جستجوی استاد راهنمای دانشگاهی

Gregory Markowskyمشاهده پروفایل

مدرس ارشد

• Stochastic processes
• Complex analysis
• Graph theory

Gregory Markowsky serves as a Senior Lecturer in the School of Mathematics at Monash University, maintaining an active research profile with continuous publication output through 2025. His academic appointment shows no indication of part-time status, emeritus designation, or former staff classification. His research centers on three interconnected domains: Stochastic processes, particularly planar Brownian motion and random walk theory Complex analysis with applications to probabilistic models Graph theory focusing on algebraic and combinatorial structures These areas converge in his investigation of probabilistic phenomena with geometric interpretations. Recent publication trends reveal sustained productivity with 61 research outputs cataloged, including 4 articles in 2025 alone. His work demonstrates consistent methodological focus on stochastic analysis and combinatorial structures, with increasing cross-disciplinary applications in forensic science and econometrics as evidenced by 2024-2025 publications. Markowsky has secured three significant research projects funded by the Australian Research Council, including: "Planar Brownian motion and complex analysis" (2014-2017) as Primary Chief Investigator "Finite Markov chains in statistical mechanics and combinatorics" (2014-2017) "AMSI Industry Internship: Melbourne Storm" (2013) His ORCID profile (0000-0003-1656-337X) documents extensive scholarly activity with international collaborations. Professional engagement includes contributions toward UN Sustainable Development Goals through mathematical applications, though specific goal alignments aren't detailed in available materials. His email contact Greg.Markowsky@monash.edu remains active with current research dissemination.

Steven Robertsمشاهده پروفایل

استاد

• Applied Statistics
• Environmental Statistics
• Statistical Epidemiology
• +۶ مورد دیگر

Professor Steven Roberts serves as Dean of the College of Business and Economics at the Australian National University (ANU). He previously held the role of Director at the Research School of Finance, Actuarial Studies & Statistics and has taught Actuarial Studies and Statistics courses within the university. Education: PhD in Statistics from Stanford University Masters in Statistics from Stanford University Research Interests : Steven specializes in Applied Statistics , with a focus on Lasso Regression for high-dimensional data analysis and Time Series Analysis in financial and environmental contexts. His work addresses Model Selection challenges and develops Re-sampling Methods for statistical robustness. Research Trends : His publications demonstrate interdisciplinary applications in Finance (portfolio theory, health insurance economics), Statistics (regression techniques, influence diagnostics), and Public Health (statistical epidemiology). Recent work explores Retirement Expenditure patterns and Actuarial Modelling . Collaborative Projects : Steven has contributed to key initiatives including: Min/Max Autocorrelation Factors in Time Series Studies of Air Pollution Health Effects (2014-2018) Retirement Savings Expenditure Modelling (2014) Bootstrap Methods for Evolutionary Kernel Time-Series Modelling (2009-2010) Air Pollution and Statistical Model Selection (2008-2011)

• Econometrics
• Time Series Analysis
• Copula Models
• +۹ مورد دیگر

Brendan Kinnane Beare is a Professor of Econometrics at the University of Sydney , affiliated with the School of Economics under the Faculty of Arts and Social Sciences. His research focuses on econometric theory, time series analysis, copula modeling, and stochastic processes. Education: PhD in Economics (2007) from Yale University Research areas: Time series, copulas, Markov modulation, unit root testing, financial econometrics Recent work includes stochastic arbitrage with options, Pareto exponents in economic models, and tests for copula symmetry Beare's publication trends span econometric theory, applied statistics, and financial modeling, with a focus on mathematical rigor and empirical relevance. He teaches undergraduate and postgraduate econometrics courses and participates in international seminars on unit roots and cointegration.

