جست‌وجوی استاد و پژوهشگر

Erniel Bayhon Barriosمشاهده پروفایل

استاد

• Computational Statistics
• Nonparametric Methods
• Data Science/Big Data Analytics
• +۵ مورد دیگر

Erniel Bayhon Barrios is a Professor at the Malaysia School of Business, Monash University. Formerly a professor at the University of the Philippines Diliman and a visiting scholar at Karlstad University (Sweden) and the Asian Development Bank Institute (Japan). He holds a PhD in Statistics (1990) from the University of the Philippines Diliman. His research focuses on computational statistics, nonparametric methods, data science, and computational econometrics, with applications in spatiotemporal modeling, time series, and financial markets. He has contributed to high-dimensional data analysis, volatility modeling, and robust statistical techniques. Key projects include the National Mental Health Survey and Well-Being (2019–2021) and building a data-driven organization for the Habib Group (2025–2026). He is an elected member of the International Statistical Institute (2012), associate editor of Communications in Statistical Applications and Methods , and served on the board of the International Association of Statistical Computing (2022–2025). He advises PhD students on topics like stochastic frontier models, data assignment in big data, and high-frequency time series analysis. His work aligns with UN Sustainable Development Goals related to education and economic growth.

Scott Sissonمشاهده پروفایل

استاد

• Computational Statistics
• Bayesian Statistics
• Big Data
• +۴ مورد دیگر

Professor Scott Sisson is Director of the UNSW Data Science Hub (uDASH) and Professor of Statistics and Data Science at the University of New South Wales, School of Mathematics and Statistics. His research focuses on computational statistics, particularly solving 'intractable' statistical problems through Bayesian methods, big data techniques, simulation algorithms, and extreme value theory with environmental applications. Education includes a PhD in Statistics from Bristol University (2002), MSc in Environmental Statistics from Lancaster University (1997), and BSc in Mathematics and Statistics from Lancaster University (1996). Research interests span: Bayesian statistics and uncertainty quantification Big data analytics and scalable algorithms Machine learning integration with statistical methods Extreme value modeling for climate/environment Computational techniques for intractable problems Recent publications (2022-2025) demonstrate strong emphasis on Bayesian computation, spatiotemporal modeling, and interdisciplinary applications in materials science, oncology, quantum computing, transportation policy, and ecology. Methodological innovations include likelihood-free inference, modular Bayesian analyses, and symbolic data modeling. Awards and honors: 2020 Service Award (Statistical Society of Australia) 2017 ARC Future Fellowship 2015 G. N. Alexander Medal (Engineers Australia) 2011 Moran Medal (Australian Academy of Science) 2010 J.G. Russell Award (Australian Academy of Science) 2010 Queen Elizabeth II Research Fellowship As Director of uDASH, he leads data science initiatives across UNSW. He maintains sustained ARC funding and supervises students in computational statistics, Bayesian methods, extreme value theory, and machine learning. Professional service includes editorial roles for Statistics and Computing and past presidency of Statistical Society of Australia.

Massimo Piccardiمشاهده پروفایل

استاد

• Natural Language Processing
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Massimo Piccardi is a Professor of Natural Language Processing (NLP), Computer Vision, and Machine Learning at the University of Technology Sydney (UTS) , where he has been since 2002. He currently serves as the Head of the School of Electrical and Data Engineering and leads the Big Data Analytics program at the Global Big Data Technologies Centre. His research focuses on advancing NLP, machine learning applications in healthcare, and cybersecurity in IoT systems. He has authored over 200 journal papers and conference proceedings, secured significant ARC and CRC grants, and holds the IEEE Computer Society Distinguished Contributor Award (2022). Education & Professional Roles: Joined UTS in 2002, progressing from Associate Professor (2002–2007) to Professor (2008–present). Serves as Associate Editor for IEEE Transactions on Big Data and Editor for Artificial Intelligence in Medicine. Active in professional societies including IEEE, ACL, and ALTA (President, 2023–2024). Research Interests: Core areas include NLP (translation, summarization, adversarial attacks), healthcare informatics (clinical NLP, health service analysis), and cybersecurity (IoT security, privacy-preserving systems). Cross-cutting themes include generative models, cross-lingual systems, and ethical AI. Grants & Projects: Principal Investigator on ARC Discovery/Linkage projects and CRC grants. Recent projects include controllable machine translation (Amazon), privacy-preserving digital agriculture, and STEM innovation (ASTRID project with NBN Co). Labs & Collaborations: Leads the UTS Global Big Data Technologies Centre, collaborating on projects like adversarial NLP attacks, medical machine translation, and secure IoT frameworks.

