Rate My Professor Qian Li

Dr. Qian Li is a Lecturer at the School of Electrical Engineering, Computing and Mathematical Sciences (EECMS) in the Faculty of Science and Engineering at Curtin University, Perth. Her academic background includes a Ph.D. in Computer Science from the Institute of Information Engineering, Chinese Academy of Sciences (CAS), a Master by Research in Computer Science from Shandong University, and a second Master by Research in Computer Science from the University of Luxembourg, funded by the Luxembourg Scholarship. Prior to her current position, she served as a Postdoctoral Research Fellow at the University of Technology Sydney (UTS) from July 2019 to October 2021. Additionally, she worked as a Data Scientist for the Department of Industry and Providence Asset Group in Australia from 2019 to 2023, contributing to a joint project with UNSW on AI applications for solar farms and energy storage. Dr. Li has been a Chief Investigator on National Natural Science Foundation of China projects, including a 2013-2017 initiative on context-aware sensor network architecture for healthcare monitoring and a 2020-2024 project on trustworthy AI and topological data analysis, securing a $120k grant.

Dr. Qian Li's research specializations include causal reasoning for machine learning, topological data analysis, Riemannian optimization, optimal transport, computer vision, data mining, natural language processing, and data science, with applications in medical science, insurance, energy, and commerce. She has authored over 50 articles in high-quality venues such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Information Systems, ACM Transactions on Recommender Systems, ACM Transactions on Knowledge Discovery from Data, VLDB Journal, Expert Systems with Applications, Neurocomputing, and Pattern Recognition, as well as conferences including CIKM, SIGIR, WWW, CVPR, and AAAI (CORE A*/A). Key publications are "Causality-guided Graph Learning for Session-based Recommendation" (CIKM 2023), "Counterfactual Explainable Conversational Recommendation" (IEEE TKDE 2023), "Be Causal: De-biasing Social Network Confounding in Recommendation" (ACM TKDD 2022), "Deep Treatment-Adaptive Network for Causal Inference" (VLDB 2021), and "Hilbert Sinkhorn Divergence for Optimal Transport" (CVPR 2021). Her contributions have advanced causal inference, fairness-aware recommendations, and counterfactual explanations in AI. Dr. Li received awards including the 2016 Chinese National Graduate Scholarship (Top 1%), 2015 Director Scholarship (Top 1%), and 2010 Luxembourg Student Scholarship (Top 2%). She served on the Program Committee for AAAI 2022.