| 2026 | AAAI | Knowledge-Guided Machine Learning: A Paradigm Shift in AI for Science. | Anuj Karpatne, Xiaowei Jia, Vipin Kumar |
| 2026 | AAAI | EcoDiffusion: Uncertainty-Aware Emulation of Ecosystem Processes with Conditional Diffusion for Long Sequences with Single-Step Initialization. | Ruohan Li, Zhihao Wang, Xiaowei Jia, Gengchen Mai, Lei Ma, George C. Hurtt, Quan Shen, Zhili Li, Yiqun Xie |
| 2026 | AAAI | GREAT: Generalizable Representation Enhancement via Auxiliary Transformations for Zero-Shot Environmental Prediction. | Shiyuan Luo, Chonghao Qiu, Runlong Yu, Yiqun Xie, Xiaowei Jia |
| 2026 | CHI | When to Explain: Modeling User Need for Explanations in Real-World Autonomous Driving. | Shihong Ling, Yaohan Ding, Yu Liu, Yue Wan, Xiaowei Jia, Na Du |
| 2026 | KDD | Physics-enhanced Neural Operator: An Application in Simulating Turbulent Transport. | Shengyu Chen, Peyman Givi, Can Zheng, Xiaowei Jia |
| 2026 | KDD | X-MethaneWet: A Cross-scale Global Wetland Methane Emission Benchmark Dataset for Advancing Science Discovery with AI. | Yiming Sun, Shuo Chen, Shengyu Chen, Chonghao Qiu, Licheng Liu, Youmi Oh, Sparkle L. Malone, Gavin McNicol, Qianlai Zhuang, Chris Smith, Yiqun Xie, Xiaowei Jia |
| 2025 | AAAI | Multi-Scale Graph Learning for Anti-Sparse Downscaling. | Yingda Fan, Runlong Yu, Janet R. Barclay, Alison P. Appling, Yiming Sun, Yiqun Xie, Xiaowei Jia |
| 2025 | AAAI | Physics-Guided Fair Graph Sampling for Water Temperature Prediction in River Networks. | Erhu He, Declan Kutscher, Yiqun Xie, Jacob Zwart, Zhe Jiang, Huaxiu Yao, Xiaowei Jia |
| 2025 | AAAI | Physics-Guided Foundation Model for Scientific Discovery: An Application to Aquatic Science. | Runlong Yu, Chonghao Qiu, Robert Ladwig, Paul C. Hanson, Yiqun Xie, Xiaowei Jia |
| 2025 | ACL | Unveiling Confirmation Bias in Chain-of-Thought Reasoning. | Yue Wan, Xiaowei Jia, Xiang Lorraine Li |
| 2025 | ICCV | Compressed Diffusion: Pruning with Knowledge Distillation for Efficient Text-to-Image Generation. | Nasrin Kalanat, Ohiremen Dibua, Yan Kang, Yifan Gong, Xiaowei Jia |
| 2025 | ICDM | Learning to Retrieve for Environmental Knowledge Discovery: An Augmentation-Adaptive Self-Supervised Learning Framework. | Shiyuan Luo, Runlong Yu, Chonghao Qiu, Rahul Ghosh, Robert Ladwig, Paul C. Hanson, Yiqun Xie, Xiaowei Jia |
| 2025 | ICDM | Truth Without Comprehension: A Bluesky Agenda for Steering the Fourth Mathematical Crisis. | Runlong Yu, Xiaowei Jia |
| 2025 | IROS | DriveBLIP2: Attention-Guided Explanation Generation for Complex Driving Scenarios. | Shihong Ling, Yue Wan, Xiaowei Jia, Na Du |
| 2025 | PAKDD | A Survey of Foundation Models for Environmental Science. | Runlong Yu, Shengyu Chen, Yiqun Xie, Xiaowei Jia |
| 2025 | SDM | Domain-Adaptive Continual Meta-Learning for Modeling Dynamical Systems: An Application in Environmental Ecosystems. | Yiming Sun, Runlong Yu, Runxue Bao, Yiqun Xie, Ye Ye, Xiaowei Jia |
| 2025 | SDM | What We Talk About When We Talk About AI for Science. | Runlong Yu, Yiqun Xie, Xiaowei Jia |
| 2024 | AAAI | Referee-Meta-Learning for Fast Adaptation of Locational Fairness. | Weiye Chen, Yiqun Xie, Xiaowei Jia, Erhu He, Han Bao, Bang An, Xun Zhou |
| 2024 | AAAI | Fair Graph Learning Using Constraint-Aware Priority Adjustment and Graph Masking in River Networks. | Erhu He, Yiqun Xie, Alexander Y. Sun, Jacob Zwart, Jie Yang, Zhenong Jin, Yang Wang, Hassan A. Karimi, Xiaowei Jia |
| 2024 | AAAI | SimFair: Physics-Guided Fairness-Aware Learning with Simulation Models. | Zhihao Wang, Yiqun Xie, Zhili Li, Xiaowei Jia, Zhe Jiang, Aolin Jia, Shuo Xu |
