| 2026 | ACL | ReviewGrounder: Improving Review Substantiveness with Rubric-Guided, Tool-Integrated Agents. | Zhuofeng Li, Yi Lu, Dongfu Jiang, Haoxiang Zhang, Yuyang Bai, Chuan Li, Yu Wang, Shuiwang Ji, Jianwen Xie, Yu Zhang |
| 2025 | ACL | Reasoning with Graphs: Structuring Implicit Knowledge to Enhance LLMs Reasoning. | Haoyu Han, Yaochen Xie, Hui Liu, Xianfeng Tang, Sreyashi Nag, William Headden, Yang Li, Chen Luo, Shuiwang Ji, Qi He, Jiliang Tang |
| 2025 | ACL | EcomScriptBench: A Multi-task Benchmark for E-commerce Script Planning via Step-wise Intention-Driven Product Association. | Weiqi Wang, Limeng Cui, Xin Liu, Sreyashi Nag, Wenju Xu, Chen Luo, Sheikh Muhammad Sarwar, Yang Li, Hansu Gu, Hui Liu, Changlong Yu, Jiaxin Bai, Yifan Gao, Haiyang Zhang, Qi He, Shuiwang Ji, Yangqiu Song |
| 2025 | ICLR | Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models. | Cong Fu, Xiner Li, Blake Olson, Heng Ji, Shuiwang Ji |
| 2025 | ICLR | Learning to Discover Regulatory Elements for Gene Expression Prediction. | Xingyu Su, Haiyang Yu, Degui Zhi, Shuiwang Ji |
| 2025 | ICLR | Eliminating Position Bias of Language Models: A Mechanistic Approach. | Ziqi Wang, Hanlin Zhang, Xiner Li, Kuan-Hao Huang, Chi Han, Shuiwang Ji, Sham M. Kakade, Hao Peng, Heng Ji |
| 2025 | ICML | DiffMS: Diffusion Generation of Molecules Conditioned on Mass Spectra. | Montgomery Bohde, Mrunali Manjrekar, Runzhong Wang, Shuiwang Ji, Connor W. Coley |
| 2025 | ICML | Discovering Physics Laws of Dynamical Systems via Invariant Function Learning. | Shurui Gui, Xiner Li, Shuiwang Ji |
| 2025 | ICML | On Explaining Equivariant Graph Networks via Improved Relevance Propagation. | Hongyi Ling, Haiyang Yu, Zhimeng Jiang, Na Zou, Shuiwang Ji |
| 2025 | ICML | Geometry Informed Tokenization of Molecules for Language Model Generation. | Xiner Li, Limei Wang, Youzhi Luo, Carl Edwards, Shurui Gui, Yuchao Lin, Heng Ji, Shuiwang Ji |
| 2025 | ICML | Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design. | Masatoshi Uehara, Xingyu Su, Yulai Zhao, Xiner Li, Aviv Regev, Shuiwang Ji, Sergey Levine, Tommaso Biancalani |
| 2024 | EMNLP | A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery. | Yu Zhang, Xiusi Chen, Bowen Jin, Sheng Wang, Shuiwang Ji, Wei Wang, Jiawei Han |
| 2024 | ICLR | On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods. | Montgomery Bohde, Meng Liu, Alexandra Saxton, Shuiwang Ji |
| 2024 | ICLR | Active Test-Time Adaptation: Theoretical Analyses and An Algorithm. | Shurui Gui, Xiner Li, Shuiwang Ji |
| 2024 | ICLR | Complete and Efficient Graph Transformers for Crystal Material Property Prediction. | Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji |
| 2024 | ICLR | SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations. | Xuan Zhang, Jacob Helwig, Yuchao Lin, Yaochen Xie, Cong Fu, Stephan Wojtowytsch, Shuiwang Ji |
| 2024 | ICML | Position: TrustLLM: Trustworthiness in Large Language Models. | Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao |
| 2024 | ICML | Graph Structure Extrapolation for Out-of-Distribution Generalization. | Xiner Li, Shurui Gui, Youzhi Luo, Shuiwang Ji |
| 2024 | ICML | Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency. | Yuchao Lin, Jacob Helwig, Shurui Gui, Shuiwang Ji |
| 2024 | ICML | A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction. | Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji |
| 2024 | SDM | Lattice Convolutional Networks for Learning Ground States of Quantum Many-Body Systems. | Cong Fu, Xuan Zhang, Huixin Zhang, Hongyi Ling, Shenglong Xu, Shuiwang Ji |
