PhD - University of Adelaide. 2014
Prof. Lina Yao is currently a Senior Principal Research Scientist and Science Lead at CSIRO's Data61, and Conjoint Full Professor at UNSW. Prior to that, she is a Scientia Associate Professor and Acting Associate Head of School (Research) in the School of Computer Science and Engineering. She is leading the research group Data Dynamics Lab (D2 Lab) founded in 2016. We strive for developing generalizable and explainable data-efficient data mining, machine learning and deep learning algorithms—as well as designing systems and interfaces—to enable novel ways of human-machine interactions, including an improved understanding of challenges such as robustness, trust, explainability and resilience that improve human-autonomy partnership.
Her research area is in Few-Shot Learning, Zero-Shot Learning, Deep Reinforcement Learning, Meta-Learning, Neural Process, Self-supervised Learning, Graph Neural Networks and their applications in a broad range of applications in Recommender Systems, Computer Vision, Brain-Computer Interface, Biomedical Image Analysis, Intelligent Transportation System, and Internet of Things. She maintains a strong international research collaboration with world-leading universities such as Stanford University, Tsinghua University, UCSD, TU Wien etc. She is serving as Associate Editor for ACM Transactions on Sensor Networks (ACM TOSN), Knowledge-based Systems (KNOSYS) and Section of Recommender Systems of Frontiers in Big Data. She has over 200 peer-reviewed publications both in international leading conferences and journals including NeurIPS, SIGKDD, WWW, SIGIR, ICDM, CVPR, UbiComp, AAAI, IJCAI etc.
Up to date information can be found at her personal website - https://www.linayao.com/
Australia Category-1 Grants:
My Research Supervision
Please check my personal website or Data Dynamics website for more information.
COMP9727 - Recommender Systems
COMP9321 - Data Service Engineering
UNSW CSE Honour thesis and Master's research project students
Vertically Integrated Project - Data Dynamics