| 2024 | AAAI | Spatial-Logic-Aware Weakly Supervised Learning for Flood Mapping on Earth Imagery. | Zelin Xu, Tingsong Xiao, Wenchong He, Yu Wang, Zhe Jiang, Shigang Chen, Yiqun Xie, Xiaowei Jia, Da Yan, Yang Zhou |
| 2024 | HRI | Improving Explainable Object-induced Model through Uncertainty for Automated Vehicles. | Shihong Ling, Yue Wan, Xiaowei Jia, Na Du |
| 2024 | ICDM | ExoTST: Exogenous-Aware Temporal Sequence Transformer for Time Series Prediction. | Kshitij Tayal, Arvind Renganathan, Xiaowei Jia, Vipin Kumar, Dan Lu |
| 2024 | ICDM | Adaptive Process-Guided Learning: An Application in Predicting Lake DO Concentrations. | Runlong Yu, Chonghao Qiu, Robert Ladwig, Paul C. Hanson, Yiqun Xie, Yanhua Li, Xiaowei Jia |
| 2024 | IJCAI | Transfer Learning Using Inaccurate Physics Rule for Streamflow Prediction. | Tianshu Bao, Taylor T. Johnson, Xiaowei Jia |
| 2024 | PPSN | Evolution-Based Feature Selection for Predicting Dissolved Oxygen Concentrations in Lakes. | Runlong Yu, Robert Ladwig, Xiang Xu, Peijun Zhu, Paul C. Hanson, Yiqun Xie, Xiaowei Jia |
| 2024 | SDM | Knowledge Guided Machine Learning for Extracting, Preserving, and Adapting Physics-aware Features. | Erhu He, Yiqun Xie, Licheng Liu, Zhenong Jin, Dajun Zhang, Xiaowei Jia |
| 2024 | SDM | Only Attending What Matter within Trajectories - | Mingzhi Hu, Xin Zhang, Yanhua Li, Yiqun Xie, Xiaowei Jia, Xun Zhou, Jun Luo |
| 2024 | SDM | Spatial-Temporal Augmented Adaptation via Cycle-Consistent Adversarial Network: An Application in Streamflow Prediction. | Nasrin Kalanat, Yiqun Xie, Yanhua Li, Xiaowei Jia |
| 2024 | SDM | Combining Satellite and Weather Data for Crop Type Mapping: An Inverse Modelling Approach. | Praveen Ravirathinam, Rahul Ghosh, Ankush Khandelwal, Xiaowei Jia, David J. Mulla, Vipin Kumar |
| 2023 | AAAI | Physics Guided Neural Networks for Time-Aware Fairness: An Application in Crop Yield Prediction. | Erhu He, Yiqun Xie, Licheng Liu, Weiye Chen, Zhenong Jin, Xiaowei Jia |
| 2023 | AAAI | Task-Adaptive Meta-Learning Framework for Advancing Spatial Generalizability. | Zhexiong Liu, Licheng Liu, Yiqun Xie, Zhenong Jin, Xiaowei Jia |
| 2023 | AAAI | Point-to-Region Co-learning for Poverty Mapping at High Resolution Using Satellite Imagery. | Zhili Li, Yiqun Xie, Xiaowei Jia, Kara Stuart, Caroline Delaire, Sergii Skakun |
| 2023 | AAAI | Auto-CM: Unsupervised Deep Learning for Satellite Imagery Composition and Cloud Masking Using Spatio-Temporal Dynamics. | Yiqun Xie, Zhili Li, Han Bao, Xiaowei Jia, Dongkuan Xu, Xun Zhou, Sergii Skakun |
| 2023 | CIKM | Meta-Transfer-Learning for Time Series Data with Extreme Events: An Application to Water Temperature Prediction. | Shengyu Chen, Nasrin Kalanat, Simon N. Topp, Jeffrey M. Sadler, Yiqun Xie, Zhe Jiang, Xiaowei Jia |
| 2023 | ICDM | Self-supervised Pre-training for Robust and Generic Spatial-Temporal Representations. | Mingzhi Hu, Zhuoyun Zhong, Xin Zhang, Yanhua Li, Yiqun Xie, Xiaowei Jia, Xun Zhou, Jun Luo |
| 2023 | ICDM | Koopman Invertible Autoencoder: Leveraging Forward and Backward Dynamics for Temporal Modeling. | Kshitij Tayal, Arvind Renganathan, Rahul Ghosh, Xiaowei Jia, Vipin Kumar |
| 2023 | IJCAI | CGS: Coupled Growth and Survival Model with Cohort Fairness. | Erhu He, Yue Wan, Benjamin H. Letcher, Jennifer H. Fair, Yiqun Xie, Xiaowei Jia |
| 2023 | IJCAI | Confidence-based Self-Corrective Learning: An Application in Height Estimation Using Satellite LiDAR and Imagery. | Zhili Li, Yiqun Xie, Xiaowei Jia |
| 2023 | SDM | A Hidden Markov Forest Model for Terrain-Aware Flood Inundation Mapping from Earth Imagery. | Zhe Jiang, Yupu Zhang, Saugat Adhikari, Da Yan, Arpan Man Sainju, Xiaowei Jia, Yiqun Xie |
