جستجوی استاد راهنمای دانشگاهی

Raj Mehrotraمشاهده پروفایل

پژوهشگر ارشد

• Hydrology
• Climate Change Impact Assessment
• Statistical Modeling
• +۳ مورد دیگر

Dr Raj Mehrotra is a Senior Research Fellow at the Water Research Centre, School of Civil and Environmental Engineering, University of New South Wales. He holds a PhD from UNSW, M.E. from Indian Institute of Technology Roorkee, and B.E. from Jiwaji University. His work focuses on statistical applications in hydrology and hydroclimatology, particularly on multivariate bias correction and stochastic downscaling of climate model simulations. Education: PhD: University of New South Wales M.E.: Indian Institute of Technology, Roorkee B.E.: Jiwaji University, Gwalior Raj develops innovative methodologies for climate data processing, including the Multivariate Bias Correction (MBC) and Multisite Rainfall Downscaling (MRD) software. His research addresses climate change impacts on water resources, reservoir management, and flood/drought risk assessment, with applications in Australia, India, and Thailand. Recent publications reveal a focus on climate projections, bias correction frameworks, and hydrological modeling. Key topics include CMIP5 decadal predictions, stochastic rainfall generation, and uncertainty quantification in climate simulations. His work has been supported by ARC Linkage projects, WaterNSW, Bureau of Meteorology, and international collaborations like the Australia-India Strategic Research Fund. He contributes to climate-hydrology software development and has advised on projects related to water infrastructure, agricultural productivity, and groundwater sustainability. Current projects include multivariate bias correction of regional climate simulations, development of the MINBC package, and ensemble modeling for ungauged catchments.

Badal Pokharelمشاهده پروفایل

پژوهشگر ارشد

• Geospatial Engineering
• Disaster Risk Reduction and Management
• Climate Change
• +۴ مورد دیگر

Dr. Badal Pokharel is a Research Associate at the Research Centre for Integrated Transport Innovation (rCITI) within the School of Civil and Environmental Engineering at the University of New South Wales (UNSW), Faculty of Engineering. She holds a PhD in Civil and Environmental Engineering from UNSW (2023) and an M.Sc. in Engineering Geology from Tri-Chandra Multiple Campus, Tribhuvan University, Nepal (2018), where she was the university topper. Her research focuses on the assessment of natural and human-induced disasters, particularly earthquake-triggered landslides and climate change-induced floods, using advanced geospatial approaches. Dr. Pokharel has extensive expertise in Geographic Information Systems (GIS), remote sensing (RS), and implementing geospatial systems for geohazards, agriculture, climate change, land administration, and geomorphology projects. Her methodological expertise integrates machine learning techniques with traditional geospatial methods, showing particular focus on the Himalayan region, especially Nepal. Dr. Pokharel's publications demonstrate strong expertise in landslide susceptibility mapping, earthquake-triggered landslides, and geospatial analysis of natural disasters. Her recent work includes innovative approaches using random forest methods, Persistent Scatterer Interferometry, and slope-unit-based assessments for disaster risk management, with a geographical focus on Central Nepal and the Himalayan region. Early Career Academic Social Impact Award 2023, UNSW Early Career Network (ECAN), Sydney Australia Best Talent Award, 2021 Young Generation Forum/Young Professional Forum hosted by the Korean Academy of Scientists and Engineers in Australasia University topper for Master of Science in Engineering Geology, Tri-Chandra Multiple Campus, 2018 Dr. Pokharel has secured multiple research grants including UNSW Seed funding (AUD 25000), Global Partnership Project Grant from Virginia Tech University (AUD 7200), HPC-Europa3 Transnational Access Programme research grant (AUD 3630), and PhD Research Support Grant from UNSW (AUD 3000). She is passionate about interdisciplinary and transdisciplinary research that contributes towards disaster risk reduction and management, bridging engineering, geoscience, and data science to develop practical solutions for natural disaster prediction and management.

