Rate My Professor Nan Ye

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.