Find Academic Supervisors

• Acoustics and noise control
• Dynamics, vibration and vibration control
• Signal processing
• +3 more

Dr. Sipei Zhao is a Senior Lecturer at the School of Mechanical and Mechatronic Engineering at the University of Technology Sydney (UTS), where he has been employed since January 2021. Prior to this, he worked as a Post-doctoral Research Fellow at the Centre for Audio, Acoustics and Vibration of UTS from July 2018 to December 2020. His educational background includes a PhD in Electrical Engineering from RMIT University (2018), a Master's degree in Acoustics from Nanjing University (2015), and a Bachelor's degree in Electronics Engineering from Nanjing University (2012). Dr. Zhao's research focuses on acoustics and noise control, dynamics and vibration control, and signal processing. His work spans theoretical development and practical applications in active noise control, architectural acoustics, and machine learning for acoustic analysis. He has made significant contributions to distributed acoustic systems, neural network applications in sound field reconstruction, and innovative approaches to sound zone control. His recent publications demonstrate a strong trajectory in distributed acoustic systems, neural network applications in acoustics, and innovative approaches to sound field control and reproduction. His work combines theoretical rigor with practical implementations, often resulting in significant reductions in computational complexity while maintaining or improving performance. Best Student Paper at the 22nd International Congress on Sound and Vibration (ICSV22) in 2015 Best Paper Prize at the 21st International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRA2016) in 2016 Best Paper Award at the 23rd International Congress on Acoustics (ICA2019) in 2019 Young Professionals Grant from the International Institute of Noise Control Engineering (I-INCE) Ford Publication Commendation Prize from RMIT University in 2017 ARC Early Career Industry Fellowship in 2024 Dr. Zhao has successfully secured multiple research grants and contracts from organizations including the Australian Research Council, NSW Environment Protection Authority, and industry partners like Noizend Pty Ltd. His research has practical applications in industrial settings, transportation, and building acoustics. He serves as a peer reviewer for prestigious journals including the Journal of Sound and Vibration and IEEE/ACM Transactions on Audio, Speech, and Language Processing.

Yi LiuView profile

Associate Professor

• Earth Observation
• Ecohydrology
• Climate Change
• +5 more

Associate Professor Yi Liu is a faculty member at the University of New South Wales' School of Civil and Environmental Engineering. He holds a PhD in Remote Sensing in Hydrology from UNSW (2012) and dual MSc degrees from Vrije Universiteit Amsterdam in Hydrology (2007) and Environment and Resource Management (2005). His office is located in Room 112, Civil Engineering Building at UNSW's Kensington Campus. Liu's research focuses on earth observation, ecohydrology, climate change impacts, and extreme event analysis using satellite remote sensing. His work integrates microwave and optical remote sensing to study vegetation dynamics, soil moisture patterns, drought mechanisms, and carbon cycle processes across global ecosystems. Recent investigations examine Amazon rainforest responses to drought, high-mountain precipitation reconstruction, and CO2 fertilization effects on vegetation. Analysis of Liu's recent publications reveals strong emphasis on: • Satellite data fusion techniques • Climate-vegetation feedback mechanisms • Hydrological extremes and drought prediction • Global carbon cycle constraints • Machine learning applications in earth observation Scientific Awards: ARC Future Fellowship (2023) Clarivate Highly Cited Researcher - Cross-Field (2020-2022) UNSW Scientia Program (2021) ARC DECRA Award (2014) Malcolm Chaikin Engineering Research Prize (2013)

Badal PokharelView profile

Research Fellow

• Geospatial Engineering
• Disaster Risk Reduction and Management
• Climate Change
• +4 more

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.