• Urban Design
• Architecture
• Urban Geography
• +۷ مورد دیگر

Stephen Cairns is a Professor in Urban Design at Monash University, based in Indonesia, with a strong interdisciplinary focus bridging architecture, geography, and urban studies. He is actively involved in research projects related to urban sustainability, public space, and smart cities, often in collaboration with regional and international partners. His research interests include urban design, architectural theory, public space in high-density Asian cities, material culture of buildings, and the socio-spatial implications of urban development. He explores themes such as urban decay, temporality, and the lived experience of built environments, particularly in Southeast Asia. The recent publications and projects reflect a consistent engagement with interdisciplinary methodologies, especially at the intersection of geography and architecture. His work emphasizes empirical, practice-based research and contributes to broader discourse on sustainable and equitable urban futures. Scientific Awards: No awards mentioned in the provided text. Stephen Cairns has served as a Chief Investigator on multiple research projects, including the Citarum Action Research Program and a project on privacy-preserving machine learning for smart city policy. These indicate active grant involvement and leadership in collaborative, policy-relevant research. While no students are listed, his role as a professor suggests advisory responsibilities. He is associated with Monash University’s initiatives in Indonesia, contributing to research on intermediary cities and urban well-being in Asia. His work is integrated into broader networks focused on sustainable urban development and smart city innovation.

• Landscape Ecology
• Conservation Biology
• Sustainable Agriculture
• +۶ مورد دیگر

Dr. Jim Radford is an Associate Professor at La Trobe University , where he leads the Landscape Ecology Lab and co-directs the Research Centre for Future Landscapes . His work focuses on natural capital accounting , conservation biology , and sustainable agriculture , addressing global challenges in sustaining ecosystems under climate change. Current Research: Farm-scale natural capital metrics, fire regime impacts on biodiversity, AI-driven ecological monitoring, and bird community condition indicators. Funded Projects: Includes National Landcare Program grants , Bushfire and Natural Hazards CRC projects , and Australian Department of Climate Change initiatives . Teaching: Coordinates Water Management (AGR3WMT) and teaches Landscape Ecology and Conservation (ENV3LEC) and Issues in Conservation (WBC2IC) . Scientific Awards: Fellow of Birdlife Australia (2024) for ornithological contributions.

Binghao Liمشاهده پروفایل

دانشیار

• Indoor Positioning
• Pedestrian Navigation
• Satellite Positioning
• +۳ مورد دیگر

Associate Professor Binghao Li leads the MIoT & IPIN Lab at the School of Minerals and Energy Resources Engineering, University of New South Wales, Sydney. He holds a PhD in Spatial Information Systems from UNSW and advanced degrees in Civil and Electrical/Mechanical Engineering from Tsinghua University and Beijing Jiaotong University. Expertise in indoor/outdoor positioning systems Pioneering mine IoT applications Leader in pedestrian navigation research His research spans indoor positioning technologies, satellite navigation, and mining IoT solutions. Key grant projects include: 2021 CRC-P grant ($2m) for underground mine LoRa networks 2020 ARC Research Hub ($5m) for connected sensors 2018 Digital Grid Seed Funding for indoor navigation 2015-2019 ARC Linkage grants for positioning systems Award highlights: 2019 Best Paper & Presentation Awards 2010 VC's Post-Doctoral Fellowship 2004-2005 student research awards He supervises research in indoor positioning and mine IoT, and teaches courses including ENGG1000 Engineering Design and MINE8710 Mine Slope Stability.

