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Nic Kuo is a Research Fellow at the Centre for Big Data Research in Health at UNSW Sydney, where his research focuses on developing machine learning methods to generate realistic synthetic health data. He aims to improve predictive model calibration and support evidence-based clinical decision-making. A founding member of Health Gym, a global platform for open synthetic clinical datasets, he has made significant contributions with flagship datasets such as the ART HIV Dataset v2. Nic's academic journey includes a PhD in Computer Science from the Australian National University and a Master of Science in Applied Mathematics with First Class Honours from the University of Auckland. His work intersects machine learning, mathematics, and statistics, particularly in addressing complex challenges in healthcare. Nic is also involved in guest lecturing at UNSW and ANU, providing insights into health data science and document analysis, respectively. His passion lies in understanding memory, latent spaces, and representation in machine learning models, emphasizing the need for interpretable and trustworthy models in real-world applications.
Centre for Big Data Research in Health • Kensington, NSW, Australia
Develops machine learning methods to generate synthetic health data and improve predictive models.
Includes Business Intelligence, Enterprise Systems, and Cybersecurity Management streams.