Rate My Professor Nan Ye

Nan Ye is a Senior Lecturer in Statistics and Data Science in the School of Mathematics and Physics within the Faculty of Science at the University of Queensland. He earned a PhD in Computer Science from the National University of Singapore, where he also obtained double first-class honours degrees in Computer Science and Applied Mathematics. Following his PhD, Ye held a postdoctoral researcher position at the National University of Singapore from 2013 to 2014. He then served as a joint postdoctoral researcher at Queensland University of Technology and the University of California, Berkeley from 2015 to 2018. Joining the University of Queensland thereafter, he has established a research program at the intersection of machine learning, statistics, and optimization. Ye received a UQ Early Career Researcher Grant for his project on Sparse Methods for Learning, Prediction and Decision Making. He is an Associate Investigator at the ARC Centre of Excellence for Mathematical and Statistical Frontiers.

Ye's academic interests include machine learning algorithms and theory, applications of machine learning, sequential decision making under uncertainty, weakly supervised learning, probabilistic graphical models, and statistical learning theory. His publications, exceeding 2,300 citations, appear in leading conferences and journals such as NeurIPS, ICML, ICLR, IJCAI, UAI, ICRA, JAIR, Nature Communications, and Annals of Operations Research. Prominent works include "DESPOT: Online POMDP Planning with Regularization" (JAIR, 2017), recipient of the IJCAI-JAIR Best Paper Prize in 2022; "Near-optimal Adaptive Pool-based Active Learning with General Loss" (UAI, 2014), awarded the UAI Best Student Paper Award; "Positive-unlabeled learning using random forests via recursive greedy risk minimization" (NeurIPS, 2022); "Greedy Convex Ensemble" (IJCAI, 2020); "Robust and interpretable prediction of gene markers and cell types from spatial transcriptomics data" (Nature Communications, 2026); and "Spatial-temporal neural networks for catch rate standardization and fish distribution modeling" (Fisheries Research, 2024). Ye has contributed as Senior Program Committee member for AAAI 2023 and IJCAI 2023, and served as a tutorial speaker at ANZIAM 2023. His research influences areas including robotics, fisheries stock assessment, cardiovascular modeling, and telehealth.