ORION: Online Regularized Multi-task Regression and Its Application to Ensemble Forecasting. - Jianpeng Xu; Pang-Ning Tan; Lifeng Luo (ICDM, 2014)

WISDOM: Weighted incremental spatio-temporal multi-task learning via tensor decomposition. - Jianpeng Xu; Jiayu Zhou; Pang-Ning Tan; Xi Liu; Lifeng Luo (IEEE BigData, 2016)

GSpartan: a Geospatio-Temporal Multi-task Learning Framework for Multi-location Prediction. - Jianpeng Xu; Pang-Ning Tan; Lifeng Luo; Jiayu Zhou (SDM, 2016)

Assessing the impacts of climate and land use lane cover changes on hydrological droughts in the Yellow River Basin using SWAT model with time-varying parameters. - Yunyun Li; Jianxia Chang; Lifeng Luo (Agro-Geoinformatics, 2017)

Online Multi-Task Learning Framework for Ensemble Forecasting. - Jianpeng Xu; Pang-Ning Tan; Jiayu Zhou; Lifeng Luo (IEEE Trans. Knowl. Data Eng., 2017)

Distribution Preserving Multi-task Regression for Spatio-Temporal Data. - Xi Liu; Pang-Ning Tan; Zubin Abraham; Lifeng Luo; Pouyan Hatami (ICDM, 2018)

A Low Rank Weighted Graph Convolutional Approach to Weather Prediction. - Tyler Wilson; Pang-Ning Tan; Lifeng Luo (ICDM, 2018)

MUSCAT: Multi-Scale Spatio-Temporal Learning with Application to Climate Modeling. - Jianpeng Xu; Xi Liu; Tyler Wilson; Pang-Ning Tan; Pouyan Hatami; Lifeng Luo (IJCAI, 2018)

Hierarchical LSTM Framework for Long-Term Sea Surface Temperature Forecasting. - Xi Liu; Tyler Wilson; Pang-Ning Tan; Lifeng Luo (DSAA, 2019)

OMuLeT: Online Multi-Lead Time Location Prediction for Hurricane Trajectory Forecasting. - Ding Wang; Boyang Liu; Pang-Ning Tan; Lifeng Luo (AAAI, 2020)

Convolutional Methods for Predictive Modeling of Geospatial Data. - Tyler Wilson; Pang-Ning Tan; Lifeng Luo (SDM, 2020)

Automated Analysis of the US Drought Monitor Maps With Machine Learning and Multiple Drought Indicators. - Pouyan Hatami Bahman Beiglou; Lifeng Luo; Pang-Ning Tan; Lisi Pei (Frontiers Big Data, 2021)

Spatio-Temporal Multi-Task Learning via Tensor Decomposition. - Jianpeng Xu; Jiayu Zhou; Pang-Ning Tan; Xi Liu; Lifeng Luo (IEEE Trans. Knowl. Data Eng., 2021)

DeepGPD: A Deep Learning Approach for Modeling Geospatio-Temporal Extreme Events. - Tyler Wilson; Pang-Ning Tan; Lifeng Luo (AAAI, 2022)

DeepExtrema: A Deep Learning Approach for Forecasting Block Maxima in Time Series Data. - Asadullah Hill Galib; Andrew McDonald 003; Tyler Wilson; Lifeng Luo; Pang-Ning Tan (IJCAI, 2022)

COMET Flows: Towards Generative Modeling of Multivariate Extremes and Tail Dependence. - Andrew McDonald 003; Pang-Ning Tan; Lifeng Luo (IJCAI, 2022)

Beyond Point Prediction: Capturing Zero-Inflated & Heavy-Tailed Spatiotemporal Data with Deep Extreme Mixture Models. - Tyler Wilson; Andrew McDonald 003; Asadullah Hill Galib; Pang-Ning Tan; Lifeng Luo (KDD, 2022)

SimEXT: Self-supervised Representation Learning for Extreme Values in Time Series. - Asadullah Hill Galib; Pang-Ning Tan; Lifeng Luo (ICDM, 2023)

Self-Recover: Forecasting Block Maxima in Time Series from Predictors with Disparate Temporal Coverage Using Self-Supervised Learning. - Asadullah Hill Galib; Andrew McDonald 003; Pang-Ning Tan; Lifeng Luo (IJCAI, 2023)

Unraveling Block Maxima Forecasting Models with Counterfactual Explanation. - Yue Deng 004; Asadullah Hill Galib; Pang-Ning Tan; Lifeng Luo (KDD, 2024)

FIDE: Frequency-Inflated Conditional Diffusion Model for Extreme-Aware Time Series Generation. - Asadullah Hill Galib; Pang-Ning Tan; Lifeng Luo (NeurIPS, 2024)

FABLE: A Localized, Targeted Adversarial Attack on Weather Forecasting Models. - Yue Deng 004; Asadullah Hill Galib; Xin Lan; Pang-Ning Tan; Lifeng Luo (CoRR, 2025)