• Geophysics
• Seismology
• Planetary Science
• +۴ مورد دیگر

Dr. Zhi Wei is a Postdoctoral Research Fellow at the Research School of Earth Sciences (RSES), Australian National University (ANU), specializing in computational seismology and planetary interior imaging. She joined ANU in February 2023 after serving as a Postdoctoral Fellow at Peking University (2018-2022), with research spanning Earth and planetary seismology through innovative wavefield analysis techniques. Her academic foundation includes: PhD in Geophysics, University of Chinese Academy of Sciences (2013-2018), thesis on S-wave velocity structure of the Australian continent's uppermost mantle Jointly Cultivated Postgraduate at ANU (2016-2017) BSc in Geophysics, China University of Mining and Technology (2009-2013) Dr. Wei pioneers methods for imaging planetary interiors using coda-correlation wavefields and full-waveform inversion, with current projects involving lunar seismology (Australian Space Agency), nuclear explosion monitoring (US Air Force), and 3D modeling of the Macquarie Ridge. Her work bridges fundamental geophysics with applied defense and space exploration initiatives, emphasizing high-resolution seismic imaging of crustal and mantle structures. Analysis of her publications reveals consistent focus on Earth's interior structure (particularly Australia and Sichuan-Yunnan regions), expanding recently into planetary applications (Mars crustal evolution, lunar seismology). Her methodology combines computational seismology with ambient noise tomography, showing increasing interdisciplinary collaboration with space agencies and defense organizations. Her scientific recognition includes: Peking University Boya Fellowship (2020) Multiple Outstanding Student awards from University of Chinese Academy of Sciences (2015-2018) China Scholarship Council and Chinese Academy of Sciences Graduate Scholarships She actively mentors PhD students, currently co-supervising Vishnupriya Pradeep on seismic station azimuth correction while providing daily guidance to the entire research group. Her work is supported by competitive grants including ANU Early Career Researcher Travel Grant, National Computational Infrastructure projects (as Chief Investigator), and National Natural Science Foundation of China funding. Dr. Wei also contributes to the field through AGU session convening, journal reviewing, and organizing technical workshops on Obspy/GMT. As part of international consortia involving Caltech, Cambridge, and Fleet Space Technologies, she operates at the intersection of academic research, space exploration, and nuclear treaty verification, maintaining active roles in the American Geophysical Union and ANU's Geophysics Group Seminars.

• Financial Econometrics
• Time Series Modelling
• Volatility Models
• +۶ مورد دیگر

Dr. Chao Wang is a Senior Lecturer at the University of Sydney's Sydney Business School. He holds a PhD in Econometrics from the same university, along with master's degrees in Machine Learning & Data Mining (Helsinki University of Technology) and Mechatronic Engineering (Beijing Institute of Technology). His research focuses on financial econometrics, time series modeling, and volatility analysis, particularly using Bayesian methods and high-frequency data. He teaches courses like Quantitative Business Analysis (BUSS1020) and Machine Learning for Business (QBUS6840). Dr. Wang's research interests include parametric/non-parametric volatility models, Bayesian MCMC estimation, and applications of machine learning in finance. His work addresses microstructure noise in high-frequency data and integrates realized measures like variance and range. He has supervised students on topics such as spatiotemporal volatility forecasting and financial technology-based risk management. Grants: Machine learning and high-frequency data-based risk forecasting (2022), financial tail risk forecasting with deep learning (2021), and parametric tail risk forecasting (2020). Key collaborations: With Prof. Robert Gerlach and Minh-Ngoc Tran on Bayesian frameworks and realized measures. Publications: Over 15 peer-reviewed articles in top journals like Quantitative Finance and Journal of Financial Econometrics , focusing on risk forecasting methodologies. His work bridges econometric theory and practical financial applications, emphasizing robust risk prediction under volatile market conditions.

