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Dr. James McDonald serves as a Lecturer and Research Fellow at the University of New South Wales (UNSW) within the School of Civil and Environmental Engineering's Water Research Centre (WRC). His work at the Vallentine Annexe (H22), Room 102, Kensington Campus focuses on advancing water treatment technologies and understanding contaminant behavior in water systems. His position bridges academic instruction with cutting-edge research in environmental engineering. McDonald's research spans multiple critical areas in water science and engineering, with particular emphasis on trace organic contaminants, membrane technologies, and advanced water treatment processes. His work investigates the fate and removal of pharmaceuticals, personal care products, and industrial chemicals in various water treatment systems. He has made significant contributions to understanding disinfection by-product formation, chiral inversion of pharmaceuticals, and the development of novel membrane technologies for improved water purification. His research combines experimental approaches with computational modeling to address complex water quality challenges. Analysis of McDonald's recent publications reveals a strong focus on emerging contaminants, particularly PFAS compounds and chiral pharmaceuticals, and their behavior in water treatment systems. His work demonstrates expertise in both conventional and advanced water treatment technologies, with increasing emphasis on sustainable approaches including green infrastructure and novel membrane processes. The interdisciplinary nature of his research connects environmental engineering, chemistry, microbiology, and materials science to address contemporary water quality challenges. McDonald actively collaborates with researchers across multiple institutions and has contributed to numerous significant studies on water quality and treatment. His work supports the development of more effective water recycling systems and safer drinking water supplies. While specific grant information isn't detailed in the available text, his extensive publication record suggests sustained research funding in water treatment technologies and contaminant fate studies. As part of UNSW's Water Research Centre, McDonald contributes to one of Australia's leading water research facilities. The WRC provides a collaborative environment for addressing complex water challenges through interdisciplinary research that integrates engineering, chemistry, and environmental science perspectives.

• Water Treatment
• Membrane Technology
• Trace Organic Contaminants
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Associate Professor Adam Irwin is an NHMRC Emerging Leadership Fellow and Associate Professor in Infectious Diseases at the University of Queensland (UQ) and Queensland Children’s Hospital. He holds positions within the UQ Centre for Clinical Research, Faculty of Health, Medicine and Behavioural Sciences. His work focuses on early sepsis recognition, antimicrobial stewardship, and pediatric infectious diseases. Dr. Irwin completed his medical degree at the University of Birmingham and his PhD in 2016 from the University of Liverpool’s Institute of Infection and Global Health. He has led initiatives like the Queensland Paediatric Sepsis Program, recognized with a Global Sepsis Alliance Award and Queensland Health Excellence Awards. His research spans sepsis pathway implementation, antimicrobial resistance trends, and rapid diagnostic tools. Notable grants include NHMRC funding for studies on multi-drug resistant infections and Children’s Hospital Foundation support for genomics and antimicrobial stewardship projects. He supervises PhD candidates in areas like bloodstream infections and molecular diagnostics. Dr. Irwin collaborates across institutions, contributing to projects such as the RAPIDS Study Group and the PAEDS surveillance network. Awards include the NHMRC Emerging Leadership Fellowship and recognition for sepsis program excellence. His work emphasizes translating research into clinical practice, improving outcomes for critically ill children through evidence-based protocols and innovative diagnostics.

• Infectious Diseases
• Pediatric Medicine
• Antimicrobial Resistance
• +3 more

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.