| 2024 | SDM | 3D Molecular Geometry Analysis with 2D Graphs. | Zhao Xu, Yaochen Xie, Youzhi Luo, Xuan Zhang, Xinyi Xu, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji |
| 2023 | ICLR | Learning Fair Graph Representations via Automated Data Augmentations. | Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou |
| 2023 | ICLR | Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models. | Meng Liu, Haoran Liu, Shuiwang Ji |
| 2023 | ICLR | Automated Data Augmentations for Graph Classification. | Youzhi Luo, Michael McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji |
| 2023 | ICLR | Learning Hierarchical Protein Representations via Complete 3D Graph Networks. | Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji |
| 2023 | ICML | Group Equivariant Fourier Neural Operators for Partial Differential Equations. | Jacob Helwig, Xuan Zhang, Cong Fu, Jerry Kurtin, Stephan Wojtowytsch, Shuiwang Ji |
| 2023 | ICML | Graph Mixup with Soft Alignments. | Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou |
| 2023 | ICML | Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction. | Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji |
| 2023 | ICML | Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. | Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji |
| 2023 | KDD | Graph and Geometry Generative Modeling for Drug Discovery. | Minkai Xu, Meng Liu, Wengong Jin, Shuiwang Ji, Jure Leskovec, Stefano Ermon |
| 2022 | ICLR | Spherical Message Passing for 3D Molecular Graphs. | Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, Shuiwang Ji |
| 2022 | ICLR | An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch. | Youzhi Luo, Shuiwang Ji |
| 2022 | ICML | Generating 3D Molecules for Target Protein Binding. | Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, Shuiwang Ji |
| 2022 | ICML | Self-Supervised Representation Learning via Latent Graph Prediction. | Yaochen Xie, Zhao Xu, Shuiwang Ji |
| 2022 | ICML | GraphFM: Improving Large-Scale GNN Training via Feature Momentum. | Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji |
| 2022 | KDD | Frontiers of Graph Neural Networks with DIG. | Shuiwang Ji, Meng Liu, Yi Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Zhao Xu, Haiyang Yu |
| 2022 | KDD | Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions. | Rui Yang, Jie Wang, Zijie Geng, Mingxuan Ye, Shuiwang Ji, Bin Li, Feng Wu |
| 2022 | SDM | Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences. | Meng Liu, Shuiwang Ji |
| 2021 | AMIA | Graph Based Machine Learning for Healthcare: State of the Art, Challenges, and Opportunities. | Yuan Luo, Fei Wang, Marinka Zitnik, Shuiwang Ji |
| 2021 | CIKM | AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter. | Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, Jundong Li |
| 2021 | ICML | GraphDF: A Discrete Flow Model for Molecular Graph Generation. | Youzhi Luo, Keqiang Yan, Shuiwang Ji |
| 2021 | ICML | On Explainability of Graph Neural Networks via Subgraph Explorations. | Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji |
| 2021 | ICWSM | Machine Learning Explanations to Prevent Overtrust in Fake News Detection. | Sina Mohseni, Fan Yang, Shiva K. Pentyala, Mengnan Du, Yi Liu, Nic Lupfer, Xia Hu, Shuiwang Ji, Eric D. Ragan |
| 2020 | AAAI | A Multi-Scale Approach for Graph Link Prediction. | Lei Cai, Shuiwang Ji |
| 2020 | AAAI | Adaptive Convolutional ReLUs. | Hongyang Gao, Lei Cai, Shuiwang Ji |
| 2020 | AAAI | Non-Local U-Nets for Biomedical Image Segmentation. | Zhengyang Wang, Na Zou, Dinggang Shen, Shuiwang Ji |
