جست‌وجوی استاد و پژوهشگر

Sarah Boydمشاهده پروفایل

استاد مدعو

• Systems Biology
• Computational Biology
• Cardiac Research
• +۳ مورد دیگر

Sarah Boyd is an Adjunct Senior Research Fellow at Monash University's Faculty of Medicine with Monash Health. She has maintained an active research career spanning over two decades with significant contributions across multiple domains of biomedical research. Her research interests encompass Systems Biology, Computational Biology, Cardiac Research, Protease Research, and Medical Informatics. Dr. Boyd has developed expertise in computational modeling of biological systems, particularly focusing on cardiac fibroblasts and protease specificity. Her work bridges computational approaches with experimental biology, creating tools and frameworks for understanding complex biological processes. She has made significant contributions to the development of computational tools for protease research and cardiac systems biology, with applications spanning from basic science to clinical applications. Her recent publications demonstrate a strong focus on cardiac biology, with particular emphasis on fibroblast function and identity. She has also maintained research interests in marine biology, specifically coral reef ecosystems and adaptation mechanisms. The trajectory of her work shows increasing integration of computational methods with biological systems across diverse domains. Dr. Boyd has secured research funding from multiple sources including the Australian Research Council (ARC) and personal donations. Her projects include 'Systems modelling of the cardiac fibroblast' (2013-2016), 'Computational techniques for protease research' (2007-2009), and 'Research of protease specificity' (2006). She has also served as Chair of the Communications Committee for the International Society for Systems Biology since 2016. Her research has been widely disseminated through 42 research outputs, including numerous high-impact publications in journals such as eLife, Frontiers in Immunology, Molecular Ecology, and PLoS ONE. Her work has garnered significant attention, with some publications receiving over 80 citations. Her research activities show consistent productivity from 1999 through 2022, demonstrating sustained scholarly engagement throughout her career.

Azin Jananiمشاهده پروفایل

مدرس

• Signal Processing
• Artifact Removal
• Feature Extraction
• +۴ مورد دیگر

Dr. Azin Janani is a Lecturer at the School of Electrical Engineering and Computer Science, University of Queensland. She is a member of the Electromagnetic Research Group where she conducts research on signal processing and disease classification using electromagnetic technologies for medical applications. Her educational background includes: B.S. in Biomedical Engineering from Amirkabir University (Tehran Poly-Technique), Iran (2008) M.S. in Biomedical Engineering from Amirkabir University (Tehran Poly-Technique), Iran (2010) Ph.D. from Flinders University, Australia (2019) Dr. Janani specializes in artifact removal, feature extraction, and disease classification from various biological signals including Electrocardiogram (ECG), Phonocardiogram (PCG), and Electroencephalogram (EEG). Her expertise in electromagnetic imaging has led to innovations in non-invasive diagnostic tools, particularly for liver disease detection. She is proficient in Python, Matlab, Java, and C programming languages, supporting her development of computer-aided diagnosis systems. Her recent publications demonstrate a strong focus on portable electromagnetic devices for medical diagnostics, with particular emphasis on torso imaging and liver health monitoring. These works integrate antenna design, signal processing, and biomedical applications to create novel diagnostic approaches that could transform non-invasive medical testing. Her notable recognition includes: Australian Endeavour Postgraduate Scholarship (2016) Dr. Janani is actively involved in research supervision and grant-funded projects. She currently supervises PhD research on portable electromagnetic devices for dental vitality testing. Her current funding includes an NHMRC IDEAS Grant (2025-2027) for developing a Portable Electromagnetic Torso Scanner, demonstrating her leadership in translating research into practical medical applications. As a key member of the Electromagnetic Research Group at the University of Queensland, Dr. Janani collaborates with interdisciplinary teams including Professor Amin Abbosh, Sasan Ahdi Rezaeieh, and Amin Darvazehban to advance electromagnetic sensing technologies for healthcare applications. Her work bridges electrical engineering, computer science, and medical diagnostics to create innovative solutions for challenging healthcare problems.