Scott McManusView profile

Lecturer

• Data Science
• Spatial Science
• Geostatistics
• +12 more

Scott McManus is a Lecturer in Spatial Science at Charles Sturt University, affiliated with the School of Agricultural, Environmental and Veterinary Sciences. He is an active academic researcher and educator, contributing to interdisciplinary studies that bridge data science, geostatistics, and Indigenous knowledge systems. PhD in Data Science, Charles Sturt University (2022) Graduate Certificate in Applied Statistics, CSU (2017) Graduate Diploma in Applied Science (Information Science), CSU (2005) Graduate Diploma in Archaeological Heritage, University of New England (2004) B.App.Sci in Applied Geology, CSU (1994) Scott's research focuses on the application of data science and machine learning in environmental and health contexts, with a strong emphasis on ethical AI, digital data sovereignty, and responsible use of data when working with First Nations communities. His work integrates Western scientific methods with Indigenous methodologies, particularly in conservation efforts such as koala habitat protection and mangrove ecosystem recovery. His recent publications and research outputs (23 total) demonstrate a consistent trend in merging geospatial analytics, Bayesian uncertainty modeling, and deep learning with ethical and cultural frameworks. Key areas include fire impact on coastal vegetation, river blockage detection in Southeast Asia, and reconciliation in science through collaborative Indigenous-Western research practices. Faculty Early Career Researcher (ECR) Scheme (2023) Open Access Publishing Scheme (2025) Conference Travel Grant (2018) CSU ILWS Category B Research Support Fund (2020) Executive Deans List (2017) Scott is a registered Professional Geologist (Australian Institute of Geoscientists), member of the International Association for Mathematical Geosciences, and the Aboriginal and Torres Strait Islander Mathematics Alliance. He serves as a Faculty representative on the Indigenous Board of Studies and is a registered supervisor. His work is supported by ongoing grants focused on AI, machine learning, and open-access research dissemination. He actively participates in academic workshops, particularly in digital learning platforms like Brightspace, and contributes to public engagement through media appearances on koala conservation and environmental stewardship. Scott is involved in the Data Science and Engineering Research Unit and the Data Mining Research Group (DaMRG) at CSU, where he contributes to projects on predictive analytics and responsible data use. His collaborative network includes researchers in environmental science, Indigenous studies, and conservation biology, reflecting his commitment to interdisciplinary and culturally responsive research.

Fernando Marmolejo RamosView profile

Lecturer

• Experimental Psychology
• Embodied Cognition
• Artificial Intelligence
• +7 more

Fernando Marmolejo Ramos is a Lecturer in Psychology at Flinders University's College of Education, Psychology and Social Work. He holds external roles including Adjunct Research Fellow at University of South Australia (2024–present) and Visiting Research Fellow at University of Adelaide (2011–present). His research focuses on embodied cognition, AI, statistical modeling, and open science practices. Education: PhD in Psychology (University of Adelaide, 2007–2011), MSc (University of Ballarat, 2005–2007), and BSc (Universidad del Valle, 1997–2003). Research interests include language processing in neurodegenerative disorders, machine learning applications in healthcare, and AI in education. He has secured grants totaling over $1M AUD for projects like statistical infection detection algorithms using wearables and AI-enhanced learning tools. Recent awards include CSIRO On Prime Innovation Reward (2024) and Flinders University Teaching Award (2025). He reviews for journals like Neuroscience and Biobehavioral Reviews and serves on grant review panels for national research councils in multiple countries.

• Film Noir
• Urban History
• Documentary Filmmaking
• +4 more

Associate Professor Sean Maher is a researcher and educator in Film, Screen & Animation at Queensland University of Technology's Faculty of Creative Industries, Education & Social Justice. He serves as Faculty Ethics Chair and holds a Visiting Professorship at the University of Greenwich (2023-2028). Recognized as Australia's leading film researcher in 2019 by The Australian, his work bridges academic research and practical filmmaking. PhD from Queensland University of Technology Master's from University of New South Wales Maher's research explores: Film noir as urban historiography Media platformization in documentary Creative practice in tertiary education Screen production in global contexts Historical analysis of cinematic cities Media technology epistemologies His recent publications examine intersections of music video hyperreality, animation for cultural safety, and platform-driven transformations in screen media. Awards include: 2019 : Australia's National Field Leader in Film Research 2017 : UCLA Scholar-in-Residence 2016 : UK AHRC Filmmaking Research Network 2015 : President of ASPERA Maher supervises postgraduate research in documentary pitching, film festivals, and screen education. He pioneered the QUT/UCLA Los Angeles study tour and contributes to Australian screen policy through Cinema Ventures board membership.