• Computational Statistics
• Bayesian Statistics
• Big Data
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Dr. Ehsan Abbasnejad is an Associate Professor at Monash University's Department of Data Science and Artificial Intelligence, and holds adjunct positions at the Australian Institute for Machine Learning (AIML, University of Adelaide) and the Centre for Augmented Reasoning (CAR). He specializes in foundational AI, focusing on vision-language tasks, adversarial machine learning, and reinforcement learning. His work bridges theory with real-world applications in agriculture, energy, healthcare, and sports. Education: PhD in Computer Science from Australian National University (ANU). Research Interests: Machine Learning Theory and Adversarial Defenses Neural Network Robustness and Generalization Multimodal Learning (Vision-Language) Continual and Transfer Learning Applications in Energy, Healthcare, and Robotics Awards: Finalist for Australian AI Academic/Researcher of the Year (2024) Multidisciplinary competition wins (e.g., OzMineral Explorer Challenge) Advising & Grants: Australian Research Council (ARC) Discovery Project on Reinforcement Learning CSIRO's Next Generation Graduate Fund Accepting PhD students in foundational AI and applications Labs & Teams: Director of Foundational Machine Learning & Reasoning at Monash, leading global teams in AI competitions and industry collaborations (Microsoft Research, NEC Labs America).

• Machine Learning
• Computer Vision
• Natural Language Processing
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Scientia Professor Robert Kohn is a distinguished academic at the University of New South Wales, holding a position in the School of Economics within the UNSW Business School. With a career spanning several decades, Professor Kohn has established himself as a leading expert in statistical methodology and econometric modeling. His research has significantly contributed to Bayesian statistics and computational methods for complex data analysis. Professor Kohn's research focuses on advanced statistical methodologies including Bayesian methodology, variable selection and model averaging, nonparametric regression models, time series modeling, multivariate Gaussian and non-Gaussian regression, and Markov chain Monte Carlo simulation algorithms. His work bridges theoretical statistics with practical applications across economics, finance, and cognitive science. His research demonstrates a consistent trajectory toward developing more efficient computational methods for complex statistical models, with recent work emphasizing variational Bayesian methods, particle filtering techniques, and applications to time series analysis. Analysis of his recent publications (2022-2025) reveals a strong focus on advancing computational statistical methods, particularly in Bayesian inference for complex models. His work shows increasing integration of machine learning techniques with traditional statistical methods, especially in handling high-dimensional data and complex time series structures. Professor Kohn has made significant contributions to variational inference methods, particle-based computational techniques, and applications to financial time series and cognitive modeling. Professor Kohn has maintained an exceptionally productive research career with continuous publication output since the 1970s, demonstrating remarkable longevity and adaptability in his research focus as statistical methodologies have evolved. His work shows strong international collaboration, particularly with researchers in Australia, the United States, and Europe, reflecting his standing in the global statistical community.

• Bayesian methodology
• Variable selection and model averaging
• Nonparametric regression models
• +3 more

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

• Econometrics
• Non- and Semi-Parametric Econometrics
• Time-Series Analysis
• +3 more

Quoc Thong Le Gia is an Associate Professor in the School of Mathematics & Statistics at the University of New South Wales (UNSW), Sydney. He holds a PhD in Mathematics from Texas A&M University (2003), an MS in Mathematics from Texas A&M University (2000), and a BSc in Mathematics and Computer Science from UNSW (1998). His research focuses on Numerical Analysis , Approximation Theory , Partial Differential Equations , and Stochastic Processes , with particular expertise in problems on spherical domains. His work bridges theoretical mathematics with practical applications in computational science, data science, and machine learning. Le Gia's recent publications demonstrate a strong focus on numerical methods for PDEs on spheres, stochastic analysis, and machine learning applications. His work shows consistent progression from theoretical foundations to practical implementations, with increasing interdisciplinary applications in recent years. L. F. Guseman Prize in Mathematics, Texas A&M University (2003) As a dedicated academic mentor, Le Gia has supervised numerous PhD, Master's, and Honours students across computational mathematics and data science topics. He has secured significant research funding through ARC Discovery Projects including DP220101811 (2022-2024) and DP180100506 (2018-2020). Professionally, he serves as External Associate Editor for Frontiers in Applied Mathematics and Statistics , Secretary for ANZIAM's Computational Mathematics Group, and Co-chair of Mathematics of Computation and Optimisation (AustMS Special Interest Group).

