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Wei LiuView profile

Associate Professor

• Natural Language Processing
• Generative AI
• Knowledge Graph Construction
• +6 more

Associate Professor Wei Liu is a full-time academic in the Department of Computer Science and Software Engineering at The University of Western Australia (UWA), leading the UWA Centre for Natural and Technical Language Processing. Her research focuses on knowledge discovery from natural language text, generative AI, semantic technologies, deep learning for knowledge graphs, and sequential data mining. She holds a PhD from the University of Newcastle (2003) and an MEng from Huazhong University of Science and Technology (China). Research Interests: Generative AI and Large Language Models (LLM) Multimodal Knowledge Graph Construction Human-AI Collaboration Systems Clinical Data Analysis (Ophthalmology) Technical Language Processing for Maintenance Data Neural-Symbolic Computation Recent Work Trends: Her publications emphasize multimodal systems integration, knowledge graph refinement, and adversarial AI applications. Notable 2025 work includes Docs2KG (human-LLM collaboration), Auto-Regressive Diffusion for 3D interactions, and spherical embeddings for logical queries. Scientific Awards: First Prize in IEEE ICDM/ICBK Knowledge Graph Contest (2020) Best Contribution to Science Award at DICTA 2020 2022 Students Choice Award for academic support Advising & Grants: Leads 25 active grants including ARC Training Centres in Critical Resources and Maintenance Data Science. Collaborates with industry partners like Aspire Digital Group and Minerals Research Institute of Western Australia. Labs/Teams: Directs UWA's Natural and Technical Language Processing Centre, focusing on projects like maintenance work order analysis, geological survey data fusion, and clinical data integration in ophthalmology.

Noorul AminView profile

Research Fellow

• Bioinformatics
• Computational Biology
• Machine Learning
• +5 more

Dr. Noorul Amin is a Postdoctoral Research Fellow at the School of Veterinary Science, The University of Queensland, affiliated with the SAAFE CRC's data analytics program. His research focuses on computational approaches to biological challenges, including omics data analysis, antimicrobial resistance, and machine learning applications in agribusiness and environmental systems. Education: Masters (Research) of Computer Engineering, Kyung Hee University Doctor of Philosophy of Computer Science, La Trobe University Research Focus: His work integrates machine learning, cloud computing, and big data analytics to address biological problems, with emphasis on antimicrobial resistance pathways, omics tool development, and computational genomics. Primary domains include bioinformatics, non-coding RNA classification, and single-cell sequencing methodologies. Publication Trends: Recent articles (2019-2025) predominantly explore machine learning in genomics and non-coding RNA analysis, with emerging focus on single-cell sequencing technologies and antimicrobial resistance mechanisms. Earlier work (2014-2017) centered on computational algorithms for graph theory and sensor networks. Student Advising & Projects: Actively seeking Honours and PhD candidates for projects including: AMR Digital Twin: Machine learning framework for antimicrobial risk assessment Semantic interoperability for OneHealth antimicrobial data integration AI-powered knowledge graphs for agricultural optimization Self-evolving ontology systems for cross-sectoral antimicrobial resistance analysis Collaborations: Contributes to the SAAFE CRC's mission through data analytics program initiatives, collaborating with interdisciplinary teams on food security and environmental health challenges.

Bevan KoopmanView profile

Associate Professor

• Information Retrieval
• Health Informatics
• Natural Language Processing
• +2 more

Dr. Bevan Koopman leads the Health Search team at CSIRO's Australian e-Health Research Centre and serves as Associate Professor in Language Technologies at University of Queensland. His research develops AI systems for clinical information retrieval, focusing on evidence-based medicine and health decision support. Current work examines large language models for medical question answering, automated clinical trial matching, and systematic review acceleration. Methodologies combine neural ranking, query refinement, and domain-specific knowledge integration. Publications demonstrate innovations in semantic search for medical records, Boolean query generation for systematic reviews, and conversational agents for agricultural health questions. Recent work evaluates ChatGPT for health information reliability. Teaching emphasizes quantitative skills development in biosciences. Funded projects include MathBench Australia for improving STEM education and automated diagnostic coding systems.

Falk ScholerView profile

Professor

• Information Access and Retrieval
• Fairness and Ethics of AI Systems
• Search Engine Evaluation
• +5 more

Professor Falk Scholer is a Professor of Information Access and Retrieval Technologies in the School of Computing Technologies at RMIT University, Melbourne, Australia. He leads the RMIT University Centre for Human-AI Information Environments (CHAI). His research focuses on understanding how search engines and recommender systems assist users in resolving information needs and measuring their effectiveness. His work emphasizes fairness, accountability, and human-centered computing. Research interests include interactive information access, evaluation methodologies, misinformation, and the ethical implications of AI systems. His projects span topics like bias mitigation in conversational search, physiological data analysis for user behavior, and generative AI adaptation for diverse scenarios. He collaborates on industry projects, such as enhancing job search systems with SEEK, improving query performance prediction, and developing fact-checking tools. His teaching interests include Data Science, Web Programming, and Research Methods. He actively supervises PhD and Master’s students in areas like fairness-aware systems and complex answer retrieval. Professor Scholer serves on committees including RMIT’s Academic Board and Human Research Ethics Committee. His research has been recognized through high-impact publications and partnerships addressing real-world challenges in search and information systems.