| 2020 | ICDM | Context-aware Deep Representation Learning for Geo-spatiotemporal Analysis. | Hanzi Mao, Xi Liu, Nick Duffield, Hao Yuan, Shuiwang Ji, Binayak P. Mohanty |
| 2020 | ICDM | CorDEL: A Contrastive Deep Learning Approach for Entity Linkage. | Zhengyang Wang, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Shuiwang Ji |
| 2020 | ICLR | StructPool: Structured Graph Pooling via Conditional Random Fields. | Hao Yuan, Shuiwang Ji |
| 2020 | KDD | Kronecker Attention Networks. | Hongyang Gao, Zhengyang Wang, Shuiwang Ji |
| 2020 | KDD | Towards Deeper Graph Neural Networks. | Meng Liu, Hongyang Gao, Shuiwang Ji |
| 2020 | KDD | Deep Learning of High-Order Interactions for Protein Interface Prediction. | Yi Liu, Hao Yuan, Lei Cai, Shuiwang Ji |
| 2020 | KDD | XGNN: Towards Model-Level Explanations of Graph Neural Networks. | Hao Yuan, Jiliang Tang, Xia Hu, Shuiwang Ji |
| 2020 | SDM | Deep Neural Networks with Knowledge Instillation. | Fan Yang, Ninghao Liu, Mengnan Du, Kaixiong Zhou, Shuiwang Ji, Xia Hu |
| 2019 | AAAI | Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods. | Hao Yuan, Yongjun Chen, Xia Hu, Shuiwang Ji |
| 2019 | ICDM | An Efficient Policy Gradient Method for Conditional Dialogue Generation. | Lei Cai, Shuiwang Ji |
| 2019 | ICDM | Learning Local and Global Multi-context Representations for Document Classification. | Yi Liu, Hao Yuan, Shuiwang Ji |
| 2019 | ICDM | Learning Hierarchical and Shared Features for Improving 3D Neuron Reconstruction. | Hao Yuan, Na Zou, Shaoting Zhang, Hanchuan Peng, Shuiwang Ji |
| 2019 | ICML | Graph U-Nets. | Hongyang Gao, Shuiwang Ji |
| 2019 | IJCAI | Dense Transformer Networks for Brain Electron Microscopy Image Segmentation. | Jun Li, Yongjun Chen, Lei Cai, Ian Davidson, Shuiwang Ji |
| 2019 | KDD | Graph Representation Learning via Hard and Channel-Wise Attention Networks. | Hongyang Gao, Shuiwang Ji |
| 2019 | PAKDD | An Interpretable Neural Model with Interactive Stepwise Influence. | Yin Zhang, Ninghao Liu, Shuiwang Ji, James Caverlee, Xia Hu |
| 2019 | WWW | On Attribution of Recurrent Neural Network Predictions via Additive Decomposition. | Mengnan Du, Ninghao Liu, Fan Yang, Shuiwang Ji, Xia Hu |
| 2019 | WWW | Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations. | Hongyang Gao, Yongjun Chen, Shuiwang Ji |
| 2019 | WWW | XFake: Explainable Fake News Detector with Visualizations. | Fan Yang, Shiva K. Pentyala, Sina Mohseni, Mengnan Du, Hao Yuan, Rhema Linder, Eric D. Ragan, Shuiwang Ji, Xia (Ben) Hu |
| 2019 | SDM | Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation. | Lei Cai, Hongyang Gao, Shuiwang Ji |
| 2019 | SDM | Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions. | Zhengyang Wang, Hao Yuan, Shuiwang Ji |
| 2018 | KDD | Deep Adversarial Learning for Multi-Modality Missing Data Completion. | Lei Cai, Zhengyang Wang, Hongyang Gao, Dinggang Shen, Shuiwang Ji |
| 2018 | KDD | Voxel Deconvolutional Networks for 3D Brain Image Labeling. | Yongjun Chen, Hongyang Gao, Lei Cai, Min Shi, Dinggang Shen, Shuiwang Ji |
| 2018 | KDD | Large-Scale Learnable Graph Convolutional Networks. | Hongyang Gao, Zhengyang Wang, Shuiwang Ji |
| 2018 | KDD | Smoothed Dilated Convolutions for Improved Dense Prediction. | Zhengyang Wang, Shuiwang Ji |
| 2018 | SDM | Learning Convolutional Text Representations for Visual Question Answering. | Zhengyang Wang, Shuiwang Ji |
| 2017 | CIKM | IDM 2017: Workshop on Interpretable Data Mining - Bridging the Gap between Shallow and Deep Models. | Xia Hu, Shuiwang Ji |