Stuart JamesView profile

Lecturer

• Music Composition
• Immersive Audio and Video
• Electroacoustic Performance Practice
• +5 more

Dr. Stuart James is a Lecturer in the Composition and Music Technology program at the Western Australian Academy of Performing Arts , part of Edith Cowan University . His career spans composition, sound design, performance, and music technology development, with a focus on integrating acoustic and electronic media. Education: PhD (2015) in Spatial Audio and Synthesis Master of Arts in Creative Arts (2006) Bachelor of Music with First Class Honours (2001) Certificate in Jazz (1995) Research Interests encompass Music Composition with a blend of acoustic and electronic instruments, Immersive Audio-Visual Systems , Wave Terrain and Spectral Synthesis , and Digital Signal Processing for performance. His work explores Electroacoustic Performance Practice and Networked Music Environments . Publication Trends reflect a focus on experimental composition , interactive notation (notably iPad-based systems like the Decibel ScorePlayer), and spatial audio techniques . Collaborative projects with ensembles such as Decibel and artists like Erin Coates and Louise Devenish highlight his interdisciplinary approach. Scientific Awards include the ASME Young Composers' Competition State Finals Winner , the Dorothy Ransom Composition Prize , and nominations for Australian Music Centre Awards . Professional Contributions include founding membership in the Decibel Ensemble , managing a commercial recording studio for artists like ShockOne, and developing networked music notation software . He has supervised PhD projects on topics like meditative sonic praxis and timbre analysis .

• Transport Emissions
• Air Quality
• Emission Modeling
• +5 more

Dr. Robin Smit is an Adjunct Professor at the School of Civil and Environmental Engineering , University of Technology Sydney (UTS), and serves as Director/Founder of Transport Energy/Emission Research (TER). With nearly 30 years of experience across Europe, Australia, and Asia, he specializes in transport emissions modeling, remote sensing, and statistical analysis. Education: MSc in Air Quality (Wageningen University, 1994), PhD in Transport Emissions (Griffith University, 2007) Research Focus: Measurement/modeling of transport emissions, dynamic fleet modeling, software development, and air quality assessment using remote sensing and portable measurement systems. Key areas include diesel particulate filter malfunction analysis, NOx/NO2 discrepancies in Euro standards, and integration of AIS data for shipping emissions. Recent Publications demonstrate trends in real-world emission factors, validation of international models (COPERT) in Australian contexts, and methodological improvements in remote sensing data accuracy. Awards: CASANZ Distinguished Service Medal (2022) Collaborations: Member of the European Research Group on Mobile Emission Sources (ERMES), founder of the Transport Special Interest Group at CASANZ, and contributor to environmental policy development.

Binghao LiView profile

Associate Professor

• Indoor Positioning
• Pedestrian Navigation
• Satellite Positioning
• +3 more

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 MacIntyreView profile

Professor

• Emerging infectious diseases
• Biosecurity
• Epidemiology
• +8 more

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.

• Quantum Mechanics
• Quantum Information Theory
• Classical Mechanics
• +3 more

Sam Elman is a Postdoctoral Research Fellow at the School of Computer Science, University of Technology Sydney. His research focuses on Quantum mechanics and quantum information theory Mathematical aspects of free-parafermion solvability Topological entanglement entropy in multiple dimensions Optimal scheduling of quantum graph states Recent work includes publications on path decomposition algorithms for quantum computation and integrability of spin systems via frustration graphs. He is available for Masters Research or PhD student supervision. He is affiliated with the Faculty of Engineering and Information Technology Centre for Quantum Software and Information (QSI) UTS Research Centre