Raina MacIntyreمشاهده پروفایل

استاد

• Emerging infectious diseases
• Biosecurity
• Epidemiology
• +۸ مورد دیگر

Professor Raina MacIntyre is NHMRC Leadership 3 Fellow and Professor of Global Biosecurity at the University of New South Wales, Faculty of Medicine & Health. She heads the Biosecurity Program at the Kirby Institute, conducting research in epidemiology, bioinformatics, health intelligence, vaccinology, bioterrorism prevention, mathematical modelling, and public health. As of 2024, she is ranked #1 globally on Respiratory Protective Devices and highly ranked in Smallpox research according to Expertscape, with an H-index of 81/64 and over 30,000 citations. Her educational background includes: MBBS (1st Class Honours), University of Sydney, 1988 Master of Applied Epidemiology, Australian National University, 1992 PhD (Epidemiology), Australian National University, 1998 Fellow, Royal Australasian College of Physicians (FRACP), 1994 Fellow, Australian Faculty of Public Health Medicine (FAFPHM), 1995 Professor MacIntyre's research spans four key areas: Personal protective equipment, Vaccinology, Epidemic response and emerging infectious diseases, and bioterrorism prevention. Her innovation, EPIWATCH®, is an advanced AI system for real-time global health intelligence that uses NLP, prioritization algorithms, and LLMs to scan open-source data for early epidemic signals. She has a 31-year track record in pandemics and respiratory virus control, with particular expertise in mask research, having published the largest body of clinical trials on face masks for healthcare workers internationally. Her research publications demonstrate strong focus on emerging infectious disease modeling, vaccine effectiveness, and biosecurity threats. Recent work emphasizes AI-driven health intelligence systems, airborne transmission mitigation, and preparation for re-emergent pathogens like smallpox. Her articles consistently address practical applications of epidemiological research to inform public health policy and emergency response. Professor MacIntyre has received numerous prestigious awards including the Eureka Prize for Leadership and Innovation in Science (2022), the Frank Fenner Award for Research in Infectious Diseases (2003), and the Sir Henry Wellcome Medal and Prize (2007). Her work has been globally recognized, with a quote from her mask research featured on the cover of Lancet in 2020. She currently supervises PhD, ILP, and Masters students in infectious diseases epidemiology and biosecurity. Her research is supported by significant grants including an NHMRC Investigator grant (2023-2027), an MRFF grant for aerosol transmission of SARS-CoV-2, and a $5.39 million gift from Vitalik Buterin's Balvi Philanthropic Fund for EPIWATCH expansion in low and middle-income countries. Professor MacIntyre leads a multidisciplinary team at the Kirby Institute including analysts, epidemiologists, AI specialists, and software engineers developing EPIWATCH® into a global hub for epidemic detection and mitigation. She also co-founded the ARM network for Australian outbreak response and serves on multiple WHO committees including the Technical Advisory Group on COVID-19 Vaccine Composition and the SAGE Ad Hoc Working Group on Smallpox and Monkeypox.

• Forensic Science
• Drug Intelligence
• Illicit Drug Markets
• +۶ مورد دیگر

Associate Professor Marie Mc Nerney is a faculty member at the University of Technology Sydney (UTS) in the School of Mathematical and Physical Sciences, where she serves as Associate Professor and Course Director for the Bachelor of Forensic Science program. She is affiliated with the Centre for Forensic Science (CFS) at UTS and has established herself as a leading researcher in forensic intelligence and drug market analysis. Dr. Mc Nerney completed her Bachelor and Master's degrees in Forensic Science at the University of Lausanne (Switzerland) in 2009. After working as a forensic scientist with the Wallis State Police in Switzerland, she moved to Australia to complete a project on gunshot residues at the UTS Centre for Forensic Science in collaboration with the Australian Federal Police. She earned her PhD on drug intelligence at UTS in 2015, which was a collaboration between the Australian Federal Police, the University of Lausanne, and UTS. In 2016, she was awarded a prestigious Chancellor's Postdoctoral Research Fellowship from UTS. Her research focuses on the use of illicit drug data from multiple sources for intelligence purposes, with particular expertise in analyzing drug markets through the triangulation of data from cryptomarkets, drug seizures, wastewater analysis, and governmental sources. She has extended this approach to other organized systems such as organized crime and security. Dr. Mc Nerney has made significant contributions to forensic intelligence methodology, particularly in document examination and the application of forensic science for proactive crime prevention. Her extensive publication record demonstrates a consistent focus on applying forensic science to intelligence gathering, with recent work examining drug trends among people who inject drugs, dark web market analysis for fraudulent documents, portable technology for drug identification, and the utility of trace evidence for intelligence purposes. Her research shows a clear trajectory toward developing systematic methods for transforming forensic data into actionable intelligence for law enforcement and public health agencies. 2024 UTS Medal for Excellence in Research and Teaching Integration Citations for outstanding contributions to student learning (2024) UTS Teaching and Learning Award - Team Teaching (2022) Dr. Mc Nerney has secured significant research funding, including the 'Residue and Post Overdose Substance Testing (RePOST)' grant (2024-2025), 'Understanding emerging opioid-related harms through improved surveillance, drug checking and information sharing systems' (2020-2021), and 'The use of forensic case data in an intelligence perspective' (2015-2019). She serves as Associate Editor for Forensic Science International and edited the 23rd Meeting collection for the International Association of Forensic Sciences (IAFS). As Course Director for the Bachelor of Forensic Science program, she has developed and taught courses including 'Foundations of Forensic Science,' 'Forensic Intelligence,' and 'Introduction to Forensic Science.' Her work with the Centre for Forensic Science has positioned her at the intersection of academic research and practical forensic applications, collaborating with multiple agencies including the Australian Federal Police. She has been instrumental in developing the forensic intelligence approach that shifts forensic science from a purely reactive service to a proactive contributor to crime prevention and disruption.