• Actuarial Science
• Insurance
• Statistics
• +۳ مورد دیگر

Edward Frees is a Professor at the Australian National University (ANU) within the Research School of Finance, Actuarial Studies & Statistics. He holds dual Fellowships from the Society of Actuaries (SoA) and the American Statistical Association (ASA), a rare distinction. His roles include former founding chair of the SoA's Education and Research Section, Board member of the SoA, and Trustee of the Actuarial Foundation. He has advised the U.S. Social Security Advisory Board on long-term solvency and currently serves on editorial boards of journals like the North American Actuarial Journal and Insurance: Mathematics and Economics. His research focuses on actuarial science, insurance modeling, and statistical methodologies, with contributions to loss reserving, customer churn analysis, and interdisciplinary ethical practices. Notable collaborations include work on hybrid insurance data modeling and discrimination in insurance decision-making. Awards : ASA and SoA Fellowships Editorial Roles : North American Actuarial Journal (Editor Emeritus), Insurance: Mathematics and Economics (Associate Editor) Recent work emphasizes methodological advancements in multivariate longitudinal data analysis and joint modeling frameworks applicable to insurance claims and policyholder behavior. His articles highlight cross-disciplinary approaches to address industry challenges such as customer retention and regulatory compliance.

• Machine Learning
• Time Series Analysis
• Statistics
• +۵ مورد دیگر

Dr. Pablo Montero-Manso is a Lecturer in the Discipline of Business Analytics at the University of Sydney. His research focuses on Machine Learning and Statistics for Time Series Analysis, particularly in clustering, classification, and forecasting. He has developed methodologies for automatic forecasting on large datasets and applied his work to pandemic modeling during the 2020–2021 pandemic. His open-source tools (e.g., tsfeatures , TSclust ) are widely used in academia and industry. Education : PhD from the University of A Coruña, Spain (pre-Sydney postdoc at Monash University). Research Interests : Time series forecasting, machine learning applications in energy and public health, automated ensemble models, and clustering algorithms for large datasets. His work bridges theoretical advancements with practical tools for real-world challenges. Recent articles include contributions to renewable energy scheduling, pandemic forecasting, and AI-driven decision-making in business. He leads projects like the Augmented Judgments grant exploring AI-human collaboration in product launches. Labs/Teams : Maintains active collaborations through open-source projects and academic networks in statistics and data science.

Luca Maestriniمشاهده پروفایل

مدرس

• Methodological and Computational Statistics
• Statistical Theory
• Variational Approximations
• +۴ مورد دیگر

Dr. Luca Maestrini is a Lecturer of Statistics at the Research School of Finance, Actuarial Studies & Statistics at the Australian National University (ANU), Canberra. His research focuses on methodological and computational statistics, with expertise in variational approximations, generalized linear mixed models (GLMMs), and statistical theory. He previously held postdoctoral positions at ANU (2022–2024) under Prof. Francis Hui and Prof. Alan Welsh, and at the University of Technology Sydney (2018–2022) under Prof. Matt Wand. He completed his PhD in Statistics at the University of Padova, Italy (2015–2019), studying under Prof. Nicola Sartori and co-supervisors Prof. Alessandra Salvan and Prof. Matt Wand. He also served as a Research Fellow at the Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS). His research interests span computational statistics, Bayesian inference, and applications in forensic science, ecology, and finance. Notable collaborations include work on inverse problems, multivariate abundance data analysis, and stochastic variational inference for GARCH models. He currently chairs the Australian Capital Territory branch of the Statistical Society of Australia. Key research trends in his articles include advancements in variational inference frameworks, asymptotic improvements to GLMMs, and statistical methods for postmortem interval estimation using lipid degradation biomarkers. His work bridges theoretical developments with practical applications in diverse fields. He has advised students through ANU’s research programs and contributed to ACEMS initiatives. His lab focuses on computational methods and applied statistical modeling, emphasizing interdisciplinary collaboration.

• Economic Geology
• Structural Geology
• Tectonics
• +۵ مورد دیگر

Associate Professor Ioan Sanislav is an academic at James Cook University (JCU), serving as Director of the Resources and Critical Minerals Trailblazer Projects. His research focuses on economic geology, structural geology, and tectonics with a particular emphasis on mineral deposit exploration, structural controls, and tectonic evolution. Current research interests include Proterozoic copper mineralization in northern Queensland, critical metals in NE Queensland, gold mineralization in the Archean Tanzania Craton, and REE/Nb/Ta mineralization in NE Egypt. He employs multidisciplinary approaches integrating geochemistry, field geology, and numerical modeling, collaborating closely with the mining industry on sponsored projects. Research Areas: Structural geology, metamorphic petrology, geochronology, and mineral exploration. Teaching: Lecture and coordinate Structural Geology and Tectonics (EA5211) at JCU. Projects: Lead initiatives like the North Queensland Proterozoic Metallogenesis and Critical Minerals Trailblazer Programs. Dr. Sanislav has advised numerous PhD students on topics such as ductile shear zones, sulfide mineral geochemistry, and seismic interpretations of mineral systems. He has authored over 60 peer-reviewed articles, with recent work emphasizing geochemical anomaly detection and crustal evolution studies. His collaborations with industry ensure applied relevance to resource exploration challenges.

