جست‌وجوی استاد و پژوهشگر

Shabnam Kasra Kermanshahiمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Cryptography
• Information Security
• +۳ مورد دیگر

Dr. Shabnam Kasra Kermanshahi is a Senior Lecturer in cybersecurity at UNSW Canberra, affiliated with the School of Systems & Computing. She holds a Ph.D. in Security Sciences (Applied Cryptography) from Monash University. Her professional experience includes roles as a Postdoctoral Research Fellow at CSIRO's Data61, Lecturer at RMIT University's School of Computing Technologies, and her current position at UNSW. Her research focuses on cybersecurity and cryptographic systems. Educational Background: Ph.D. in Security Sciences (Applied Cryptography), Monash University Research Interests: Dr. Kermanshahi specializes in cybersecurity, cryptography, and information security. Her work addresses challenges in network security, data protection, and applied cryptographic protocols. She contributes to advancing secure systems and technologies through interdisciplinary research. Awards & Grants: No specific awards or grants listed in available texts. Advising & Labs: No student advising records or lab affiliations explicitly mentioned. Her professional roles indicate involvement in academic supervision and research teams, but details are not provided.

Zigan Wangمشاهده پروفایل

دانشیار

• Applied Microeconomics
• International Economics
• Environmental Economics
• +۶ مورد دیگر

Associate Professor Zigan Wang holds dual appointments at Tsinghua University (School of Economics and Management and Shenzhen International Graduate School) and is an Honorary Associate Professor at The University of Queensland. He specializes in interdisciplinary research bridging economics, business, and computer science. His work focuses on applied microeconomics, international and environmental economics, econometrics, and emerging technologies like computer vision and GANs. Education: Ph.D., M.Phil., and M.A. from Columbia University; B.A. from Tsinghua University. Research Interests: Systematic financial risk analysis in economic networks, financial data security, computational analysis of business and genomics data, and knowledge graph applications. His research has influenced policy-making in corporate governance, environmental regulation, and financial markets. Key Contributions: Highlighted corporate governance effects of share repurchases on innovation and capital expenditure. Explored regulatory enforcement biases favoring politically connected firms. Secured grants including Hong Kong General Research Fund (three times) and China National Science Fund for Distinguished Young Scholars. Awards: Bureau van Dijk Prize in Corporate Finance (2018, 2021) Faculty Research Postgraduate Supervision Award (2021, 2022) Advising & Grants: Supervised over 15 Ph.D./Masters students, with notable placements at Xiamen University and global institutions. His interdisciplinary teams address financial programming, cryptography, and FinTech curriculum development. Labs & Collaborations: Leads research on financial data security, genomics computational analysis, and cross-institutional projects with Harvard, Columbia, and global universities.

Nan Yeمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Statistics
• Optimization
• +۴ مورد دیگر

Dr. Nan Ye is a Senior Lecturer in Statistics and Data Science at the University of Queensland's School of Mathematics and Physics. His research focuses on machine learning, statistics, and optimization, with contributions to sequential decision making, weakly supervised learning, and probabilistic graphical models. He holds a PhD in Computer Science from the National University of Singapore (NUS) and double first-class honors in Computer Science and Applied Mathematics from NUS. Previously, he held postdoctoral positions at QUT, UC Berkeley, and NUS. Dr. Ye teaches advanced courses such as STAT3007/7007 Deep Learning, covering topics from foundational machine learning to state-of-the-art deep learning architectures and applications. His work has been published in top venues like NeurIPS, ICML, and UAI, earning awards including the IJCAI-JAIR Best Paper Prize (2022) and UAI Best Student Paper Award (2014). His research interests span theoretical and applied machine learning, including reinforcement learning, optimization algorithms, and their applications in fields like healthcare and environmental science. He actively supervises students in these areas and collaborates on interdisciplinary projects. Dr. Ye's academic profile includes extensive contributions to open-source tools and educational materials, reflecting his commitment to advancing both research and pedagogy in data science.

• Data Science
• Computer Vision
• Machine Learning
• +۹ مورد دیگر

Patrick Zhang is a Postdoctoral Research Fellow at the School of Electrical Engineering and Computer Science, The University of Queensland (UQ). His research focuses on applying advanced machine learning techniques to real-world challenges in domains such as medical imaging, environmental monitoring, and structural analysis. Key collaborators include Liangchen Liu, Kun Zhao, Arnold Wiliem, and Brian Lovell. His research interests revolve around data science , with a strong emphasis on computer vision and deep learning . Specific topics include: Wild animal detection and pose estimation Medical slide quality assessment and computational pathology Thermal-to-visible face recognition systems Multi-modal clustering for unsupervised learning Low-resolution image processing and boundary-guided translation Infrastructure corrosion assessment using neural networks Patrick Zhang has produced a steady stream of publications since 2018, demonstrating growth in applying deep learning to healthcare and engineering. His recent work (2022) addresses cell labelling challenges in medical diagnostics, while earlier contributions explored foundational GAN-based approaches and cross-modal recognition systems. The trajectory highlights both technical innovation and cross-domain application of AI. No scientific awards have been listed for Patrick Zhang in the provided information. His advising and grant details are not explicitly mentioned, though his collaborative projects suggest involvement in interdisciplinary research teams.