• Cancer research
• Paediatric malignancies
• Acute lymphoblastic leukaemia
• +۶ مورد دیگر

Associate Professor Daniel Catchpoole is a distinguished researcher in paediatric oncology at the University of Sydney's Faculty of Medicine and Health, specializing in Paediatrics & Child Health. He serves as the Head of the Tumour Bank at The Children's Hospital at Westmead, a position he has held since 2001, and is a founding member of the Australian Biospecimens Network. As an Associate Professor, he lectures on Molecular Biology of Development at Sydney University and serves as President of the International Society for Biological and Environmental Repositories (2020-2021). Dr. Catchpoole holds a BAppSc in Biomedical Science and a PhD from UNSW (1995). With over 20 years of full-time laboratory research experience, his career has focused on the molecular basis of paediatric malignancies, particularly acute lymphoblastic leukaemia and neuroblastoma, as well as cancer-prone syndromes in children like Beckwith Wiedemann syndrome. His research spans multiple disciplines within cancer biology, with particular emphasis on bioinformatics, molecular biology, and translational approaches to paediatric malignancies. Dr. Catchpoole has established microarray technology within the Children's Cancer Research Unit at Westmead and has extensive experience with gene expression analysis. His work bridges cellular and molecular approaches with clinical applications, focusing on improving outcomes for children with cancer through advanced genomic and bioinformatic techniques. Analysis of his recent publications reveals a strong focus on biobanking infrastructure, cancer genomics, neuroblastoma research, and computational approaches to omics data. His work demonstrates increasing integration of machine learning techniques with traditional molecular biology approaches, particularly in the analysis of neuroblastoma and other childhood cancers. The research shows a clear trajectory toward more sophisticated genomic analysis methods and their application to clinical problems in paediatric oncology. President of International Society for Biological and Environmental Repositories (2020-2021) Founding member of Australian Biospecimens Network Active participant in Australasia's Biospecimens Network Association Dr. Catchpoole has secured multiple significant research grants including NHMRC equipment grants for the Fluidigm BioMark HD system (2012) and the Ion Torrent Personal Genome Machine (2010), as well as Cancer Institute NSW grants for high-throughput virtual microscopy systems and research on systems biology for personalized medicine of childhood leukaemia. His work with the Tumour Bank has been instrumental in supporting childhood cancer research across multiple institutions. As Head of the Tumour Bank at The Children's Hospital at Westmead, Dr. Catchpoole leads a critical infrastructure for pediatric cancer research in Australia. His work establishing microarray technology within the Children's Cancer Research Unit has created a foundation for advanced genomic analysis of pediatric malignancies. The biobanking initiatives he has developed support multiple research teams investigating childhood cancers, providing essential resources for translational research from bench to bedside.

Boris Berangerمشاهده پروفایل

مدرس ارشد

• Extreme Value Theory
• Environmental Extremes
• Spatial Statistics
• +۳ مورد دیگر

Boris Beranger is a Senior Lecturer in Statistics and Data Science at the School of Mathematics and Statistics, UNSW Sydney . He is also a member of the UNSW Data Science Hub (uDASH) and previously served as an Associate Investigator at the ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) . His research spans theoretical and applied statistics, focusing on Extreme Value Theory (environmental, financial, and insurance applications) and Symbolic Data Analysis (complex/non-standard data structures). Education: PhD in Statistics (Université Pierre and Marie Curie & UNSW, 2016), MSc in Mathematics (Université Pierre and Marie Curie, 2011) Research Trends are evident in: High-dimensional extremal dependence modeling (ExtremalDep package) Spatial extremes and max-stable processes Symbolic/histogram/interval-valued data analysis Composite likelihood and aggregated data methods Tail density estimation via kernel methods Scientific Awards & Grants include: J.B. Douglas Award for Postgraduate Excellence (2014) Multiple ARC ACEMS Research Support Schemes Discovery Project DP220103269 ($405,000) for modeling real-world extremes Supervision covers PhD, Masters, and Honours students in areas like Symbolic Data Analysis, Spatial Extremes, and Statistical Computing. He also co-organized workshops and served as Vice-President (2025-26) of the Statistical Society of Australia's NSW Branch.