• Artificial Intelligence
• Brain-Computer Interfaces
• Fuzzy Neural Networks
• +۸ مورد دیگر

Distinguished Professor Chin-Teng Lin is a leading academic at the University of Technology Sydney (UTS) , where he serves as Co-Director of the Australian AI Institute (AAII) and Director of the Computational Intelligence and Brain Computer Interface Lab . With a career spanning decades, he has pioneered advancements in artificial intelligence (AI) and brain-computer interfaces (BCI) , focusing on human-machine collaboration, wearable EEG systems, and neuroergonomics. School of Computer Science, UTS Co-Director, Australian AI Institute Director, Computational Intelligence and BCI Lab Lin’s research interests are deeply rooted in machine-intelligent systems , cognitive neuroscience , and human-centric AI . He has developed groundbreaking technologies like fuzzy neural networks (FNNs) in 1992, which revolutionized AI by integrating human-like reasoning. His work extends to multi-agent reinforcement learning for cybersecurity, wearable EEG devices for real-world applications, and neurofeedback interventions for chronic pain management. His research outputs include over 950 peer-reviewed publications , with a focus on deep learning , transformer models , and clustering algorithms . Articles like the MGRW-Transformer (2025) and Autonomous Clustering (2025) highlight his leadership in interpretable AI and parameter-free methods. Scientific awards and recognitions include: IEEE Fellow (2005) IFSA Fellow (2012) IEEE Fuzzy Systems Pioneer Award (2017) Outstanding Achievement Award, Asia Pacific Neural Network Assembly Lin has supervised 72 PhD candidates , 30 postdoctoral fellows , and 237 research Masters students since 1992, mentoring notable alumni such as Dr. Zehong Cao (ARC DECRA Fellow) and Prof. Chia-Feng Juang (IEEE Fellow). His funding portfolio includes $10M+ from the US Army Research Lab , $3.8M from the Australian Defence Innovation Hub , and $30.2M in industry collaborations .

• Computer Vision
• Machine Learning
• Human Attention Modeling
• +۲ مورد دیگر

Minh Hoai Nguyen is a Professor at the School of Computer and Mathematical Sciences and the Australian Institute for Machine Learning (AIML) at the University of Adelaide. Previously, he was a tenured Associate Professor at Stony Brook University (2014-2024) and worked at VinAI Research in Vietnam. He holds a Bachelor of Software Engineering from the University of New South Wales (2006) and a PhD in Robotics from Carnegie Mellon University (2012). His research focuses on computer vision and machine learning, with specialization in human attention modeling, gaze prediction, action recognition, and object counting. Recent work explores applications in educational technology, driver monitoring, and multimodal interaction systems using advanced deep learning approaches. Publication analysis reveals strong emphasis on attention mechanisms across domains, with recent works exploring: (1) Gaze and scanpath prediction using transformer architectures, (2) Few-shot learning for action counting and personalized modeling, (3) Multimodal analysis of cognitive states, and (4) Efficient scene-adaptive vision systems. His research consistently bridges theoretical machine learning with practical applications in human behavior analysis. Scientific Awards: Best Student Paper Award at IEEE CVPR (2012)