• Geophysics
• Applied Mathematics
• Computational Science
• +۳ مورد دیگر

Associate Professor David Ivers is affiliated with the Faculty of Science at The University of Sydney. His research focuses on geophysical fluid dynamics, numerical methods, and geomagnetism. He has contributed to studies on magnetoconvection, computational instabilities, and crustal magnetization analysis. His grants include the 2013 Space SyReNS initiative and the 2000 ARC grant for satellite magnetic data analysis. His work bridges computational mathematics and geophysics, addressing problems in Earth's core dynamics and geophysical data interpretation. David’s expertise spans applied mathematics, with a focus on developing numerical models for geophysical phenomena. His publications highlight interdisciplinary approaches to understanding complex fluid dynamics and magnetic processes.

• Statistical Bioinformatics
• Precision Medicine
• Genomics
• +۵ مورد دیگر

Andy Tran is an Education-Focused Lecturer in the School of Mathematics and Statistics at The University of Sydney, part of the Faculty of Science. He holds a PhD in statistical bioinformatics from the University of Sydney. His research interests span precision medicine, computational biology, genomics, and the development of bioinformatics tools for analyzing single-cell multi-omic data and gene regulatory networks. His work integrates systems biology approaches to address challenges in cell reprogramming, allograft dysfunction, and viral pathogenesis. Tran’s publications reflect a focus on precision medicine pathways, transcriptomic analysis, and scalable methodologies for understanding cell-cell communication in diseases like COVID-19. His educational role emphasizes innovative teaching strategies using tools like SCDNEY for data storytelling. While no awards are explicitly mentioned, his contributions to computational frameworks such as scREMOTE highlight his technical expertise. He actively supervises research projects and contributes to interdisciplinary collaborations within the Faculty of Science. His research spans from foundational studies in systems biology to applied computational models, with a commitment to advancing both academic and clinical applications of bioinformatics. Current work includes optimizing multi-platform precision medicine strategies and leveraging single-cell data to decode complex biological systems.

• Marine renewable energy
• Offshore engineering
• Wave-structure interaction
• +۵ مورد دیگر

Hugh Wolgamot is a DECRA Fellow at The University of Western Australia's School of Earth and Oceans and UWA Oceans Institute, where he has conducted research since 2014. His work focuses on wave-structure and fluid-structure interaction problems applied to offshore renewable energy and offshore engineering, with specific expertise in wave energy, floating offshore wind, and floating solar technologies. His research interests include: Marine renewable energy Offshore engineering Wave-structure interaction Ocean wave energy devices and arrays Hydrodynamics Computational Fluid Dynamics Wave energy converters Harmonics and wave group dynamics Wolgamot's research portfolio demonstrates a strong focus on practical applications of marine renewable energy systems, with significant industry collaboration. His work spans fundamental hydrodynamics to applied engineering solutions for renewable energy conversion in marine environments. The research fingerprint shows particular strength in wave energy converters (100%), harmonics (78%), wave group dynamics (74%), and hydrodynamics (64%). His notable scientific achievement is the DECRA Fellowship from the Australian Research Council, supporting his research into offshore renewable energy hydrodynamics. Wolgamot actively contributes to education through teaching OCEN 4007 Ocean Renewable Energy since 2020 and is affiliated with Marine Energy Research Australia and the Coastal and Offshore Research Lab. He has supervised 9 research students and engaged in public outreach through seminars on wave energy converters and ocean renewable energy.