• Numerical Analysis
• Approximation Theory
• Partial Differential Equations
• +5 more

Associate Professor Bambang Trigunarsyah holds a position at RMIT University since 2018, affiliated with the School of Property, Construction and Project Management (PCPM). He earned his BSc in Civil Engineering from Colorado School of Mines, a Master's in Civil Engineering (Construction Management) from the University of Indonesia, and a PhD in Engineering Project Management from the University of Melbourne. His career spans industry roles, including project engineering in Indonesia's oil and gas sector, academic leadership at the University of Indonesia, and international teaching/research appointments at Queensland University of Technology (QUT) and King Fahd University of Petroleum and Minerals in Saudi Arabia. Research interests focus on post-disaster reconstruction, infrastructure project governance, constructability of infrastructure, and project management in developing countries. Notable projects include risk management frameworks using blockchain, circular economy in Saudi construction, and BIPV energy solutions. He actively supervises HDR students in areas like public-sector project success determinants and thermal environment studies. Bambang serves as Higher Degree Research Delegate Authority (HDR DA) for the School of PCPM and teaches postgraduate project management programs. Professional memberships include AIPM, PMI, and ASCE. His industry advisory roles include Indonesia's National Construction Service Development Board (2002-2007) and Australia-Indonesia Centre's Infrastructure Cluster (2016-2018). Recent research emphasizes BIM applications in infrastructure preservation, risk assessment methodologies, and climate-resilient construction. His work bridges theory and practice, addressing challenges in emerging economies and complex project environments.

• Project Management
• Infrastructure Project Delivery
• Post-Disaster Reconstruction
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Scientia Professor Nasser Khalili is the Head of the School of Civil and Environmental Engineering at the University of New South Wales (UNSW). He also serves as the Director of the ARC Research Hub for Resilient and Intelligent Infrastructure Systems (RIIS), President of the Australian Association for Computational Mechanics (AACM), and a core member of the International Technical Committee on Unsaturated Soil (TC106). His research focuses on geotechnical engineering, computational mechanics, porous media behavior, and sustainable infrastructure systems. Key areas of expertise include unsaturated soils, hydraulic fracturing modeling, and advanced material characterization for asphalt mixtures. Professor Khalili's work integrates computational methods with experimental analysis to address challenges in infrastructure resilience and environmental sustainability. He has pioneered studies on pore pressure dynamics, fracture mechanics in porous media, and the application of waste materials in construction. His leadership roles in national and international committees reflect his influence in advancing geotechnical and computational engineering practices. His scientific contributions include over 150 peer-reviewed articles, with recent work emphasizing machine learning applications in civil engineering and innovative solutions for sustainable asphalt mixes. Awards include Fellowship of the Academy, recognizing his significant impact on the field.

• Civil Engineering
• Geotechnical Engineering
• Unsaturated Soils
• +4 more

Professor Stuart James Khan is an Adjunct Professor in the School of Civil & Environmental Engineering at the University of New South Wales (UNSW). He previously served as Director of the Australian Graduate School of Engineering (AGSE). His research focuses on sustainable urban water management, water treatment processes, and chemical contaminant analysis. Khan holds a PhD in Environmental Engineering from UNSW (2003) and a BSc (Hons 1 in Organic Chemistry) from the University of Sydney (1995). His research interests include water recycling, desalination, disinfection byproduct formation, and the safe management of chemical contaminants. He has advised over 15 PhD students on topics ranging from advanced treatment technologies to risk assessment frameworks. Khan has published extensively, with over 200 journal articles and 18 book chapters, emphasizing interdisciplinary approaches to water quality challenges. Key contributions include advancing membrane bioreactor performance, optimizing water recycling systems, and assessing risks associated with emerging contaminants. His work bridges fundamental science and practical engineering solutions, addressing global water security challenges. Current projects explore wastewater-based epidemiology, PFAS remediation, and climate-resilient water infrastructure. Khan collaborates internationally on water reuse strategies and has contributed to policy frameworks for safe water management. His teaching spans courses like Water & Wastewater Treatment and Environmental Risk Analysis, reflecting his commitment to educating future engineers in sustainable practices.

