جست‌وجوی استاد و پژوهشگر

Ali Intezariمشاهده پروفایل

دانشیار

• Decision-Making
• Human-Technology Interaction
• Wisdom Theory
• +۴ مورد دیگر

Ali Intezari is an **Associate Professor of Management and Technology** at the **University of Queensland (UQ) Business School**, part of the **School of Business** within the **Faculty of Business, Economics and Law**. He serves as **Deputy Director for Teaching and Learning (MIBSE)** and holds expertise in decision-making, human-technology interaction, wisdom theory, knowledge management, cultural studies, and Middle Eastern business. His research bridges practical wisdom with contemporary challenges in AI ethics, organizational culture, and leadership. He has authored/co-authored over 30 journal articles, 11 book chapters, and two books, including *Wisdom, Analytics and Wicked Problems* (2019) and *Leadership: Regional and Global Perspectives* (2018). His work emphasizes integrating wisdom into management education and AI systems, addressing ethical and cultural dimensions of technology use. Intezari has presented at conferences like the Academy of Management, Hawaii International Conference on System Sciences, and International Leadership Association. His contributions span interdisciplinary topics such as AI bias mitigation, sustainable leadership, and indigenous conflict management strategies. He has been recognized with multiple teaching and research awards, though specific names remain unlisted. His research also explores cultural variations in AI reliance, sustainable management practices, and the role of philosophy in modern business education. He actively engages with industry through advisory roles and collaborations, advocating for ethical AI deployment and culturally informed decision-making frameworks.

• Control Engineering
• System Identification
• Bayesian Estimation
• +۵ مورد دیگر

Adrian Wills is an Associate Professor in the School of Engineering (Mechatronics) at the University of Newcastle, Australia. He leads the Mechatronics Engineering program and holds academic appointments since July 2015. His research focuses on Bayesian estimation, system identification, and control engineering, with applications in robotics and mechatronics. Wills has collaborated with institutions globally, including Linköping University, Uppsala University, and the University of British Columbia. He earned his B.E. (Elec.) and Ph.D. from the University of Newcastle in 1999 and 2003, respectively. Teaching expertise includes delivering advanced courses in estimation and optimization within the Mechatronics Engineering program. Administrative roles include program convenor for Mechatronics Engineering. Research highlights include contributions to state-space models, nonlinear system identification, and model predictive control. His work bridges theoretical advancements with practical applications in engineering systems and healthcare. Key collaborations involve Professors Lennart Ljung, Thomas Schön, and Bhushan Gopaluni, among others. His technical contributions span MATLAB toolboxes (e.g., UNIT), FPGA/ASIC implementations for control systems, and interdisciplinary projects in strain measurement using neutron diffraction.

• Energy Conversion
• Electrical Machinery
• Statistics and Probability
• +۴ مورد دیگر

Dr. Andrew Allison is a Lecturer in the School of Electrical and Mechanical Engineering at the University of Adelaide, within the Faculty of Sciences, Engineering and Technology. His primary roles include teaching and research in areas such as Energy Conversion, Electrical Machinery, and Applied Mathematics. Research Interests: 1. Energy Conversion and Electrical Power : Focuses on transformers, rotating machines, solar panels, batteries, and switching electronics. 2. Electrical Machinery Modeling : Applies variational techniques and mathematical frameworks (Euler, Lagrange, Hamilton) to analyze electromagnetic fields and energy storage. 3. Statistics and Probability : Uses stochastic processes and statistical models for parameter estimation in electrical systems. 4. Biomedical Signal Processing : Develops methods to identify signals in noisy data for clinical applications. 5. Mathematical Innovations : Applies advanced techniques like geometric algebra and complex optimization to solve engineering problems. Publications Trends: Recent work emphasizes renewable energy systems (e.g., grid optimization), tumor vascular modeling, and cybersecurity in key distribution. His articles span interdisciplinary fields such as biomedical engineering, economics, and signal processing, reflecting his broad expertise in mathematical and engineering applications. Supervision and Grants: Eligible to supervise Masters and PhD students in his research areas. Collaborates on projects requiring expertise in electrical engineering, statistics, and computational methods.