• Machine Learning
• Statistical Learning Theory
• Optimization
• +۳ مورد دیگر

Professor Yiming Ying is a faculty member in the Faculty of Science at the University of Sydney, where he joined in December 2023. Previously, he held tenured positions at SUNY Albany (Departments of Mathematics & Statistics and Computer Science) and was a Lecturer at the University of Exeter. He completed his PhD in Mathematics at Zhejiang University (2002) and postdoctoral training at CityU Hong Kong, UCL, and University of Bristol. Research Focus His research spans statistical learning theory, optimization algorithms, trustworthy AI, and data science mathematics. Key applications include cancer informatics for early detection. His work aligns with Faculty research strengths in Data and Decisions and Decision-Making for a Sustainable Future. Recent Research Trends Analysis of recent publications shows strong focus on theoretical foundations of machine learning: differential privacy, fairness algorithms, optimization methods for AUC maximization, generalization guarantees, and robust learning techniques for adversarial settings and biological data. Awards and Honors SUNY Chancellor’s Award for Excellence (2023) University at Albany Presidential Research Award (2022) University of Exeter Merit Award (2012) Grants and Advising Significant funding includes current ARC DP250101359 (2025-2028) and multiple past NSF grants. He founded the UALBANY Machine Learning Group and currently advises PhD student Peilin LIU on operator learning.

Jiti Gaoمشاهده پروفایل

استاد

• Econometrics
• Non- and Semi-Parametric Econometrics
• Time-Series Analysis
• +۳ مورد دیگر

Professor Jiti Gao is a Donald Cochrane Chair in Econometrics & Business Statistics at Monash University's Faculty of Business and Economics. He leads the Department of Econometrics and Business Statistics, specializing in non- and semi-parametric econometrics, time-series analysis, and panel data methodologies. His research focuses on developing statistical models for climate change, energy demand, and financial forecasting. Affiliations: Monash University, Impact Labs Grants: Multiple ARC Discovery Projects (e.g., 2020–2025 on climate-energy time series, 2017–2020 on econometric model building) Collaborations: CSIRO, Yale University, and international partners from China, Norway, and Singapore Research interests include climate econometrics, financial time series, and policy evaluation. Over 136 publications span econometric theory and applications, with recent work on nonlinear trending models and quantile regression. His grants emphasize methodological advancements in time series and panel data analysis. Awards: Not explicitly mentioned, but recognition includes Australian Professorial Fellow status and international research leadership roles. Advising/Grants: Primary Investigator on multiple ARC-funded projects, focusing on climate modeling and financial econometrics Labs/Teams: Part of Monash's Impact Labs and collaborates with global institutions on climate and econometric initiatives

Alyas Widitaمشاهده پروفایل

استادیار

• Urban Design
• Transportation Planning
• Urban Analytics
• +۱۱ مورد دیگر

Dr. Alyas Widita is an Assistant Professor in the Urban Design program at Monash University, Indonesia. He is actively involved in research and teaching, focusing on urban planning, transportation, and smart city technologies. He serves as the Program Coordinator for Urban Design and teaches courses such as Urban Design Studio: Smart City and Smart City Technologies. Education: Ph.D. in City and Regional Planning, Georgia Institute of Technology, United States Dr. Widita's research centers on the built environment, transportation systems, and urban analytics, with a strong emphasis on developing Asian cities. His work explores congestion impacts of mass transit, ride-hailing effects on vehicle ownership, rural-urban migration, walking behavior, and spatial patterns of MSMEs. He employs advanced data analytics and causal evaluation methods to inform urban policy. His recent publications span high-impact journals such as Transport Reviews , Journal of Planning Education and Research , and Travel Behaviour and Society . The research trend shows a consistent focus on data-driven urban policy, sustainable mobility, and equity in urban development across Indonesia and Southeast Asia. Scientific Awards and Recognition: No specific awards listed, but research widely cited and featured in media outlets. Dr. Widita has secured and contributed to multiple research projects funded by international and national agencies, including the World Bank, Korea Transport Institute (KOTI), Central Bank of Indonesia, and Georgia Department of Transportation. He is currently leading or co-leading projects on Jakarta’s subsidence, flood risk management using remote sensing, and the Citarum River revitalization. He collaborates extensively with researchers across disciplines and institutions. His work contributes to UN Sustainable Development Goals, particularly those related to sustainable cities and communities. He is accepting PhD students interested in the built environment, transportation, and urban analytics in developing Asia. He is involved in key labs and research teams including the Citarum Action Research Program (CARP), Intelligent and Dynamic Remote Sensing for Flood Risk, and interdisciplinary urban analytics initiatives at Monash Indonesia.