• Machine Learning
• Computer Vision
• 3D Geometry
• +2 more

Dr. Jun Li is a Senior Lecturer at the School of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney (UTS), Australia. He received his Ph.D. in Computer Science from Queen Mary University of London in 2009 and is affiliated with the Australian Artificial Intelligence Institute (AAII) at UTS. His research spans multiple domains within artificial intelligence, with primary focus on Machine Learning applications in computer vision and 3D geometry. Dr. Li has published extensively in high-impact journals including IEEE Transactions (TPAMI, TIP, TNNSLS) and Pattern Recognition, with recent work expanding into interdisciplinary research in earth science and marine applications. His research output demonstrates consistent productivity with numerous publications each year across diverse AI application areas. Dr. Li's work shows strong thematic progression from foundational computer vision techniques to applied interdisciplinary research. Early work focused on face hallucination and video super-resolution, while more recent publications address environmental applications using Graph Neural Networks for wave prediction and damage classification for disaster response. His research consistently bridges theoretical AI advances with practical real-world applications across healthcare, autonomous systems, and environmental science. AI to assist disaster emergency response (2023-2026) Applying Generative Adversarial Network in Medical Image Analysis (2020-2021) Big Massive Open Online Course (MOOC) Data Retrieval (2017-2020) As an educator, Dr. Li teaches core courses including '31005 Machine Learning' and '32513 Advanced Data Analytics Algorithms' at UTS, and is available for Masters Research and PhD student supervision, contributing to the development of next-generation AI researchers.

• Artificial Intelligence
• Brain-Computer Interfaces
• Fuzzy Neural Networks
• +8 more

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 .

• Low vision rehabilitation
• Depth perception
• Binocular vision
• +5 more

Dr. Vincent Nguyen serves as a Senior Lecturer in Orthoptics within the Graduate School of Health at the University of Technology Sydney. With a distinguished career spanning clinical practice, research, and academia, he brings extensive expertise in visual science and rehabilitation. His academic journey began with Honours in Orthoptics (1993) followed by a Master of Applied Science (1996), culminating in a PhD from the University of Sydney (2003) focused on binocular rivalry in visual psychophysics. Dr. Nguyen's research interests focus on low vision rehabilitation, depth perception, binocular vision, and the application of virtual reality and spatial audio technologies for assistive applications. His work bridges fundamental visual neuroscience with practical rehabilitation solutions, particularly for people with visual impairments. He has pioneered research in acoustic touch interfaces, virtual reality rehabilitation environments, and spatial audio navigation systems. His publication record demonstrates a clear trajectory from fundamental visual neuroscience to applied rehabilitation technologies. Recent work emphasizes immersive virtual reality applications for communication and physical rehabilitation, as well as innovative spatial audio systems that enhance navigation for people who are blind. His research integrates principles from neuroscience, engineering, and clinical practice to develop practical assistive solutions. Dr. Nguyen has secured significant research funding including NHMRC Ideas Grants (2023-2027) for 'Fluent Mobility for the Blind Individual Using Multimodal Auditory Sensory Augmentation' and CRC-P projects like 'ARIA - Bionic Visual-Spatial Medical Device for the Blind' (2022-2024). Current projects include 'EyeBot: AI-Powered Triage for Ophthalmology Referrals' (2025) and 'Next-Generation Extended Reality, Wearable Biosensors, and Metaverse Technologies for Medical Applications' (2024). As an educator, Dr. Nguyen teaches courses in Therapy and Rehabilitation (96037), Clinical Management of Refractive Error (96031), and Eye and Visual Systems (96027). His clinical background includes appointments as a Clinical Electrophysiologist with NSW Health (2007) and work with Vision Australia assisting people with low vision (2012). His postdoctoral work at York University's Centre for Vision Research with Professor Ian Howard focused on human depth perception, building on his foundational expertise in visual neuroscience.

• Data Mining
• Machine Learning
• Computer Vision
• +5 more

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.