical frameworks with practical applications in data science and engineering. Collaborations span international teams addressing nonlinear dynamics and topological data analysis. No formal awards are listed, though his research shows strong growth in citations and interdisciplinary impact.

• Bayesian statistics
• Spatio-temporal modeling
• Environmental science
• +۴ مورد دیگر

Edward Cripps is an Associate Professor in the School of Physics, Maths and Computing at The University of Western Australia, specializing in Mathematics and Statistics. He holds degrees including a BEc from UWA and a PhD in Statistics from UNSW. His research focuses on Bayesian longitudinal analysis, spatio-temporal models, and integrating physical models with probabilistic approaches for environmental, meteorological, and oceanographic applications. He leads major grants including the ARC Industrial Transformation Research Hub for Transforming Energy Infrastructure (2021-2025) and the DARE Training Centre (2021-2025). Collaborations include industry partners like INPEX, Shell, Woodside, and governmental bodies such as the Bureau of Meteorology. He teaches undergraduate courses in probability and applied statistics. Grants & Awards: ARC Hub ($10M) as Chief Investigator/Data Science Leader (2021-2025) MinEx CRC 2022-2023 publication prize (2023) Research Interests: His work addresses model-data mismatch in complex systems, leveraging high-quality data for decision-making in resource management and engineering. Recent projects include geophysical feature discovery, spectral estimation bias correction, and offshore wind turbine structural analysis.

Linqing Wenمشاهده پروفایل

استاد

• Gravitational Wave Astrophysics
• Multi-messenger Astronomy
• High-performance Computing
• +۴ مورد دیگر

**Linqing Wen** is a Professor in the School of Physics, Mathematics and Computing at The University of Western Australia (UWA). He leads the Gravitational Wave Astronomy Group and holds roles such as Chief Investigator in the ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav). His work focuses on gravitational wave astrophysics, real-time detection, and multi-messenger astronomy, with contributions to the LIGO-Virgo Collaboration (LVC) and the SPIIR search pipeline. **Education**: PhD in Astrophysics from MIT (2001), MS in Physics and ME in Computer Science from PSU (1995), and BS in Condensed Matter Physics from USTC (China, 1992). Professional experience includes roles at Caltech, the Max-Planck Institute, and UWA since 2004. **Research Interests**: Gravitational Wave Astrophysics, High-performance Computing, Machine Learning for GW detection, and Early Warning Systems. Notable projects include SPIIR pipeline development, GW multi-messenger studies, and GPU acceleration for real-time analysis. **Awards**: 2016 Special Breakthrough Prize (shared), ARC Future Fellowship (2009), UPRF Fellowship (2007), and Rossi Fellowship (1995). **Grants & Projects**: Over $30M in funding, including ARC grants for GW detection, multi-messenger astronomy, and pulsar timing arrays. Active roles in OzGrav, UWA research clusters, and international collaborations like the LVC and CRAFT. **Teaching**: Courses include SCIE1121 (introductory astronomy) and specialized modules on Gravitational Wave Astronomy.

• Artificial Intelligence
• Machine Learning
• Formal Methods in Software Engineering
• +۴ مورد دیگر

Mark Reynolds is a Professor and Head of School at the School of Physics, Mathematics and Computing, University of Western Australia (UWA). He holds affiliations with the UWA Oceans Institute, UWA Data Institute, and the School of Social Sciences, Planning and Transport Research Centre. His academic journey includes a Bachelor’s (Hons) in Pure Mathematics and Statistics from UWA, a PhD in Computing from Imperial College London, and a Diploma in Education from UWA. Prior roles include lecturing at King’s College London before returning to UWA as an Associate Professor. Reynolds’ research focuses on AI, Machine Learning, Formal Methods in Software Engineering, Logic, and Optimization. Key projects include the ARC Training Centre for Transforming Maintenance through Data Science and investigations into AI-driven Intelligent Transport Systems. His work spans over $10M in research funding over a decade, addressing industry, ARC, and CRC projects. Teaching contributions include courses in Software Engineering, Computational Modelling, Machine Learning, and Logic. He has supervised 24 PhD (12 completed), 30 Masters, and 10 Honour students. Notable awards include the Journal of Informatics Editor's Choice (2023). His research aligns with UN Sustainable Development Goals, particularly in advancing technology solutions for societal challenges. Recent publications emphasize interdisciplinary applications of AI, including medical physics, transportation optimization, and healthcare informatics. Collaborations span global institutions, reflecting his influence in Temporal Logic, Formal Verification, and Data Science.