Itismita Mohantyمشاهده پروفایل

دانشیار

• Health Economics
• Public Health
• Health Policy Evaluation
• +۵ مورد دیگر

Dr. Itismita Mohanty is an Associate Professor of Health Economics at the Health Research Institute, University of Canberra. She holds a PhD in Economics from the University of Sydney (2009) and specializes in advanced statistical modeling and health policy evaluation. Her research focuses on public health systems, health economics, and translating evidence into policy. She collaborates extensively with Geoscience Australia on earthquake cost modeling and leads interdisciplinary projects on global health equity, including studies in India, Australia, and Sub-Saharan Africa. Education: PhD in Economics, University of Sydney (2009) Research Interests: Healthcare access and equity Child mortality and nutrition Health policy evaluation Disaster risk mitigation Indigenous and marginalized populations' health Recent Projects: CANBREATHE: Climate Attribution of Wildfire Smoke Impacts (2025–2028) VARIS-PPH: Vision Assessment Referral Pathway for Rehabilitation (2024–2026) CRAMS: Cardiovascular Rehabilitation for Mild Stroke (2025–2027) Grants & Collaboration: Funded projects on veterans' mental health, brain cancer rehabilitation, and climate health impacts Consultant with Geoscience Australia (earthquake risk modeling) Collaborations with UN Sustainable Development Goals initiatives Labs/Teams: Active in multidisciplinary teams addressing health inequities and disaster resilience through data-driven approaches.

• Forecasting
• Time Series Analysis
• Computational Statistics
• +۶ مورد دیگر

Rob Hyndman is a Professor of Statistics at Monash University , Australia, in the Department of Econometrics and Business Statistics. He is an accredited statistician with the Statistical Society of Australia and a Fellow of both the Australian Academy of Science and the Academy of the Social Sciences in Australia . As former Editor-in-Chief of the International Journal of Forecasting (2005-2018), he has shaped academic discourse in his field. Research Interests : Forecasting, time series analysis, computational statistics, anomaly detection, and exploratory data analysis with applications in energy analytics, data visualization, and hierarchical forecasting Education : Bachelor of Science (Honours) and PhD from the University of Melbourne Leadership : Director of the International Institute of Forecasters (2005-2018) His scientific contributions span business analytics, machine learning, demography, and computational statistics, with recent publications focusing on responsible forecasting, hierarchical time series modeling in emergency medical services, and advanced decomposition algorithms like MSTL. His work addresses multiple UN Sustainable Development Goals through applications in public health (forecasting pandemic cases), energy (demand forecasting), and social equity (indigenous population life expectancy estimation). He has received prestigious awards including the Moran Medal (2007, Australian Academy of Science) Pitman Medal (2021, Statistical Society of Australia) Australian Awards for University Teaching (2022) Vice-Chancellor's Award for Innovation in Learning (2020) HP Innovation Research Award (2010) Vice Chancellor's Award for Postgraduate Supervision (2008) and multiple Dean's awards. Rob has supervised over 30 PhD and Masters students while developing open-source forecasting tools and organizing annual WOMBAT workshops on business analytics.

Jonathan Keithمشاهده پروفایل

دانشیار

• Bayesian Modelling
• Computational Methods
• Bioinformatics
• +۲ مورد دیگر

Jonathan Keith is an Associate Professor in the School of Mathematics at Monash University. His research focuses on Bayesian modeling, computational methods, bioinformatics, invasive species modeling, and epidemiology. He develops statistical methods for detecting functional genomic elements and applies computational approaches to biological and environmental problems. His work includes Bayesian segmentation for genome analysis, agent-based models for invasive species management, and epidemiological modeling.