• Water Quality
• Water Recycling
• Chemical Contaminants in Water
• +6 more

Professor Hilary Bambrick is a distinguished environmental epidemiologist and anthropologist at the Australian National University (ANU), leading the National Centre for Epidemiology and Population Health. She specializes in climate change and health, focusing on adaptation strategies, vector-borne diseases, and urban resilience. Her work bridges research, policy, and practice, with significant contributions to global health initiatives like the WHO and UNDP. Bambrick has over 180 publications and $11M in research funding, addressing climate impacts on vulnerable populations, including First Nations communities and Pacific Island nations. She serves on the Climate Council of Australia and the Australia Institute, advocating for evidence-based climate policies. Her research integrates epidemiology, anthropology, and environmental science to enhance health resilience in changing climates. Education: PhD (ANU, 2003), BA (Hons), BSc, Grad Cert Higher Ed. Key Research Focus: Climate change health impacts, adaptation strategies, vector-borne diseases, urban design, and health equity. She leads interdisciplinary projects on climate litigation, heatwaves, and infectious disease forecasting. Grants & Funding: Over $11 million in research grants, including projects on bushfire preparedness, dengue transmission modeling, and climate-sensitive disease surveillance. Labs/Teams: National Centre for Epidemiology and Population Health (ANU), collaborating with global networks like the Lancet Countdown and MJA-Lancet Countdown.

• Climate Change and Health
• Environmental Epidemiology
• Public Health Policy
• +5 more

Dr. Bo Liu is an Associate Professor in the School of Computer Science at the University of Technology Sydney (UTS), where he serves as a core member and director of the AI Security and Privacy (AISP) Research Lab at the Australian Artificial Intelligence Institute (AAII). With expertise spanning cybersecurity, privacy protection, AI and machine learning, and wireless communications, Dr. Liu has established himself as a leading researcher in the field of AI security and privacy. Dr. Liu earned his PhD from the Department of Electronic Engineering at Shanghai Jiao Tong University in 2010. His academic journey at UTS has progressed from Senior Lecturer (November 2019-December 2022) to his current position as Associate Professor (January 2023-present). Dr. Liu's research focuses on the critical intersection of artificial intelligence and security, particularly addressing emerging threats in the age of advanced AI systems. His work spans multiple dimensions of security and privacy, including deepfake detection, privacy-preserving data synthesis, AI model security, and fair machine learning. He has pioneered approaches to detect AI-generated content, protect visual privacy through de-identification techniques, and address the complex relationship between algorithmic fairness and privacy preservation. His publication record demonstrates significant contributions across multiple cutting-edge research areas, with particular emphasis on detecting and mitigating threats from generative AI systems. His recent work reveals a strong focus on deepfake detection across multiple modalities (images, video, and audio), privacy-preserving techniques for sensitive data, and the security implications of emerging AI architectures like Retrieval-Augmented Generation systems. Dr. Liu has secured substantial research funding, including as Lead Chief Investigator on multiple ARC Discovery and Linkage Projects, totaling over $3.5 million AUD. His industry collaborations include partnerships with the NSW Department of Planning and the Reserve Bank of Australia, demonstrating the practical applicability of his research. As an academic leader, Dr. Liu serves as Associate Editor for IEEE Transactions on Broadcasting and actively contributes to the academic community through conference organization, peer review for top-tier venues, and assessment for ARC grant schemes. He also teaches courses including Penetration Testing, Ethical Hacking and Offensive Security, and supervises Masters and PhD students in cybersecurity and privacy research.

• Cybersecurity and privacy
• Privacy protection
• AI and machine learning
• +4 more