• Nonlocal Differential Equations
• Fractional Calculus
• Difference Equations
• +۴ مورد دیگر

Dr. Chris Goodrich is a Senior Lecturer at the School of Mathematics and Statistics, UNSW Sydney. He holds a PhD in Mathematics from the University of Nebraska-Lincoln. His research focuses on analytical and theoretical aspects of nonlocal differential equations, fractional calculus, and variational problems, with particular emphasis on operator theory and regularity analysis. Education: PhD Mathematics, University of Nebraska-Lincoln Research Interests: Dr. Goodrich specializes in nonlocal operators and fractional calculus applied to differential/difference equations. His work investigates existence theory, monotonicity properties, and topological analysis of solutions. Key areas include convolution equations, (p,q)-growth conditions in PDEs, and applications of Sobolev inequalities to Kirchhoff-type problems. He maintains strong collaborations with international researchers in fractional analysis and discrete calculus. Publications: His recent articles (2023-2025) demonstrate consistent focus on nonlocal operators, fractional differences, and convolution equations. Predominant themes include topological methods for elliptic equations, monotonicity analysis of fractional operators, and existence/nonexistence theorems for Kirchhoff systems. Analytical techniques leverage convexity, variational principles, and asymptotic characterization across both continuous and discrete frameworks.

• Environmental Geography
• Remote Sensing
• GIS Applications in Environmental Monitoring
• +۴ مورد دیگر

Dr. Sharyn Hickey is a Senior Lecturer at the UWA School of Agriculture and Environment, affiliated with the UWA Oceans Institute and the Centre for Water and Spatial Science. Her research focuses on environmental systems, particularly coastal and marine habitats, utilizing GIS and remote sensing. She has attracted over $4 million in research funding and leads projects on habitat mapping, blue carbon, and marine conservation. She teaches GIS and remote sensing courses and coordinates units like ENVT4408 and ENVT3306. Awards include the 2024 Early-Career Research Award and 2022 Postgraduate Teaching Award. Education: PhD Research Interests: Remote sensing, GIS applications, marine ecology, coastal habitat dynamics, blue carbon assessment Key grants include the Mardie Offset Funding and projects on marine heatwaves and benthic habitat mapping. She has published extensively in journals like Remote Sensing in Ecology and Conservation and collaborates with institutions like AIMS and the Australian Institute of Marine Science. Media coverage highlights her work on mangrove discoveries and coral reef monitoring.

Flora Salimمشاهده پروفایل

استاد

• Ubiquitous computing
• Machine learning
• Data science
• +۶ مورد دیگر

Professor Flora Salim is a leading academic at the University of New South Wales (UNSW) Sydney, holding a full Professorship in the School of Computer Science and Engineering. She serves as Deputy Director (Engagement) of the UNSW AI Institute and contributes to multidisciplinary research at the intersection of ubiquitous computing, machine learning, and data science. Human-centred AI and ethical systems Spatio-temporal data modeling Applications for climate resilience and urban mobility Her research focuses on multimodal foundation models, continual learning, and responsible AI deployment in real-world environments. She explores: Time-series and sensor data analysis Wearable and environmental sensing AI for sustainable infrastructure Robustness and trustworthiness in models Recent publications highlight her work on: Transformer-based climate downscaling Cross-modal fairness in mobility Privacy-preserving spatio-temporal generation Patient similarity networks in healthcare She has received multiple competitive fellowships including: Humboldt Fellowship Bayer Fellowship Victoria Fellowship ARC Australian Postdoctoral Industry (APDI) Fellowship Additional accolades include: Women in AI Award Australia and New Zealand (2022) IBM Smarter Planet Industry Innovation Award As Chief Investigator in: ARC Centre of Excellence for Automated Decision Making and Society (ADM+S) ARC Training Centre for Whole Life Design for Carbon Neutral Infrastructure She maintains active collaborations through: Associate position at ELLIS Alicante Visiting Professor roles at University of Kassel (2019-2020) and University of Cambridge (2019) Editorial board memberships in ACM TIST, IEEE Pervasive Computing, and Nature Scientific Data

Xibin Zhangمشاهده پروفایل

استاد

• Bayesian inference
• Financial econometrics
• Nonparametric estimation and testing
• +۷ مورد دیگر