• Bayesian computations
• Posterior simulation methods
• Econometric and statistical methods
• +۷ مورد دیگر

David Gunawan is a Senior Lecturer in Statistics at the School of Mathematics and Applied Statistics, University of Wollongong. He holds a PhD from Monash University and specializes in Bayesian computational methods, bridging methodological development and real-world applications in economics, health, and environmental sciences. His research focuses on posterior simulation techniques (e.g., MCMC, SMC, ABC) and applies these to problems like economic inequality measurement, health outcomes analysis, and offshore engineering challenges. He has secured significant funding from the Australian Research Council (ARC) and other bodies, including leadership in projects on energy infrastructure digitalization and cognitive model inference. Gunawan supervises multiple PhD/Master’s students on topics ranging from wave prediction algorithms to socioeconomic inequality analysis. His work integrates machine learning with traditional statistical methods, exemplified by contributions to phase-resolved wave modeling and spatial statistics. He collaborates with the National Institute for Applied Statistics Research Australia (NIASRA) and maintains a Google Scholar profile at bit.ly/2Gi1PVy .

• Differential Geometry
• Computational Geometry
• Numerical Analysis
• +۲ مورد دیگر

Erchuan Zhang is an Adjunct Research Fellow at the School of Physics, Mathematics and Computing, The University of Western Australia. His research focuses on differential geometry, computational geometry, and numerical analysis, particularly in the areas of Riemannian manifolds, geodesics, and variational curves. Dr. Zhang's work centers on geometric modeling and optimization on non-Euclidean spaces, with significant contributions to cubic curve construction via the de Casteljau algorithm on manifolds and efficient computation of multi-objective variational curves. His research bridges theoretical differential geometry with practical computational methods for solving complex geometric problems. Recent publications (2022-2025) consistently address geometric modeling on manifolds, featuring themes like geodesic convergence analysis, boundary value problem solutions for Lagrangian systems, and cubic curve generalizations. These works appear in high-impact journals including Computer Aided Geometric Design and the SIAM Journal on Numerical Analysis , reflecting strong interdisciplinary connections between pure mathematics and computational science.

Jack Pezzeyمشاهده پروفایل

دانشیار

• Environmental Economics
• Sustainability Economics
• Climate Economics
• +۳ مورد دیگر

Jack Pezzey is an Honorary Associate Professor at the Fenner School of Environment and Society, Australian National University (ANU). He holds a BA in Mathematics from Cambridge, an MSc in Economics from the University of London, and a PhD in Economics from the University of Bristol, focusing on sustainability and environmental policies. His research spans sustainability economics, climate policy, and the comparison of carbon tax versus emissions trading systems. Pezzey has advised on climate policy, contributed to over 46 publications, and supervised numerous students. He is a founding member of the Economics and Environment Network at ANU and has received awards in the UK, USA, and Australia. Education: BA (Applied Mathematics and Theoretical Physics), University of Cambridge, 1976 MSc (Economics), University of London, 1983 PhD (Economics), University of Bristol, 1994 Research Focus: Global sustainability under environmental constraints Climate policy design (carbon pricing vs. emissions trading) Economic analysis of sustainability metrics like adjusted net savings Key Contributions: Advocated for carbon tax thresholds to improve policy efficacy Explored inequities in solar PV distribution Highlighted uncertainties in climate cost estimation Grants & Collaborations: Economics of Sustainability Hub (ANU, 2007–2011) Energy Transitions Research (ANU, 2012–2015) Labs/Teams: Fenner School's interdisciplinary teams on environmental policy and sustainability.

Shawn Laffanمشاهده پروفایل

استاد

• Spatial Data Analysis
• GIS Applications
• Biodiversity Analysis
• +۵ مورد دیگر

Professor Shawn Laffan is a distinguished academic in the School of Biological, Earth & Environmental Sciences at the University of New South Wales (UNSW). His research program focuses on spatial analysis methodologies using Geographic Information Systems (GIS) and geocomputational tools to address complex geographic problems across biophysical and social domains. With an extensive publication record spanning two decades, Professor Laffan has established himself as a leading researcher in spatial biodiversity analysis and computational geography. Professor Laffan's research interests center on spatial data analysis with particular emphasis on biodiversity assessment, spatial phylogenetics, and terrain analysis. His methodological expertise spans geocomputational approaches that have been applied to diverse problems including spatial analysis of biodiversity patterns , disease spread modeling in animal populations , genetic and taxonomic diversity mapping , environmental correlation analysis , and spatial variation in weed infestations . His work bridges theoretical spatial analysis with practical applications in conservation and environmental management. The trajectory of Professor Laffan's recent publications reveals a consistent focus on advancing spatial analytical methods while addressing pressing environmental challenges. His work demonstrates strong integration of computational approaches with ecological theory , particularly in biodiversity assessment and conservation planning. Notable themes include the application of cellular automata models for land use change simulation, development of phylogenetic diversity metrics for conservation prioritization, and innovative approaches to spatiotemporal disease modeling . His research increasingly incorporates big data approaches through virtual laboratories like EcoCommons Australia. Professor Laffan has made significant contributions to spatial ecology through his involvement in special journal issues on spatial ecology and through developing analytical tools like Biodiverse for spatial biodiversity analysis. His collaborative research spans multiple continents and involves interdisciplinary teams working at the intersection of geography, ecology, computer science, and conservation biology. His methodological innovations have advanced how researchers approach spatial problems in environmental science and biodiversity conservation.