• Biomechanics
• Orthopaedic Research
• Computational Methods
• +۲ مورد دیگر

Professor Dominic Thewlis is a faculty member at the University of Adelaide within the Faculty of Health and Medical Sciences , specifically in the Surgical Specialities department. He leads the Centre for Orthopaedic & Trauma Research , which integrates molecular biology, biomechanics, and clinical research focused on the human musculoskeletal system. His research expertise lies in biomechanics of orthopaedic disease and injury , utilizing biomechanical modeling , medical imaging , wearable sensors , and patient-reported outcome measures . Research projects available for students include statistical shape modeling of joints , muscle activation mapping , and gait analysis using deep learning . Recent publications highlight his work on hip and knee arthroplasty , fatigue monitoring in athletes , and LiDAR-based musculoskeletal modeling . His research spans finite element analysis, gait coordination, and clinical decision-making frameworks. Awards and honors include the NHMRC R.D. Wright Fellowship (2017-2021) and the current ARC Future Fellowship (2024-2028) . He has served as Past President of ANZORS and contributes to editorial boards of leading journals in orthopaedics and biomechanics. Professor Thewlis supervises Masters and PhD students and collaborates with industry partners and Defence for applied research funding. Facilities include the Adelaide Health and Medical Sciences building and Royal Adelaide Hospital outpatient departments .

• Data Mining
• Machine Learning
• Computer Vision
• +۵ مورد دیگر

Dr. Bin Liang is a Senior Lecturer at the University of Technology Sydney (UTS), working within the Faculty of Engineering and Information Technology and the Data Science Institute. He joined UTS in December 2018 as a Lecturer and was promoted to Senior Lecturer in July 2022, following his postdoctoral fellowship at Data61 (CSIRO). PhD in Computer Vision, Pattern Recognition, and Machine Learning from Charles Sturt University, Australia (2012-2015) Masters in Computer Science from Taiyuan University of Technology, China (2009-2012) BEng in Computer Science from Taiyuan University of Technology, China (2005-2009) Dr. Liang's research spans data mining, machine learning, computer vision, pattern recognition, and survival analysis, with a strong focus on practical applications in critical infrastructure. His work develops sophisticated machine learning frameworks for anomaly detection, failure prediction, and optimization in water infrastructure, flood mapping, and real estate appraisal. He has pioneered approaches that integrate graph neural networks with temporal analysis for pipe failure prediction and has made significant contributions to water quality optimization through data-driven methods. His research consistently bridges theoretical advancements with practical implementation in industry settings. His recent publications demonstrate a clear trajectory toward increasingly sophisticated models that capture complex temporal and spatial relationships in infrastructure data. There's a notable emphasis on multimodal learning approaches and domain generalization techniques that enhance model robustness across diverse application scenarios. His work on anomaly detection frameworks like MLAD shows innovation in grouping sensors by temporal characteristics for more accurate monitoring. 2022 – AWA R&D Excellence Award (NSW) 2022 – UTS Medal for Research Impact 2022 – Finalist for 2021-22 AWA Young Water Professional of the Year Award (NSW) 2020 – Finalist for the Best Paper Award of the ICARCV 2020 2019 – Industrial & Primary Industries Merit at the Victorian iAwards 2018 – Australian Museum Eureka Prize for Excellence in Data Science Dr. Liang actively supervises Masters Research and PhD students, focusing on data science applications for infrastructure management. His research has been supported through industry partnerships with water utilities and other infrastructure organizations, translating academic research into practical solutions that reduce water loss, improve infrastructure reliability, and enhance environmental sustainability. His work on pipe failure prediction and leak detection has directly contributed to operational improvements in water distribution networks. As a core member of the Data Science Institute at UTS, Dr. Liang collaborates with interdisciplinary teams working on data-driven solutions for urban infrastructure challenges. His research group focuses on developing scalable machine learning models that can be deployed in real-world settings, often working directly with industry partners to validate and implement their approaches. This industry-academia collaboration ensures that his research remains grounded in practical challenges while pushing the boundaries of data science methodology.