Elizabeth Stojanovskiمشاهده پروفایل

مدرس ارشد

• Biostatistics
• Longitudinal Modelling
• Multivariate Statistics
• +۶ مورد دیگر

Dr. Elizabeth Stojanovski is a Senior Lecturer at the University of Newcastle , affiliated with the School of Information and Physical Sciences and the Priority Research Centre for Computer-Assisted Research Mathematics and its Applications (CARMA) . She leads the Mathematics Education Research Group and manages the statistical consulting unit, serving industry, academics, and postgraduate students. With a PhD in Statistics from the University of Newcastle, she specializes in Biostatistics , Longitudinal Modelling , and Multivariate Statistics . Education : PhD (University of Newcastle), Bachelor of Mathematics (Honours), Bachelor of Mathematics Professional Roles : Senior Lecturer (2007–present), Research Academic (2004–2006) Memberships : Member of the Australian Statistics Society Her research spans health and education , focusing on longitudinal relationships between life events and physical/mental health. She has developed Bayesian frameworks , longitudinal models , and meta-analytic techniques for applications in tobacco control, cardiovascular disease, cancer treatment, and mathematics education. Her work includes collaborations with Eric Beh on Nobel Prize data analysis, Manohar Garg on lipid-lowering studies, and Suzanne Snodgrass on physiotherapy biomechanics. Recent publications highlight her expertise in correspondence analysis for educational and scientific data, multivariate assessment of diabetes risk , and reinforcement learning for optimization. She has supervised 15 PhD/Masters students and peer-reviewed for journals and grants. Her grants total $496,207 , including projects on statistical literacy and phytosterol efficacy. Scientific Awards : 2001 "Temporal association between life events and health" Elizabeth's teaching spans theoretical and applied statistics, with a focus on psychology, health, and business applications. She has also contributed to forensic science through cut mark analysis on bone and policy research on tobacco investments in pension funds. Her leadership in CARMA and statistical consulting underscores her interdisciplinary impact.

Daniel Schmidtمشاهده پروفایل

مدرس ارشد

• Bayesian Inference
• Information Theory
• Statistical Genomics
• +۷ مورد دیگر

Daniel Schmidt is a Senior Lecturer in Data Science at Monash University's Faculty of Information Technology, specializing in Bayesian inference, information theory, and statistical genomics. He holds a PhD in Computer Science (2008) and a Bachelor of Digital Systems (Honours) from Monash University (2003). His research focuses on high-dimensional Bayesian regression, Minimum Message Length (MML) principles, and applying machine learning to medical risk prediction, particularly in breast cancer via mammography analysis. He leads projects on scalable time series forecasting, quantum computing applications, and epileptic seizure prediction. Teaching commitments include developing and lecturing in units like FIT2086 (Modelling for Data Analysis) and FIT3154 (Advanced Data Analysis). He collaborates with institutions like the University of Melbourne (Adjunct Senior Research Fellow) and has contributed to open-source tools like the BayesReg package and GitHub repositories for statistical methods. His work contributes to UN Sustainable Development Goals related to health and innovation. Key research projects include efficient time series classification (MONSTER repository), seizure forecasting using EEG data, and quantum computing applications. He has authored over 119 publications, with recent work addressing adversarial attacks on time series models and Bayesian shrinkage priors for regression. Notable collaborations involve international teams in cancer genomics, statistical epidemiology, and materials science. His GitHub contributions include tools for random correlation matrix generation and fast AR model estimation.

• Human Milk
• Microbiome
• Pediatrics
• +۴ مورد دیگر

Ali Sadiq Cheema is a Researcher affiliated with the UWA Medical School and the UWA Centre for Medical Research (affiliated with the Harry Perkins Institute of Medical Research) at The University of Western Australia. His primary research focuses on understanding the composition and functional roles of human milk, particularly its microbiome, oligosaccharides, and bacterial DNA, and their impacts on infant growth, oral and gut microbiota development, and pediatric health. He leads the BLOSOM Cohort study, a longitudinal investigation tracking breastfed infants’ microbiome development over the first two years of life. His work bridges maternal health, lactation physiology, and child nutrition, contributing to Sustainable Development Goals related to good health and well-being (SDG 3) and quality education (SDG 4) through interdisciplinary research. Cheema’s recent studies highlight how breastfeeding practices and milk components influence infant microbiota composition and body composition. His articles analyze bacterial DNA profiles, oligosaccharide intake effects, and the interplay between maternal factors (e.g., BMI) and infant outcomes. He collaborates internationally, with studies published in journals like Journal of Oral Microbiology and Scientific Reports . While no specific awards are listed, his research has garnered significant attention, including social media engagement and news coverage. He is involved in grant-funded projects exploring lactation biology and its translational applications. Cheema’s work is conducted within the UWA Centre for Medical Research, leveraging its infrastructure for advanced microbiome analysis and longitudinal cohort studies. Future directions include expanding BLOSOM to diverse populations and investigating microbiome-nutrient interactions for early-life health interventions.