• Microbial Ecology
• Biopesticides
• Integrated Pest Management
• +۴ مورد دیگر

Associate Professor Caroline Hauxwell holds a position in the School of Biology & Environmental Science at Queensland University of Technology (QUT). Her research focuses on microbial applications in agriculture, particularly biopesticides and integrated pest management. She leads projects addressing sustainable food production through the development of microbial solutions for crop protection, including biopesticide formulations and mathematical modeling of pathogen dynamics. Education: PhD (Imperial College, London), BA (University of Oxford). Research Interests: Microorganisms in food production, microbial ecology, invertebrate pathology, and the commercialization of biopesticides. Her group collaborates with industries to reduce chemical insecticide use and establish sustainable pest management strategies. Recent work includes international registration of biopesticides and founding a manufacturing company. Experience: Over 25 years of leadership in tropical forestry, pest management, and biopesticide development across Africa, Asia, and the Pacific. Key roles include developing baculovirus and fungal biopesticides, adjuvants for microbial insecticides, and diagnostic programs for plant biosecurity. Grants & Projects: Leads Australian Competitive Grant-funded projects including 'New technology for stored grain pest management' and 'A new biopesticide for Diamondback Moth management in canola'. Collaborates with organizations like GRDC and Queensland Government. Labs & Teams: Heads the Invertebrate Microbiology group at QUT, fostering interdisciplinary research in microbial applications and sustainable agriculture.

Mahsa Abbasabadiمشاهده پروفایل

پژوهشگر

• Biomass Conversion
• Bioenergy Systems
• Sustainable Engineering
• +۳ مورد دیگر

Dr. Mahsa Abbasabadi is a Senior Research Assistant at the Faculty of Engineering, Queensland University of Technology (QUT), affiliated with the Centre for Agriculture and the Bioeconomy. Her research focuses on sustainable bioenergy systems, bioprocess engineering, and valorization of lignocellulosic biomass. She specializes in pretreatment methodologies for agricultural residues like sugarcane bagasse and trash, aiming to enhance biomethane production and biofuel yields through anaerobic digestion and enzymatic hydrolysis processes. Her work integrates biochemical engineering principles with industrial microbiology, particularly in optimizing yeast-based systems for oleaginous biomass production. Dr. Abbasabadi has contributed to scaling up biorefinery processes and developing models for continuous bioethanol production plants. Her research also explores microbial community dynamics and lignin characterization to improve bioprocess efficiency. Key areas of interest include renewable resource utilization, biorefinery integration, and advancing sustainable technologies for agricultural waste conversion. While no awards or grants are explicitly listed, her contributions to bioenergy systems align with QUT's broader goals in the bioeconomy sector.

Annabelle McIverمشاهده پروفایل

استاد

• Program Verification
• Quantitative Information Flow
• Computer Security
• +۳ مورد دیگر

Annabelle McIver is a Professor at the School of Computing, Macquarie University, and a member of the Data Horizons Research Centre, Future Communications Research Centre, and Frontier AI Research Centre. Her research focuses on program verification, quantitative information flow, and privacy-preserving technologies. She holds a DPhil in Mathematics from the University of Oxford and a BA from the University of Cambridge. McIver has held visiting positions at MIT, ETH Zurich, and INRIA, and was a Junior Research Fellow at St Hilda's College, Oxford. Her work has been recognized with awards including the 2015 Best Scientific Cybersecurity Paper and the 2023 Faculty of Science and Engineering Award for Inter-School Collaboration. She leads the Topete Research Group, exploring formal methods and their applications in security and privacy. Her research interests span formal verification, differential privacy, and the mathematical analysis of security flaws. Key projects include work on probabilistic programming, privacy in machine learning, and secure data pipelines. McIver has authored over 125 publications and contributed to initiatives like the Digital Finance CRC and the AIS-SHIELDS project securing health data. Her recent work emphasizes privacy-utility trade-offs in technologies like differential privacy and adversarial attacks. Education: PhD (DPhil) in Mathematics, University of Oxford (1990) BA (Double First) in Mathematics, University of Cambridge (1985) Awards: Best Scientific Cybersecurity Paper (2015) Distinguished Paper Award (2024) Platt Prize (1984) Unwin Prize (1985) McIver collaborates internationally on cybersecurity, privacy frameworks, and formal methods, with active projects in autonomous systems, healthcare data security, and AI ethics.