• Transport Engineering
• Traffic modelling
• Microscopic simulation
• +۷ مورد دیگر

Dr. Tuo Mao serves as a Research Fellow at the Data Science Institute within the Faculty of Engineering and Information Technology at University of Technology Sydney (UTS). He also holds visiting scientist status at the Intelligent Mobility group at Data61 CSIRO. With a PhD from University of New South Wales (UNSW), Dr. Mao has established himself as a senior engineer specializing in transportation systems research. Dr. Mao's research interests span Transport Engineering with particular expertise in traffic modelling, microscopic simulation, and traffic signal control and management. His work focuses on vehicle infrastructure integration (VII) systems within intelligent transport systems (ITS), with specific applications in motorway modelling, coordinated ramp metering optimization, and V2I communication wireless connection system modelling. He has developed significant expertise in applying genetic algorithms to traffic signal control plan optimization and specializes in machine learning applications, particularly reinforcement learning, for transportation challenges. His recent publications (2023-2025) demonstrate a clear progression toward AI-driven transportation solutions, with emphasis on digital twins for passenger flow prediction, connected vehicle data analysis for railway safety, and micro-mobility pattern analysis. These works reveal consistent application of machine learning techniques to both recurrent and non-recurrent traffic conditions, with practical implementations across Australian transportation networks. EV Charging as a Service (2024-2026) - Australian Renewable Energy Agency UTS Smart Campus for energy saving (2022-2023) - UTS Central Research Budget V2X freight and emergency vehicle priority trial (2021-2022) - iMOVE CRC Safety and risk evaluation of Train Level Crossings (2021) - Transport for NSW Ai-RAP Automation for Australian Road Safety (2020-2022) - iMOVE CRC Dr. Mao actively contributes to the Future Mobility Lab at UTS, where his team develops integrated approaches to transportation challenges through collaboration with government agencies including Transport for NSW and research consortia like iMOVE CRC. His work bridges theoretical optimization methods with practical transportation solutions across Australian contexts, with particular focus on Sydney's transportation infrastructure.

• Mucosal Immunology
• Gut Microbiome
• Immune System Regulation
• +۴ مورد دیگر

Dr Amanda Cox is a Senior Lecturer in the School of Pharmacy and Medical Sciences at Griffith University, where she also serves as a Research Leader in the Institute for Biomedicine and Glycomics. She holds dual leadership roles as an academic lead for both Griffith University's Central Facility for Genomics and the Gut Health Clinic through the Allied Health Clinics. Her research career spans over a decade at Griffith University, progressing from Research Fellow to her current Senior Lecturer position. Her educational background includes: BBiomedSci (Hons) from University of Newcastle, Australia PhD from University of Newcastle, Australia Grad Cert Tertiary Teaching from University of Newcastle, Australia Dr Cox's research focuses on applied mucosal immunology, with particular emphasis on how the gut microbiome contributes to immune and inflammatory activity in various health and disease states, especially metabolic diseases. Her work uniquely integrates multiple technologies including multiparametric risk scoring, direct-counting gene expression analyses, and in situ spatial proteomic and transcriptomic analyses to assess immune pathways in disease pathogenesis and individual responses to interventions. Analysis of her recent publications reveals a clear trend toward spatial biology techniques applied to immunological questions, particularly examining inflammatory responses in conditions like eosinophilic chronic rhinosinusitis and nasal polyposis. Her work increasingly integrates machine learning with molecular profiling while maintaining strong connections to clinical applications, especially in metabolic disease and exercise physiology contexts. Dr Cox actively supervises multiple graduate students across immunology and related fields, with current projects examining tissue characterisation in eosinophilic oesophagitis and anti-cancer immunity. Her grant portfolio demonstrates substantial funding from pharmaceutical partners including Sanofi, Regeneron, and Glaxo Smith Kline, as well as university and government sources, supporting research in spatial mapping of type 2 inflammation, gut microbiome interactions, and effects of compounds like fucoidan and cannabidiol. She leads research teams within the Institute for Biomedicine and Glycomics and collaborates extensively with clinical specialists across multiple disciplines, industry partners in diagnostics and pharmaceuticals, and academic researchers. Her work with the Central Facility for Genomics supports advanced molecular analysis across the university community.