Xibin Zhang is a Professor in the Department of Econometrics and Business Statistics at Monash Business School, Monash University, Australia. He has been a faculty member since 2004, progressing from Lecturer to full Professor in 2021, and has established a strong research profile in econometrics and applied statistics. Educational Background: PhD in Econometrics, Monash University, Australia Doctoral Degree in Systems Engineering, Tianjin University, China MSc in Probability and Statistics, Nankai University, China BSc in Mathematical Statistics, Nankai University, China Research Interests: Professor Zhang’s research focuses on advanced econometric methodologies, including Bayesian inference, semiparametric and nonparametric estimation, panel data models, and hypothesis testing. His work extends into financial econometrics, actuarial studies, and energy economics, with a strong emphasis on empirical applications related to climate policy, energy transition, and economic sustainability. He applies sophisticated statistical techniques to real-world data, contributing to both methodological development and policy-relevant insights. Publication Trends: His recent publications (2019–2025) reveal a consistent focus on nonparametric and Bayesian methods in econometrics, with applications in energy economics, stochastic frontier analysis, and financial modeling. He frequently publishes in top-tier journals such as Journal of Econometrics , Energy Economics , and Economic Modelling , often in collaboration with leading researchers. A notable trend is the integration of kernel-based methods and Bayesian bandwidth selection across various modeling frameworks. Scientific Awards: Dean's Award for Excellence in Research (2009) Dean's Commendation for Excellence in Research Publication (2007) Advising and Grants: He has supervised over 15 PhD and Master’s students to completion and currently supervises multiple PhD candidates. His research is supported by competitive grants, including four Australian Research Council (ARC) Discovery Projects (2006–2016) and a DFAT-funded project (2017–2018) on Chinese tourism dispersal in regional Australia. Labs and Research Teams: While no formal lab is mentioned, Professor Zhang collaborates extensively within econometrics and business statistics research groups at Monash, particularly with colleagues like M.L. King, Jiti Gao, and Russell Smyth. He also engages in interdisciplinary work involving energy policy, finance, and actuarial science.

Tan Chee Keongمشاهده پروفایل

مدرس ارشد

• Software-defined networks
• Beyond 5G networks
• Indoor positioning systems
• +۸ مورد دیگر

Dr. Tan Chee Keong is a Senior Lecturer at the School of Information Technology, Monash University, Malaysia. He holds a PhD in Information and Communication Technology from Multimedia University (2014). His expertise lies in network system design, with a focus on software-defined networks, beyond 5G networks, indoor positioning systems, game theory, machine learning, and data science. He has secured over RM 800K in research grants as a principal or co-investigator and contributed to over 10 international journal papers. Notably, he received the Best Teaching Award from Multimedia University in 2016. Research activities include projects funded by government and industry, such as AI-Driven Energy Management for Smart Cities and IoT-based energy monitoring systems. His work addresses challenges in network efficiency, indoor positioning, and smart city technologies. Dr. Tan has collaborated on projects involving UAV swarming intelligence, reinforcement learning, and autonomous systems. Education: B.Eng (Hons) in Electronics (Telecommunication), Multimedia University, 2006 M.Eng.Sc (Information and Communication Technology), Multimedia University, 2009 Ph.D (Information and Communication Technology), Multimedia University, 2014 Research Interests: Optimizing wireless networks and protocols Indoor positioning and trajectory tracking Game theory applications in network resource management Machine learning for signal processing and localization Recent publications (2023–2025) emphasize AI-driven solutions for energy efficiency, path planning in disaster environments, and blockchain-based logistics optimization. These reflect a trend towards integrating AI/ML with traditional networking challenges. Awards: Best Teaching Award, Multimedia University (2016) Grants & Projects: AI-Enabled Energy Management (RM 800K+) IoT-Based Energy Monitoring (2022–2025) Smart City IoT Applications He plays a key role in industry-academia collaborations, particularly in Malaysia’s tech sector. His labs focus on developing practical solutions for smart city infrastructure and next-generation communication systems.