Melinda Hodkiewiczمشاهده پروفایل

استاد

• Maintenance Engineering
• Asset Management
• Data Science
• +۶ مورد دیگر

Professor Melinda Hodkiewicz is a leading academic at the University of Western Australia (UWA), affiliated with the School of Engineering's Mechanical Engineering department. Her work focuses on advancing maintenance, asset management, and safety practices through data-driven approaches, particularly in Technical Language Processing (TLP) and industrial ontologies. She has held significant roles such as the BHP Fellow for Engineering for Remote Operations (2015–2022) and leadership in the $8.8M Australian Government-funded Training Centre for Transforming Maintenance through Data Science. Research interests include applying TLP to maintenance and safety texts, ontology development for industrial interoperability, and advancing standards like ISO 23726. Awards include the MESA Medal (Lifetime Achievement in Asset Management) and Fellow of the Australian Academy of Technology and Engineering (ATSE). She has contributed to international standards (ISO 55000 series) and served on boards of organizations like NOPSEMA and MRIWA. Her work aligns with UN SDG 4 (Quality Education) and SDG 9 (Industry, Innovation & Infrastructure). Key contributions include developing the Industrial Ontology Foundry's Maintenance Working Group, creating open-source tools like OpenBoltRF for wind turbine analysis, and advancing semantic quality assurance frameworks for maintenance procedures. Her research bridges technical language processing with industrial applications, enhancing safety and operational efficiency in sectors like mining, energy, and offshore engineering. Education: BA(Hons) in Metallurgy (University of Oxford, 1985), PhD in Engineering (UWA, 2014) Grants: ARC Training Centre for Transforming Maintenance (2019–2025), ARC Hub for Offshore Floating Facilities (2014–2021) Advisory Roles: Standards Australia EL-069 (Automation Systems), ISO TC184/SC4 (Industrial Data)

• Criminal Networks
• Organized Crime
• Terrorism
• +۳ مورد دیگر

David Bright is Professor of Criminology at Deakin University's School of Humanities and Social Sciences and Alfred Deakin Institute for Citizenship and Globalisation. He directs the Deakin Covert Networks Lab, specializing in social network analysis applications for studying organized crime and terrorism. His research examines criminal networks, illicit firearms markets, drug trafficking, and desistance from crime. His primary research focuses on applying network science to understand and disrupt organized criminal groups, with current ARC-funded projects analyzing outlaw motorcycle gangs and cybercrime networks. Recent work investigates illicit firearms markets globally and ransomware group organizational structures. Bright has secured substantial research funding including six consecutive ARC grants. His methodological innovations in social network analysis have advanced the study of co-offending patterns and criminal hypernetworks. Recent publications demonstrate cross-disciplinary applications of network science in criminology and security studies. He has received multiple awards including the Vice-Chancellor's Innovation in Teaching Award (2019) and Maconochie Award for best doctoral thesis (2007). Current doctoral students under his supervision investigate topics ranging from OMCG activities to Aboriginal imprisonment reduction strategies.

Diego Molla-Aliodمشاهده پروفایل

مدرس ارشد

• Natural Language Processing
• Question Answering Systems
• Medical Text Processing
• +۴ مورد دیگر

Diego Molla-Aliod is a Senior Lecturer in the School of Computing at Macquarie University, affiliated with the Data Horizons Research Centre and Frontier AI Research Centre. He holds a PhD in Linguistics from the University of Edinburgh and has held academic positions at Macquarie since 2005. His research focuses on Natural Language Processing (NLP), particularly in medical text processing, question answering systems, and applications of Large Language Models (LLMs). He leads projects like AnswerFinder, a question-answering system participating in TREC evaluations, and develops tools for clinical evidence summarization. Notable contributions include pioneering work in logical-form-based answer extraction and applying Bayesian methods to medical text analysis. Education: PhD in Linguistics (University of Edinburgh), MSc in Speech and Language Processing (Edinburgh), 5-year Computer Science degree (Universitat Politècnica de València). Research spans medical NLP, conversational agents, and social media analysis for mental health. Recent work explores causal inference in text and LLM-driven clinical evaluation. He has supervised over a dozen PhD/Master’s students and secured grants totaling AUD $5M+. Recipient of the 2023 Faculty of Science and Engineering Award for Inter-School Collaboration. Collaborations include projects at IIT Patna (India) and institutions in Zurich, Spain, and the U.S. His lab work involves agentic conversational agent design and evidence-based summarization systems.

• Labour Economics
• Health Economics
• Education Economics
• +۵ مورد دیگر

Dr. Zhang Wei is a Grant-Funded Researcher (C) at the University of Adelaide's School of Economics and Public Policy, affiliated with the Future of Employment and Skills Research Centre. He holds a PhD in economics and has held roles including Associate Lecturer at the University of Adelaide and Senior Research Fellow at Flinders University's National Institute of Labour Studies. His research focuses on labour economics, health economics, education economics, international trade, and applied game theory. Current projects include evaluations of the National Disability Insurance Scheme, impacts of ageing populations on productivity, job mismatches, and education's role in labour markets. Education: PhD in economics (thesis on multilateral vs. bilateral trade liberalisation) Research interests span policy-relevant areas such as workforce dynamics, healthcare economics, and trade agreements. He has contributed to projects funded by ARC/NHMRC, NCVER, and government departments, addressing topics like retirement policy, VET completers' job mobility, and economic security. Supervision eligibility includes co-supervision for Masters/PhD candidates.