• Quantitative Modeling
• Machine Learning
• Big Data Analytics
• +۶ مورد دیگر

Associate Professor Steven Lu is a faculty member at the University of Sydney Business School, serving as Deputy Head of Discipline (Education). He holds a PhD in Marketing from the University of Toronto, an MA in Economics from York University, and a BA from Nankai University. His research focuses on quantitative modeling, machine learning, and big data analytics applied to digital economy challenges such as digital retailing, search advertising, and blockchain. He co-directs the Consumer Insights Research Group and is affiliated with the Sydney Institute of Agriculture. Dr. Lu has published in top journals including Marketing Science , Production and Operations Management , and Journal of Retailing . His awards include the CNS Vithala Rao Award, ANZMAC Best Paper Awards (2022-2024), and the 2021 Vice Chancellor's Teaching Award. He teaches courses on machine learning in marketing, marketing research, and new product development. He leads research grants such as 'The Era of Mobile Payment' (2021) and 'Digital Transformation of Food Sensory Quality' (2017). His advising focuses on topics like neural recommender systems, e-coupon effectiveness, and heterogeneous treatment effects analysis.

• Wireless Communication Systems and Technologies
• Signal Processing
• Full Duplex Communications
• +۳ مورد دیگر

Prof. Xiaojing Huang is a Professor of Information and Communications Technology at the University of Technology Sydney (UTS), serving as Head of Discipline for SEDE Communications and Electronics within the School of Electrical and Data Engineering. He leads the Mobile Sensing and Communications program at the Global Big Data Technologies Centre. With over 30 years of experience, he has authored over 300 publications and 31 patents, focusing on wireless communications, signal processing, and antenna technologies. Education: PhD (Electrical Engineering, Shanghai Jiao Tong University, 1989). Previous roles include Principal Research Scientist at CSIRO (2009-2014), Associate Professor at University of Wollongong (2004-2009), and key industry roles at Motorola and Shanghai Yang Tian Science and Technology Corporation. Research interests include full-duplex wireless systems, millimeter-wave and terahertz communications, massive antenna arrays, and mixed-signal processing platforms. His work on the CSIRO Ngara backhaul system earned multiple awards, including the 2012 CSIRO Chairman's Medal and Australian Engineering Innovation Award. Recent grants include $4.2M (AUD) for projects like 'Radio Frequency Camera for Radar Imaging' (ARC DP220101158) and 'Terabit mm-Wave Backbones for Integrated Space Networks' (ARC DP200101532). He has supervised numerous students in high-speed communication systems and full-duplex technologies. Awards include: 2013 CSIRO Leadership Achievement Award, 2012 Australian Engineering Innovation Award, and IEEE Sumner Award (nominee). Active in IEEE standards (802.11/802.15) and collaborations with institutions like Tsinghua University.

Xuan Liangمشاهده پروفایل

مدرس

• Spatial Modelling
• Panel Data
• Nonparametric Statistics
• +۳ مورد دیگر

Xuan Liang is a Lecturer in Statistics at the Research School of Finance, Actuarial Studies and Statistics (RSFAS), Australian National University. With a PhD from Peking University and postdoctoral experience at Monash University, his research focuses on spatial statistics, nonparametric modeling, and environmental data analysis. Education: PhD in Statistics (Peking University, 2017), BSc in Statistics (Zhejiang University, 2012) His work addresses methodological challenges in spatial panel data analysis, network modeling, and air pollution quantification. He has developed novel techniques for meteorological confounder adjustment in air quality assessments and contributed to distributed data analysis methods. Recent research trends include: Advancing quasi-score matching for spatial econometric models Improving subbagging algorithms for big data Creating robust distributed data aggregation frameworks Refining spatial autoregressive panel data methodologies Scientific contributions include: ANU Vice-Chancellor’s Citation for Outstanding Contribution to Student Learning (Early Career), 2022 CBE Teaching Commendation for Outstanding Teaching, 2020 Co-development of the ggmatplot R package for matrix visualization Co-inventor of Chinese patent 201811183512.0 for air quality assessment He teaches advanced courses in time series analysis, regression modeling, and mathematical statistics at ANU, while maintaining active research collaborations in econometrics and environmental statistics.