• Water Engineering
• Environmental Engineering
• Urban Hydrology
• +۵ مورد دیگر

Dr. Prasanna Egodawatta is an Associate Professor in the School of Civil & Environmental Engineering at Queensland University of Technology (QUT). He specializes in Water/Environmental Engineering with over 15 years of industry and academic experience. His research focuses on urban hydrology, stormwater management, water quality modelling, and resilience in water systems. Education: PhD from QUT. Teaching areas include Engineering Hydraulics, Advanced Water Engineering, and Civil Engineering Thesis Projects. He has co-supervised over 15 doctoral/master’s students and contributed to teaching innovation projects funded by QUT and the Office for Learning and Teaching (OLT). Research interests span stormwater pollution, treatment technologies, water-sensitive urban design, and risk-based water management. Key projects include ARC Linkage grants on climate change adaptation of WSUD, and collaborations with Gold Coast City Council, Port of Brisbane Corporation, and industry partners like Holcim and SPEL Environmental. He has published over 75% of his work in Q1 journals (SCIMago) and secured >$600k in research funding. His work emphasizes statistical methods for environmental data analysis and multivariate techniques for pollutant source identification. Past roles include Higher Degree Research Director (2015–2017) and RDC committee member (2015–2017). He actively reviews for journals like Water Research and Environmental Modelling & Software . Notable contributions include advancing stormwater quality models, assessing health risks of PAHs, and developing methodologies for heavy metal prediction in urban catchments. His lab focuses on bridging environmental engineering with sustainable urban systems.

John Triantafilisمشاهده پروفایل

دانشیار

• Digital Soil Mapping
• Soil Science
• Environmental Science
• +۵ مورد دیگر

Associate Professor John Triantafilis is an Honorary Associate Professor at the School of Biological, Earth & Environmental Sciences, University of New South Wales (UNSW). His research focuses on digital soil mapping (DSM), integrating proximal sensing technologies like electromagnetic induction and gamma-ray spectrometry with mathematical models such as linear mixed models, wavelet analysis, and machine learning. He addresses challenges in soil and water management, natural resource interpretation, and precision agriculture. Education: BSc.Agr, The University of Sydney, Australia (1990) PhD, The University of Sydney, Australia (1996) Research Interests: Development of DSM frameworks for soil property prediction Application of geophysical and spectral data for soil characterization Optimization of agricultural practices through precision management Environmental impact assessment of soil salinity and sodicity Funding & Collaborations: Grants from Cotton Research and Development Corporation, Sugar Research Australia, and Australian Government bodies International collaborations with universities in Australia, Portugal, Spain, and Iran Industry partnerships for practical outcomes in irrigation and fertilizer efficiency Awards: Recipient of prestigious awards including the Fulbright Fellowship and OECD Travel Fellowships Recognized for contributions to cotton research and environmental stewardship Labs/Teams: Engages in interdisciplinary projects with global research groups focused on soil science, geophysics, and environmental engineering.

• Rock Mechanics
• Geostatistics
• Mining Engineering
• +۵ مورد دیگر

Associate Professor Chaoshui Xu is affiliated with the School of Chemical Engineering and the Department of Mining and Petroleum Engineering at the University of Adelaide. With over 30 years of experience in academia and industry, his research spans rock mechanics, geostatistics, mine planning, and innovative mining technologies. He is eligible to supervise Masters and PhD candidates in areas such as stochastic rock fracture modeling, geothermal systems, and mine-to-mill optimization. Research Interests: Stochastic rock fracture modeling and fluid flow in fractured rock masses Geostatistics and mineral resource evaluation Rock mechanics and fracture toughness testing In-situ recovery of minerals and underground coal gasification Rock fragmentation and dynamic rock mechanics Publications: His recent work (2023–2024) focuses on topics such as borehole rockburst mechanics, enzyme-induced soil reinforcement, and numerical modeling of fracture networks. These studies highlight advancements in understanding rock behavior under extreme conditions and optimizing mining processes. Awards: No scientific awards explicitly mentioned in the provided text. Advising & Grants: Supervises graduate students and contributes to grants focused on mine planning and geothermal systems. Active in professional associations related to rock mechanics and mining engineering. Affiliations: Located at Engineering North, North Terrace, Adelaide. Contact via chaoshui.xu@adelaide.edu.au or +61 8 3135 421.