• Stochastic Modelling
• Applied Mathematics
• Mathematical Modelling
• +۳ مورد دیگر

Professor Nigel Bean is a distinguished academic at the University of Adelaide, holding the Chair of Applied Mathematics within the School of Computer and Mathematical Sciences under the Faculty of Sciences, Engineering and Technology. His expertise lies in stochastic modelling, supported by a B.Sc. (Hons) from the University of Adelaide (1988) and a PhD from the University of Cambridge (1993). Roles: Professor, Chair of Applied Mathematics, Head of Applied Mathematics, Director of Research (2011–2017), Deputy Head of School. Leadership: Co-Chair of Mathematics/Statistics Research Sub-committee, Steering Committee for the Mathematical Sciences Decadal Plan (2012–2016), AMSI Board member (2014–2016), and Industry Advisory Committee. His research has earned awards including the JH Mitchell Medal and PAP Moran Medal. He has supervised 23 PhD and 7 MPhil students, with ongoing supervision of 8 PhD and 5 MPhil students. He is a Chief Investigator in the ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) and Deputy Director (Outreach). Professor Bean has contributed to national education initiatives, such as the ACARA Mathematics Advisory Panel, and held governance roles in schools and scientific organizations.

Georgy Sofronovمشاهده پروفایل

دانشیار

• Statistical Analysis
• Operations Research
• Change-Point Detection
• +۶ مورد دیگر

Georgy Sofronov is an Associate Professor in Statistics and Director of Research Training at Macquarie University's School of Mathematical and Physical Sciences. He holds a PhD in Probability Theory and Mathematical Statistics from Moscow State University (2002). Previously, he held academic positions at the University of Queensland and the University of Wollongong. He serves on editorial boards for Statistical Papers and Methodology and Computing in Applied Probability , and is Treasurer of the Modelling and Simulation Society of Australia and New Zealand. His research focuses on change-point detection, statistical quality control, optimal decision rules, and computational statistics. Research Interests : Change-point problem, statistical quality control Optimal decision rules, operations research Markov chain Monte Carlo methods, Cross-Entropy method Statistical modelling and data analysis Statistical Software (R-package 'breakpoint') Affiliations : Biomolecular Discovery Research Centre Centre for Risk Analytics Data Horizons Research Centre Smart Green Cities Research Centre Transforming Energy Markets Research Centre Teaching : Courses include Statistical Theory , Probability , Market Research and Forecasting , and Statistical Inference . Grants & Projects : SmartCrete CRC (2020–2027) Multiple change-point detection methods for big data (2017–present) Awards : Learning and Teaching Award (2016) Award for Excellence in HDR Supervision (2021) Collaborations : Active in Australia, New Zealand, and international networks focusing on computational statistics and risk analytics.

Khanh Luongمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Data Mining
• Multi-Aspect Data Clustering
• +۷ مورد دیگر

Dr. Khanh Luong is a Research Fellow at the School of Communication within the Faculty of Creative Industries, Education & Social Justice at Queensland University of Technology (QUT). She holds a PhD in Computer Science specializing in Data Science (2019) from QUT. Her research focuses on multi-aspect data, addressing challenges in high-dimensional, sparse datasets through innovative machine learning and data mining methods. She contributes to real-world applications in diverse domains like text, image, and bioinformatics data. Teaching roles include tutoring in Discrete Mathematics, Programming Principles, and Database Management for undergraduate/postgraduate students. She also designed the online unit 'Introduction to Programming' for the Master of IT program. Research interests span machine learning, data mining, multi-aspect data clustering, dimensionality reduction, and unsupervised learning. She works on the Applied Data Science project at QUT's Centre for Data Science, developing solutions for complex industry datasets. Publications emphasize multi-view clustering, manifold learning, and domain adaptation. Collaborations include roles in organizing the 2021 AusDM conference and reviewing for IEEE journals.

Scott Tyoمشاهده پروفایل

استاد مدعو

• Tropical Cyclone Dynamics
• Polarimetry
• Antenna Design
• +۳ مورد دیگر

Professor Scott Tyo is an Adjunct Professor in the Department of Electrical and Computer Systems Engineering at Monash University. His research focuses on tropical cyclone dynamics, polarimetry, antenna design, and high-power microwave systems. He has contributed to advancements in remote sensing, climate science, and electromagnetic engineering through innovative approaches in polarization imaging, antenna modeling, and tropical cyclone analysis using satellite data. Key research interests include developing algorithms for tropical cyclone segmentation using CNNs, optimizing antenna systems for high-frequency applications, and advancing polarimetric imaging techniques. His work bridges theoretical physics and applied engineering, with applications in climate monitoring and defense technologies. Recent projects highlight contributions to understanding the radiative effects of tropical cyclones on Earth's energy balance and improving the accuracy of polarization-based imaging systems. His publications span topics from metamaterial design to machine learning-driven remote sensing solutions. No awards or grants are explicitly listed in the provided texts, though his extensive publication record indicates sustained research impact. He collaborates on multi-disciplinary projects involving climatology, optics, and electrical engineering.