Ho Loon Shinمشاهده پروفایل

مدرس

• Metabolic Syndrome
• Diabetes Mellitus
• Vitamin E and Its Effects
• +۳ مورد دیگر

Dr. Ho Loon Shin is a Lecturer in General Practice at the Clinical School of Johor Baru, Monash University Malaysia since 2012, working as fractional staff. He earned his MBBS from the University of Malaya in 1979 and served in government hospitals before retiring as a general practitioner in 2009. He now focuses on medical education, teaching clinical communication skills and patient-centered care in family medicine, as well as facilitating Problem-Based Learning in Surgery. Education: MBBS, University of Malaya (1979) Affiliations: Malaysian Institute of Management (MIM) certified professional trainer His research revolves around metabolic syndrome, diabetes, and vitamin E's effects, including a major project on tocotrienol-rich vitamin E's impact on diabetic microvascular complications. He has been honored with Rotary International's 'Service Above Self' award (2009) for humanitarian efforts, including establishing a non-profit hemodialysis center and disaster relief work in Chile (2009). Key collaborations include multi-center clinical trials and studies on ethnic variations in metabolic health. His work aligns with UN SDGs addressing health equity and sustainable communities.

Mark Wallaceمشاهده پروفایل

استاد

• Optimization
• Constraint Programming
• Artificial Intelligence
• +۵ مورد دیگر

Professor Mark Wallace is a renowned academic at Monash University , specializing in modelling and software platforms for planning, scheduling, and optimization problems . He has led groundbreaking projects such as the development of the ECLiPSe constraint programming platform (acquired by Cisco Systems) and the G12 hybrid optimization platform , which was commercialized through his company, Opturion . His research consistently bridges theoretical innovation with real-world applications, supported by industry funding from major companies like British Airways, Qantas, and Woodside Energy. Education: MA in Mathematics and Philosophy from Oxford University; MSc in Artificial Intelligence from Queen Mary College, London; PhD in Communicating with Databases in Natural Language from Southampton University. His work focuses on application-driven research in constraint programming, hybrid optimization systems, and decision support technologies. Recent publications highlight advancements in public transport routing , autonomous vehicle fairness constraints , and human-centred feasibility restoration . He actively collaborates with industry partners on projects involving Melbourne Water , Woodside , and the Alertness CRC , driving innovations in smart infrastructure and transport systems.

• Internet of Things
• Artificial Intelligence
• Smart Systems

Albe Chai Bing Zhe serves as an Associate Lecturer at Swinburne University of Technology's Faculty of Engineering, Computing and Science in Sarawak, having joined the institution in 2025 while completing his PhD at the same university. His academic qualifications include: Bachelor of Engineering (Hons) in Electrical and Electronic Engineering, Swinburne University of Technology, Sarawak Campus (2022) PhD in progress (examination stage), Swinburne University of Technology, Sarawak Campus Dr. Chai's research bridges Internet of Things (IoT) infrastructure with artificial intelligence to solve practical problems in agriculture and transportation. His work on smart incubators for microalgae cultivation demonstrates IoT applications in sustainable food production, while his road safety research develops machine learning models for accident prediction using non-visual data sources. This interdisciplinary approach connects engineering hardware development with data science methodologies. His 2023-2025 publications reveal a clear research trajectory: starting with foundational data mining for traffic patterns (2023), progressing to cloud-based multi-region prediction systems (2024), and culminating in integrated agricultural technology (2025). The work spans agricultural engineering, transportation safety, and embedded systems, consistently applying AI to real-world sensor data. Professional recognition includes: Graduate Engineer, Board of Engineers Malaysia (BEM) Member, Institute of Electrical and Electronics Engineers (IEEE) Dr. Chai actively seeks Master's and PhD candidates for his research areas, with supervision focusing on hands-on IoT system development and AI implementation. His examination-stage PhD status indicates he brings recent technical expertise to student projects, while his industry-aligned research suggests strong practical training opportunities. Current publications indicate active research momentum despite being an early-career academic. Though no formal lab name is specified, his research group develops physical IoT prototypes (like smart incubators) alongside data analytics pipelines, creating an environment where students gain experience from circuit design to cloud deployment.