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I am specialised in remote sensing, Earth observation (EO), and geospatial data science. My current research centres on modelling canopy height by integrating GEDI LiDAR and Sentinel-2 satellite data. This work leverages high-performance computing (HPC), cloud platforms, and machine learning (ML) to produce scalable, reproducible workflows for environmental monitoring and decision support.

My current focus includes:

• EO-driven canopy height estimation for forest structure and biomass monitoring

• Scalable HPC/cloud workflows for processing LiDAR and satellite data

• AI/ML applications in EO for ecosystem modelling and climate resilience

• Supporting policy and land planning with EO-derived environmental indicators

Previously, I led research on satellite-based grassland curing to improve fire monitoring, addressing inter-satellite variability and product accuracy for use by fire managers. I also contributed to government-led programs focusing on environmental water planning and provide the framework for coordinating the development of flood works.

I collaborate with academic, government, and industry stakeholders nationally and internationally to ensure EO science translates into tools and insights that support environmental monitoring.

Dr. Erlei Li is currently a Postdoctoral Research Fellow at the University of Queensland, where he continues his research in computational process modelling for sustainable metallurgy. He obtained his BEng and MEng degrees from Northeastern University (China) in 2011 and 2015, respectively, and was awarded a Doctor of Philosophy (PhD) from Monash University in 2022. Dr. Li previously worked as a Postdoctoral Research Fellow at the University of Queensland (2022–2023) and spent two years at the National University of Singapore (2023–2025) as a Research Fellow before returning to UQ.

Dr. Li’s research focuses on physics-based modelling and numerical simulation of complex multiphase and powder transport phenomena in metallurgy, advanced manufacturing, and mineral processing. His expertise lies in developing computational frameworks—including CFD, DEM, unresolved and resolved CFD–DEM coupling, VOF, and LBM methods to elucidate the coupled mechanisms of heat transfer, fluid flow, and particle dynamics across multiple scales.

Dr. Li received the Best Student Presentation Award at the 3rd International Symposium on Computational Particle Technology (CPT2021) and was awarded the Humboldt Research Fellowship for Postdocs. He also serves on the Youth Editorial Board of Advanced Powder Materials.

Yiqiong specializes in research within the domains of HRM and organizational behavior, with a particular focus on workplace bullying prevention. Her research agenda explores how organizational and job factors influence work-related well-being and seeks to translate this knowledge into strategies that enhance employee health and safety. Yiqiong works closely with organisations, unions, and peak work health and safety bodies to ensure that the findings of her research are translated into workplaces effectively. Her work has informed workplace practices and provided practical resources that support system-wide changes that not only prevent bullying but also promote the overall well-being of all employees.

Dr. Joan Li is a Senior Lecturer and a Research Fellow with an established national and international reputation at The University of Queensland. She holds both an MD and a PhD, blending clinical and scientific expertise, which provides her with a unique perspective on research and education. While establishing an emerging profile in medical education, she maintains engagement in discipline-related biomedical research through collaboration and supervision.

With over seven years of teaching experience, Joan has actively engaged in face-to-face teaching in biomedical science and medicine courses, contributed to curriculum design, development, and course coordination for both undergraduate and postgraduate programs. She brings her strong analytical skills and critical thinking abilities, honed through her medical and biomedical research background, to her teaching practices. Driven by a genuine passion for teaching, Joan continuously strives for excellence, with specific interests in assessment, curriculum design, development and student learning experience. She has implemented innovative teaching methods, designed diverse and inclusive curricula, created new learning activities, and fostered student engagement as learning partners, with a consistent goal of improving curriculum quality and enhancing student learning outcomes.

Leveraging her medical knowledge, extensive experience in biomedical research, and growing understanding of medical education, Joan is committed to developing medical students into critical thinkers and lifelong learners with a genuine appreciation for medical practice and medical research, enabling them to better serve an ever-changing society. Drawing upon her extensive experience in developmental biology and physiology, particularly in cardiac and renal research, Joan actively supervises higher degree research students and continues to make significant contributions to discipline-related research through publications and collaborations.

Dr. Joan Li is a versatile academic professional with a rich background in biomedical research and an emerging presence in medical education research. Her dedication to teaching and learning, combined with her impressive track record in both disciplines, makes her a valuable asset to The University of Queensland and the broader academic community.

My research focuses on environmental biotechnology for removing and transforming persistent pollutants in water and wastewater.I specialise in microbial and hybrid biological–chemical processes that transform hard-to-degrade organic contaminants and nutrient pollutants, including PFAS and nitrogen compounds, into less harmful or resource-recoverable products through sustainable, low-carbon pathways.