• Healthy Ageing
• Pharmacology
• Pharmacoepidemiology
• +۳ مورد دیگر

Dr. Kenji Fujita is a Research Fellow at the Kolling Institute, University of Sydney, specializing in ageing, pharmacology, and pharmaceutical care quality. He holds a PhD, MScMed (ClinEpid), and BPharm from the University of Sydney. Previously a pharmacist in Japan, he leads international initiatives in the Pharmaceutical Care Network Europe (PCNE) and the International Pharmaceutical Federation (FIP). His work focuses on deprescribing strategies, polypharmacy, and developing quality indicators for healthcare services. Dr. Fujita’s research integrates big data analysis, statistical modeling, and machine learning to address challenges in geriatric pharmacotherapy. Current projects include validating frailty indices, evaluating deprescribing interventions in older adults, and developing NLP tools for clinical documentation analysis. He has also contributed to assessing organizational readiness for guideline implementation in community pharmacies. Awards include the 2023 Outstanding Poster Presentation Award at the IAGG Asia/Oceania Congress and 2022 Best Poster at the Japanese Society of Social Pharmacy. He has secured grants such as the 2024 electronic frailty index project and the 2021 systems-approach to medication review initiative. Dr. Fujita collaborates with global networks like J-HOP (Japan Home Visiting Pharmacy Association) and leads multidisciplinary teams across Australia and Europe. His lab focuses on translating data-driven insights into actionable clinical practices to improve medication safety and quality in ageing populations.

Vipul Jainمشاهده پروفایل

دانشیار

• Supply Chain Management
• Sustainability and Circular Economy
• Innovation and ICT
• +۵ مورد دیگر

About Vipul Jain: Associate Professor Vipul Jain leads Supply Chain and Logistics Management at RMIT University’s School of Accounting, Information and Supply Chain Management. With over 20 years of academic experience, he has held senior roles at institutions like Victoria University of Wellington (NZ) and IIT Delhi (India), contributing to curriculum development, research strategy, and academic-industry collaboration. His international collaborations span over 20 global institutions, emphasizing interdisciplinary research in supply chain resilience, sustainability, and Industry 4.0. Education & Academic Leadership: Previously served as Programme Director for Master of Technology (Industrial Engineering) at IIT Delhi, leading the establishment of the Modelling and Analysis of Supply Chain (MASC) Lab. Holds editorial roles for journals like International Journal of Intelligent Enterprise and Computers & Industrial Engineering . Research Focus: Specializes in supply chain design, sustainability, circular economy, and business analytics. His work integrates ICT and big data to address complex supply chain challenges, with notable contributions to vaccine distribution, blockchain adoption, and post-pandemic resilience. Over 145 peer-reviewed publications, including high-impact journals like OMEGA and International Journal of Production Economics , reflect his prolific output. Industry Impact: Conducted management training for organizations like JCB and IBM. Served as an expert assessor for New Zealand’s Ministry of Business and Industry and advised the Indian Railways. His research has been funded by the Department of Science and Technology (India) and EU initiatives like FP6 I*PROMS. Awards & Recognition: Ranked #7 in India’s top logistics academics (2018), recipient of Literati Awards (2024, 2020), and multiple editorial leadership roles. Active in global conferences, including co-chairing ANZAM 2023. Labs & Collaborations: Founded MASC Lab at IIT Delhi. Collaborates with Coventry University, Monash University, Hong Kong Polytechnic, and institutions in Switzerland, Spain, Canada, and the U.S. Focus areas include sustainable supply chains, digital transformation, and crisis resilience.

• Dental Informatics
• Teledentistry
• Oral Health Policy
• +۴ مورد دیگر

Professor Heiko Spallek is Head of School and Dean at the University of Sydney’s Sydney Dental School, leading the school’s integration with the Faculty of Medicine and Health. He also serves as Academic Lead for Digital Health and Health Service Informatics at the faculty level. His research focuses on advancing dental informatics, teledentistry, and evidence-based practice, while advocating for improved oral health policy and public health initiatives. He holds roles including director at Community Connections Australia and membership in the Charles Perkins Centre. Education: DMD, Dr. med. dent., MSBA(CIS), FACD, FAIDH Leadership: Oversees Sydney Dental School’s academic and clinical programs, emphasizing interprofessional education and digital health innovation. Research interests include leveraging big data and machine learning in dentistry, improving access to oral healthcare through teledentistry, and addressing systemic issues in dental education and policy. He has led projects on laser dentistry applications, dental caries prevention, and healthcare workforce regulation. Notable contributions include the OpenWide conference series, the BigMouth dental data repository, and advocacy for equitable dental funding in Australia. Grants include initiatives on oral hygiene in aged care and analysis of healthcare advertising perceptions. Media engagements highlight his role in public discourse on dental access and policy, including commentary on Australia’s dental crisis and aged care reforms. He actively promotes interdisciplinary collaboration through platforms like the Dental Informatics Online Community. Labs/Teams: Directs the Sydney Dental School’s research programs in informatics and public health, collaborating with national and international networks such as the National Dental PBRN.