| 2023 | SDM | Physics-Guided Meta-Learning Method in Baseflow Prediction over Large Regions. | Shengyu Chen, Yiqun Xie, Xiang Li, Xu Liang, Xiaowei Jia |
| 2023 | SDM | Physics-guided Graph Diffusion Network for Combining Heterogeneous Simulated Data: An Application in Predicting Stream Water Temperature. | Xiaowei Jia, Shengyu Chen, Can Zheng, Yiqun Xie, Zhe Jiang, Nasrin Kalanat |
| 2023 | SDM | Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications. | Shaoming Xu, Ankush Khandelwal, Xiang Li, Xiaowei Jia, Licheng Liu, Jared Willard, Rahul Ghosh, Kelly Cutler, Michael S. Steinbach, Christopher J. Duffy, John Nieber, Vipin Kumar |
| 2022 | AAAI | Fairness by "Where": A Statistically-Robust and Model-Agnostic Bi-level Learning Framework. | Yiqun Xie, Erhu He, Xiaowei Jia, Weiye Chen, Sergii Skakun, Han Bao, Zhe Jiang, Rahul Ghosh, Praveen Ravirathinam |
| 2022 | ICDM | STORM-GAN: Spatio-Temporal Meta-GAN for Cross-City Estimation of Human Mobility Responses to COVID-19. | Han Bao, Xun Zhou, Yiqun Xie, Yanhua Li, Xiaowei Jia |
| 2022 | ICDM | Meta-Transfer Learning: An application to Streamflow modeling in River-streams. | Rahul Ghosh, Bangyan Li, Kshitij Tayal, Vipin Kumar, Xiaowei Jia |
| 2022 | IJCAI | Statistically-Guided Deep Network Transformation to Harness Heterogeneity in Space (Extended Abstract). | Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, Praveen Ravirathinam |
| 2022 | KDD | Physics-Guided Graph Meta Learning for Predicting Water Temperature and Streamflow in Stream Networks. | Shengyu Chen, Jacob A. Zwart, Xiaowei Jia |
| 2022 | KDD | Robust Inverse Framework using Knowledge-guided Self-Supervised Learning: An application to Hydrology. | Rahul Ghosh, Arvind Renganathan, Kshitij Tayal, Xiang Li, Ankush Khandelwal, Xiaowei Jia, Christopher J. Duffy, John Nieber, Vipin Kumar |
| 2022 | KDD | Quantifying and Reducing Registration Uncertainty of Spatial Vector Labels on Earth Imagery. | Wenchong He, Zhe Jiang, Marcus Kriby, Yiqun Xie, Xiaowei Jia, Da Yan, Yang Zhou |
| 2022 | UAI | Physics guided neural networks for spatio-temporal super-resolution of turbulent flows. | Tianshu Bao, Shengyu Chen, Taylor T. Johnson, Peyman Givi, Shervin Sammak, Xiaowei Jia |
| 2022 | SDM | Modeling Reservoir Release Using Pseudo-Prospective Learning and Physical Simulations to Predict Water Temperature. | Xiaowei Jia, Shengyu Chen, Yiqun Xie, Haoyu Yang, Alison P. Appling, Samantha Oliver, Zhe Jiang |
| 2022 | SDM | Invertibility aware Integration of Static and Time-series data: An application to Lake Temperature Modeling. | Kshitij Tayal, Xiaowei Jia, Rahul Ghosh, Jared Willard, Jordan S. Read, Vipin Kumar |
| 2021 | ICDCS | Heterogeneous Spatio-Temporal Graph Convolution Network for Traffic Forecasting with Missing Values. | Weida Zhong, Qiuling Suo, Xiaowei Jia, Aidong Zhang, Lu Su |
| 2021 | ICDM | Partial Differential Equation Driven Dynamic Graph Networks for Predicting Stream Water Temperature. | Tianshu Bao, Xiaowei Jia, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Taylor T. Johnson |
| 2021 | ICDM | Heterogeneous Stream-reservoir Graph Networks with Data Assimilation. | Shengyu Chen, Alison P. Appling, Samantha Oliver, Hayley Corson-Dosch, Jordan S. Read, Jeffrey M. Sadler, Jacob Zwart, Xiaowei Jia |
| 2021 | ICDM | Physics-Guided Machine Learning from Simulation Data: An Application in Modeling Lake and River Systems. | Xiaowei Jia, Yiqun Xie, Sheng Li, Shengyu Chen, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Jordan S. Read |