I am particularly interested in how microorganisms interact with engineered systems to drive pollutant transformation. My work combines reactor engineering, microbiology, materials-assisted treatment, and multi-omics analysis to understand both treatment performance and the underlying biological mechanisms.

Key areas of my research include:

• PFAS biotransformation and defluorination
• Membrane biofilm reactors
• Microbial ecology in engineered systems
• Biological nitrogen removal
• Bio-Fenton and reactive oxygen species-based treatment
• Metagenomics, metatranscriptomics, and bioinformatics

At UQ, my work aims to develop sustainable technologies for treating emerging contaminants and recovering valuable resources from waste streams. This includes identifying microorganisms and enzymes involved in PFAS transformation, designing hybrid treatment systems, and linking microbial function to practical environmental engineering applications.

My research sits at the interface of environmental microbiology, water engineering, contaminant chemistry, and systems biology.

Ye is a second year house officer at the Princess Alexandra Hospital. She hopes to pursue a career in ophthalmology. Ye is heavily involved in ophthalmology research projects and hopes to continue to incorporate academia in her career.

Suri Li is a Postdoctoral Research Fellow at the Institute for Social Science Research, University of Queensland and the Centre of Excellence for Children & Families over the Life Course. Her current work centres on gender inequality and family dynamic across life course and explores the interplay of gender relations in the public and private spheres.

Prior to her current position, she holds a BSc and MSc in Finance, as well as an MA in Public Policy from the University of Edinburgh, the UK and a PhD in Sociology at Trinity College Dublin, Ireland. Her DPhil Thesis focus on the relationship between household resources and child wellbeing in Ireland, Australia and the UK using longitudinal data from birth cohort studies.

Hang is a Postdoctoral Research Fellow in IELab within the School of Electrical Engineering and Computer Science at the University of Queensland, Australia, where he works closely with Prof. Guido Zuccon, A/Prof. Bevan Koopman, and Dr. Ahmed Mourad. Prior to Ph.D, he received his Bachelor of Science degree in Computer Science at the University of Minnesota Twin-Cities, United States, 2016.

Hang's research interests span Information Retrieval (IR), Large Language Models (LLMs), Natural Language Processing (NLP), Agentic Search, Retrieval-Augmented Generation (RAG), and Machine Learning (ML). In particular, he is interested in developing intelligent search and information-access systems that combine effective retrieval with the reasoning and generation capabilities of LLMs. His research explores topics including neural and dense retrieval, retrieval enhancement and feedback, LLM-based relevance assessment, agentic and conversational search, RAG system design and evaluation, and the efficient and reliable integration of LLMs into real-world information retrieval pipelines.

Hang publishes at premier academic venues in IR (e.g. SIGIR, ECIR, WSDM, WWW, TOIS, IJDL). His work was supported by Grains Research and Development Corporation, through the AgAsk project during Ph.D.

Dr Jiaying Li is a Research Fellow at Queensland Alliance for Environmental Health Sciences (QAEHS), the University of Queensland, Australia (2021 - now). She obtained her Ph.D. in 2020 at Advanced Water Management Centre (AWMC), the University of Queensland. Her research interests include applying wastewater-based epidemiology for chemical and microbial biomarkers related to environmental and human health, understanding and modelling the fate of contaminants of emerging concerns in urban water systems, and developing an integrated approach for source tracking, identification, and control of environmental pollutants and micropollutants in sewage networks. Dr Li has published over 30 top-tier papers with >2,430 citations and an H-index of 19, including over 10 lead-author papers in Nature Water, the Lancet Global Health, Environmental Science & Technology, and Water Research. Her research achievements have been recognized with the awards of Massachusetts Institute of Technology CEE Rising Stars, Australian Academy of Science Max Day Environmental Science Fellowship (highly commended), UQ Research Stimulus Fellowship, etc.

Yayong Li has been a Postdoctoral Research Fellow under the supervision of Dr. Nan at The University of Queensland, where his research focuses on graph representation learning, PIML, and AI for agriculture. He specializes in machine-learning methodologies for dynamic and weakly supervised settings, such as incremental learning, few-shot learning, and learning under label noise.

Dr. Siyi Li is a Postdoctoral Research Fellow at the University of Queensland. Her research focuses on crop modelling, climate extremes, and G×E×M interactions, with a particular emphasis on improving the resilience and sustainability of Australian cropping system under climate change. She has extensive experience in APSIM simulations, high-performance computing, big-data analytics, and integrating diverse datasets across multiple sources and dimensions.