• Control engineering
• Robotics
• Machine learning
• +۶ مورد دیگر

Felix Kong is a Lecturer at the University of Technology Sydney, Faculty of Engineering and Information Technology. He specializes in control engineering, robotics, and mechatronic systems with a focus on maritime navigation and bio-inspired locomotion. Current affiliation : University of Technology Sydney (Lecturer since 2022) Previous role : Postdoctoral Research Fellow at University of Technology Sydney (2019-2022) Education : PhD from University of Sydney His research spans multiple domains: Maritime robotics : Stochastic ship routing, ocean current estimation, visibility graph optimization Dynamic locomotion : Gait analysis in parrots, bio-inspired vertical climbing robots Control theory : Iterative learning control, contraction analysis, SLAM optimality prediction Recent publications demonstrate a strong trend toward autonomous navigation systems that integrate: Stochastic weather modeling for ship routing 3D ocean flow estimation for underwater gliders Neural network-based SLAM analysis Multi-agent planning frameworks He has received funding from: Australia's Economic Accelerator Innovate Grant (2025-2027) UTS ECR Research Capabilities Initiative (2021-2022) Teaching contributions include course development and instruction for 41099 Fundamentals of Mechatronic Engineering . Peer-review activities extend to major robotics conferences and journals.

Matt Wandمشاهده پروفایل

استاد

• Statistical Methodology
• Semiparametric Regression
• Generalized Linear Mixed Models
• +۵ مورد دیگر

Professor Matt Wand is a Distinguished Professor of Statistics at the University of Technology Sydney (UTS), affiliated with the School of Mathematical and Physical Sciences and the Statistics and Data Science Group. His academic career includes appointments at Harvard University, Rice University, Texas A&M University, the University of New South Wales, and the University of Wollongong. He is a Fellow of the Australian Academy of Science, American Statistical Association, Institute of Mathematical Statistics, and Australian Mathematical Society. Research Interests: Statistical Methodology for Multivariate Data Fast Approximate Inference, Variational Bayes, and Expectation Propagation Generalized Linear Mixed Models, Semiparametric Regression, and Streaming Data Analysis Statistical Computing, R Software Development, and CRAN Contributions Awards and Honors: Moran Medal (1997) and Hannan Medal (2013) from the Australian Academy of Science UTS Chancellor’s Medal for Exceptional Research (2013) Pitman Medal (2013) from the Statistical Society of Australia Funded Research: Principal investigator on multiple Australian Research Council grants, including projects on variational approximations, semiparametric regression, and statistical computing. Key contributions include the ACEMS Centre of Excellence and R packages like glmmEP and densEstBayes . Professional Service: Leadership roles in statistical societies, editorial work, and mentorship. Active in promoting open-source statistical tools and reproducible research.

Xiaodong Gongمشاهده پروفایل

استاد

• Labour Economics
• Public Policy
• Econometrics
• +۷ مورد دیگر

Xiaodong Gong is a Professor at the Canberra School of Politics, Economics and Society at the University of Canberra. He joined UC’s NATSEM unit in 2011 and transitioned to his current role in 2019. His expertise spans labour supply analysis, tax-transfer policy, childcare economics, and household consumption, contributing to UN Sustainable Development Goals related to economic growth and social equity. Before joining UC, he held roles at the Australian Treasury, ANU, and Germany’s IZA. He is an Adjunct Professor at ANU’s Crawford School of Public Policy and a Fellow of IZA. His research focuses on policy evaluation, econometric modeling, and social welfare dynamics. Key research interests include the economic impacts of childcare policies, labour market dynamics, and fiscal policy effects. He collaborates internationally on projects such as regional rail development and workforce shortages in the ACT. Over 40 publications and 18 research projects reflect his interdisciplinary work in economics, public policy, and social sciences. Notable awards include the IZA Fellowship. He actively advises PhD students and leads projects like the Refreshable Panel for Research and Evaluation Services (RES Panel). His work bridges academia and policy, addressing real-world challenges in taxation, education, and public health.