| 2021 | ICDM | A Statistically-Guided Deep Network Transformation and Moderation Framework for Data with Spatial Heterogeneity. | Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, Praveen Ravirathinam |
| 2021 | SDM | Graph-based Reinforcement Learning for Active Learning in Real Time: An Application in Modeling River Networks. | Xiaowei Jia, Beiyu Lin, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Jordan S. Read |
| 2021 | SDM | Physics-Guided Recurrent Graph Model for Predicting Flow and Temperature in River Networks. | Xiaowei Jia, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Steven Markstrom, Jared Willard, Shaoming Xu, Michael S. Steinbach, Jordan S. Read, Vipin Kumar |
| 2020 | COLING | Regularized Graph Convolutional Networks for Short Text Classification. | Kshitij Tayal, Nikhil Rao, Saurabh Agarwal, Xiaowei Jia, Karthik Subbian, Vipin Kumar |
| 2020 | IGARSS | Process Guided Deep Learning for Modeling Physical Systems: An Application in Lake Temperature Modeling. | Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob A. Zwart, Michael S. Steinbach, Vipin Kumar |
| 2020 | KDD | Personalized Image Retrieval with Sparse Graph Representation Learning. | Xiaowei Jia, Handong Zhao, Zhe Lin, Ajinkya Kale, Vipin Kumar |
| 2020 | KDD | Learning with Small Data. | Huaxiu Yao, Xiaowei Jia, Vipin Kumar, Zhenhui Li |
| 2020 | SDM | Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data. | Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia, Varun Mithal, Vipin Kumar |
| 2019 | IJCAI | Recurrent Generative Networks for Multi-Resolution Satellite Data: An Application in Cropland Monitoring. | Xiaowei Jia, Mengdie Wang, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar |
| 2019 | KDD | Towards Robust and Discriminative Sequential Data Learning: When and How to Perform Adversarial Training? | Xiaowei Jia, Sheng Li, Handong Zhao, Sungchul Kim, Vipin Kumar |
| 2019 | SDM | Spatial Context-Aware Networks for Mining Temporal Discriminative Period in Land Cover Detection. | Xiaowei Jia, Sheng Li, Ankush Khandelwal, Guruprasad Nayak, Anuj Karpatne, Vipin Kumar |
| 2019 | SDM | Classifying Heterogeneous Sequential Data by Cyclic Domain Adaptation: An Application in Land Cover Detection. | Xiaowei Jia, Guruprasad Nayak, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar |
| 2019 | SDM | Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles. | Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob Zwart, Michael S. Steinbach, Vipin Kumar |
| 2018 | SDM | Classifying Multivariate Time Series by Learning Sequence-level Discriminative Patterns. | Guruprasad Nayak, Varun Mithal, Xiaowei Jia, Vipin Kumar |
| 2017 | KDD | Incremental Dual-memory LSTM in Land Cover Prediction. | Xiaowei Jia, Ankush Khandelwal, Guruprasad Nayak, James Gerber, Kimberly Carlson, Paul C. West, Vipin Kumar |
| 2017 | SDM | Predict Land Covers with Transition Modeling and Incremental Learning. | Xiaowei Jia, Ankush Khandelwal, Guruprasad Nayak, James Gerber, Kimberly Carlson, Paul C. West, Vipin Kumar |
| 2015 | ICDM | DRN: Bringing Greedy Layer-Wise Training into Time Dimension. | Xiaoyi Li, Xiaowei Jia, Hui Li, Houping Xiao, Jing Gao, Aidong Zhang |
| 2014 | BIBE | A Novel Semi-Supervised Deep Learning Framework for Affective State Recognition on EEG Signals. | Xiaowei Jia, Kang Li, Xiaoyi Li, Aidong Zhang |
| 2014 | CIKM | Analysis on Community Variational Trend in Dynamic Networks. | Xiaowei Jia, Nan Du, Jing Gao, Aidong Zhang |
| 2013 | GLOBECOM | Towards efficient vacant taxis Cruising Guidance. | Yunfei Hou, Xu Li, Yunjie Zhao, Xiaowei Jia, Adel W. Sadek, Kevin F. Hulme, Chunming Qiao |