Dr. Johnson Xuesong Shen is an Associate Professor at the School of Civil and Environmental Engineering , University of New South Wales . His work integrates Digital Twins , Building Information Modeling (BIM) , and Construction Automation with a focus on robotics, AI, and LiDAR/UAS technologies. Research Interests: Digital Twins, BIM, Construction Robotics, Emissions Modeling, LiDAR/UAS, Structural Health Monitoring Education: Ph.D. in Construction Engineering and Management, The Hong Kong Polytechnic University His publications span 2025–2005, emphasizing construction automation , environmental impact reduction , and innovative tunneling solutions . Recent work includes IoT-Bayes fusion for real-time safety monitoring and life cycle analysis of construction waste. Scientific Awards: Vice Chancellor's Award for Teaching Excellence, UNSW, 2014 Best PhD Student Paper Award, CONVR, UK, 2013 Postdoctoral Fellowship, University of Alberta, 2011-2013 Best Paper Award, ASCE Construction Research Congress, 2010 Dr. Shen mentors 9 PhD candidates in areas like 3D object detection , fuel consumption modeling , and UAV-based LiDAR . His grants include $5.98M from the Australian Research Council (2022–2027) for resilient infrastructure systems and projects on modular construction and intelligent tunneling .

• Digital Twins
• Building Information Modeling (BIM)
• Construction Automation
• +5 more

Professor Valentyn Panchenko is a leading academic in Economics at the UNSW Business School, specializing in advanced econometric methodologies and financial modeling. Holding a PhD from the University of Amsterdam and an MPhil from the Tinbergen Institute, his research bridges theoretical econometrics with real-world financial applications, emphasizing big data analysis, network structures, and dependence modeling in economic systems. His expertise spans financial econometrics, time series analysis, non-parametric statistics, and agent-based economic simulations. He focuses on Granger causality, model evaluation, structural economic modeling, and bounded rationality with heterogeneous agents. His work has secured significant grants including ARC Discovery Projects and DECRA fellowships, enabling cutting-edge research on market dynamics and economic interactions. Professor Panchenko's publications appear in top-tier journals like the Journal of Econometric Theory, AEJ: Micro, Journal of Economic Dynamics & Control, and Journal of Banking & Finance. His methodological contributions include novel approaches to copula-based forecasting, nonlinear causality testing, and evolutionary learning models in strategic economic environments. While specific student advising details aren't provided, his research leadership demonstrates sustained impact across econometric theory, financial markets, and experimental economics.

• Financial Econometrics
• Time Series Analysis
• Dependence Measures and Copulae
• +11 more

Dr. Edoardo Bertone is a Senior Lecturer at Griffith University's School of Engineering and Built Environment - Architecture and Design. He holds a PhD in Water Resources Engineering from Griffith University and Bachelor/Master degrees in Civil Engineering from the Polytechnic University of Turin. His research focuses on data-driven modeling, Bayesian Networks, and System Dynamics applied to water resources management, climate change adaptation, and the water-energy nexus. He is affiliated with Griffith's Cities Research Institute and Australian Rivers Institute, collaborating on projects with water utilities, governments, and private entities. Dr. Bertone has received awards such as the 2024 PVC Science Excellence in Teaching and the JSPS Fellowship (2022). He supervises doctoral and master's students in areas like water quality management and climate change impacts. Education: PhD in Engineering (Griffith University, 2015); MEng and BEng in Civil Engineering (Polytechnic University of Turin, 2009-2011). Research Interests: Water quality modeling, drinking water optimization, data-driven prediction, climate change adaptation, and sustainable development goals. He leads over 25 funded research projects, including initiatives on reservoir water quality management in Thailand, real-time nutrient monitoring, and cyanobacteria bloom modeling. Dr. Bertone’s work integrates advanced sensors, machine learning, and Bayesian networks to address environmental challenges. Awards: Listing includes PVC Excellence Awards (2024, 2017), JSPS Fellowship, and recognition as a Rising Star in Queensland Science (2015). Grants & Supervision: Principal supervisor for 10+ doctoral candidates and collaborator on projects funded by Seqwater, CSIRO, and the Ian Potter Foundation. Key grants include $745k for biofertilizer combatting eutrophication and $269k for coagulation optimization models. Dr. Bertone’s contributions extend to urban sustainability, co-editing the book *SeaCities: Urban Tactics for Sea-Level Rise* and developing frameworks for integrating SDGs into architectural education.

• Water quality monitoring and modeling
• Data-driven prediction modeling
• Bayesian Network modeling
• +5 more