Ryan Koمشاهده پروفایل

استاد

• Cyber Security
• Data Provenance
• Industrial Control Systems (ICS) Security
• +۶ مورد دیگر

Professor Ryan Ko is a leading academic in Cyber Security at the University of Queensland (UQ), serving as Chair and Director of the UQ Cyber Research Centre, Director of Research at the School of Electrical Engineering and Computer Science, and a member of UQ's Academic Board. He holds a BEng (Computer Engineering) and PhD from Nanyang Technological University, Singapore. His research focuses on data provenance, industrial control systems (ICS) security, privacy-preserving technologies, and AI-driven cybersecurity solutions. Ko has pioneered initiatives such as the UQ Cyber Centre, interdisciplinary cybersecurity education programs (MCyber, PGDipCyber), and the Oceania Cybersecurity Challenge. He has attracted over AUD 20 million in competitive grants as lead investigator, including the NZ$12.2M STRATUS project. Ko’s work spans industry and policy, including advisory roles with INTERPOL, governments, and NGOs. He has authored over 100 publications, contributed to ISO standards (e.g., ISO/IEC 21878), and co-founded cybersecurity startups. Awards include Fellowships from the Australian Computer Society and Queensland Academy of Arts and Sciences, and the CSA Ron Knode Service Award. Education: Bachelor of Engineering (Computer Engineering) (Hons.), Nanyang Technological University (2005) PhD in Computer Science, Nanyang Technological University (2011) Awards: Fellow, Australian Computer Society (2016) Fellow, Queensland Academy of Arts and Sciences (2020) Young Professional Award, Singapore Government (2018) Grants & Leadership: AUD 20M+ lead investigator grants; NZ$12.2M STRATUS project (2014–2018) Established UQ Cyber Centre (2019) and NZ’s first cybersecurity graduate program (2012) His research emphasizes returning data control to users, with applications in agriculture, energy, and critical infrastructure. Ko’s contributions include patents, open-source tools (e.g., Kali Linux), and frameworks like TrustCloud for cloud accountability.

Kerry Taylorمشاهده پروفایل

دانشیار

• Ontologies
• Semantic Web
• Linked Data
• +۵ مورد دیگر

Kerry Taylor is an Associate Professor (Data Science) at the School of Computing, Australian National University (ANU). She holds visiting roles at the University of Surrey (UK) and University of Melbourne. Her career spans 20 years at CSIRO, UN big data projects with ABS, and interdisciplinary research in data management, IoT, and semantic technologies. She lectures in data mining and convenes ANU's postgraduate applied data analytics programs. Education includes a BSc (Hons 1) in Computer Science from UNSW (1983) and a PhD in Computer Science and Technology from ANU (1996). She co-chaired the W3C/OGC Spatial Data on the Web working group (2015-2017) and serves on editorial boards for Knowledge-Based Systems and International Journal of Distributed Sensor Networks . Research focuses on ontologies, semantic web, machine learning in IoT, and spatial data systems. Active projects include government information frameworks, distributed IoT facilities, and sensor data integration. Her work emphasizes interdisciplinary applications of logic-based and semantic approaches to data challenges.

• Forecasting
• Time Series Analysis
• Applied Econometrics
• +۵ مورد دیگر

George Athanasopoulos is Professor and Head of the Department of Econometrics and Business Statistics at Monash University, a position he has held since 2022. He was appointed Professor in 2019 and has established himself as an internationally recognized expert in forecasting, time series analysis, and applied econometrics. He serves as Past President (since 2024) and former Director (2014-2024) of the International Institute of Forecasters, and is Associate Editor of the International Journal of Forecasting since 2014. His research focuses on hierarchical and grouped time series forecasting, where he has pioneered methods for forecast reconciliation and cross-temporal coherence. His work has significantly influenced forecasting practices across diverse fields including national statistics offices, energy markets, and public health. He is particularly renowned for his contributions to tourism forecasting and macroeconomic modeling in big data environments. Awarded the Australian Awards for University Teaching in 2022 for outstanding contributions to student learning, Professor Athanasopoulos has also received multiple Dean's Awards from Monash Business School for research excellence, teaching innovation, and publication quality. His research output includes over 49 publications and leadership of six major research projects, including the ARC-funded 'Macroeconomic forecasting in a Big Data world' and the RACE for 2030 CRC project on clean energy forecasting. His work contributes to UN Sustainable Development Goals through applications in economic forecasting, energy modeling, and sustainable tourism development. He has supervised numerous research students and collaborated extensively with institutions including Australian National University, Griffith University, and international partners across multiple continents.