Dr Ling Chen is a Professor in the School of Computer Science at the University of Technology Sydney (UTS), Australia. She received her PhD in Computer Engineering from Nanyang Technological University (NTU), Singapore, and subsequently completed postdoctoral training at the Leibniz University Hannover's L3S Research Centre in Germany.

Dr Chen’s research focuses on trustworthy machine learning, with particular emphasis on anomaly detection in graph-structured data and its applications, including fraud detection in financial transactions and malicious user detection in recommender systems. More recently, her work has expanded to the development of advanced decision-making agents, leveraging reinforcement learning and large language models (LLMs) to enable safe and reliable decision-making in interactive systems. Her current research includes hallucination detection and mitigation, as well as the design and implementation of guardrails for LLM-powered agents.

Dr Chen has successfully secured multiple competitive research grants, including an Australian Research Council (ARC) Future Fellowship (Level 3), underscoring the significance and impact of her contributions to the field. Her research has attracted funding and recognition from leading industry partners, including Facebook, TPG Telecom, and Zurich Insurance, as well as government agencies such as the NSW Department of Environment, Climate Change and Water, and the NSW Police Force.

As Research Director of the Australian Artificial Intelligence Institute (AAII), Australia’s largest AI research institute, Dr Chen leads the strategic development of a research community comprising more than 30 researchers and over 200 higher degree research students. Throughout her career, she has supervised 38 higher degree research (HDR) students and six postdoctoral researchers.

Dr Chen has delivered keynote addresses at six major national and international conferences in machine learning and data science. She currently serves as the IEEE Task Chair for Data Science and Advanced Analytics, contributing to the advancement of research and professional practice in the field.