| 2017 | ICDM | A Deep Transfer Learning Approach for Improved Post-Traumatic Stress Disorder Diagnosis. | Debrup Banerjee, Kazi Aminul Islam, Gang Mei, Lemin Xiao, Guangfan Zhang, Roger Xu, Shuiwang Ji, Jiang Li |
| 2017 | ICDM | Efficient and Invariant Convolutional Neural Networks for Dense Prediction. | Hongyang Gao, Shuiwang Ji |
| 2017 | ICDM | Recurrent Encoder-Decoder Networks for Time-Varying Dense Prediction. | Tao Zeng, Bian Wu, Jiayu Zhou, Ian Davidson, Shuiwang Ji |
| 2017 | KDD | Multi-Modality Disease Modeling via Collective Deep Matrix Factorization. | Qi Wang, Mengying Sun, Liang Zhan, Paul Thompson, Shuiwang Ji, Jiayu Zhou |
| 2016 | KDD | Multi-Task Feature Interaction Learning. | Kaixiang Lin, Jianpeng Xu, Inci M. Baytas, Shuiwang Ji, Jiayu Zhou |
| 2016 | KDD | Parallel Lasso Screening for Big Data Optimization. | Qingyang Li, Shuang Qiu, Shuiwang Ji, Paul M. Thompson, Jieping Ye, Jie Wang |
| 2016 | KDD | Collaborative Multi-View Denoising. | Lei Zhang, Shupeng Wang, Xiaoyu Zhang, Yong Wang, Binbin Li, Dinggang Shen, Shuiwang Ji |
| 2015 | ICDM | Deep Convolutional Neural Networks for Multi-instance Multi-task Learning. | Tao Zeng, Shuiwang Ji |
| 2015 | KDD | Structural Graphical Lasso for Learning Mouse Brain Connectivity. | Sen Yang, Qian Sun, Shuiwang Ji, Peter Wonka, Ian Davidson, Jieping Ye |
| 2015 | KDD | Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis. | Wenlu Zhang, Rongjian Li, Tao Zeng, Qian Sun, Sudhir Kumar, Jieping Ye, Shuiwang Ji |
| 2015 | PSB | Automated Gene Expression Pattern Annotation in the Mouse Brain. | Tao Yang, Xinlin Zhao, Binbin Lin, Tao Zeng, Shuiwang Ji, Jieping Ye |
| 2014 | MICCAI | Robust Deep Learning for Improved Classification of AD/MCI Patients. | Feng Li, Loc Tran, Kim-Han Thung, Shuiwang Ji, Dinggang Shen, Jiang Li |
| 2014 | MICCAI | Deep Learning Based Imaging Data Completion for Improved Brain Disease Diagnosis. | Rongjian Li, Wenlu Zhang, Heung-Il Suk, Li Wang, Jiang Li, Dinggang Shen, Shuiwang Ji |
| 2013 | SDM | Evolutionary Soft Co-Clustering. | Shuiwang Ji, Wenlu Zhang, Rui Zhang |
| 2012 | KDD | A sparsity-inducing formulation for evolutionary co-clustering. | Shuiwang Ji, Wenlu Zhang, Jun Liu |
| 2010 | ICML | 3D Convolutional Neural Networks for Human Action Recognition. | Shuiwang Ji, Wei Xu, Ming Yang, Kai Yu |
| 2009 | ICML | An accelerated gradient method for trace norm minimization. | Shuiwang Ji, Jieping Ye |
| 2009 | ICML | A least squares formulation for a class of generalized eigenvalue problems in machine learning. | Liang Sun, Shuiwang Ji, Jieping Ye |
| 2009 | IJCAI | Linear Dimensionality Reduction for Multi-label Classification. | Shuiwang Ji, Jieping Ye |
| 2009 | IJCAI | DrosophilaGene Expression Pattern Annotation through Multi-Instance Multi-Label Learning. | Ying-Xin Li, Shuiwang Ji, Sudhir Kumar, Jieping Ye, Zhi-Hua Zhou |
| 2009 | IJCAI | On the Equivalence between Canonical Correlation Analysis and Orthonormalized Partial Least Squares. | Liang Sun, Shuiwang Ji, Shipeng Yu, Jieping Ye |
| 2009 | KDD | Drosophila gene expression pattern annotation using sparse features and term-term interactions. | Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, Sudhir Kumar, Jieping Ye |
| 2009 | KDD | Mining discrete patterns via binary matrix factorization. | Bao-Hong Shen, Shuiwang Ji, Jieping Ye |
| 2009 | UAI | Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization. | Jun Liu, Shuiwang Ji, Jieping Ye |
| 2008 | CVPR | A unified framework for generalized Linear Discriminant Analysis. | Shuiwang Ji, Jieping Ye |
| 2008 | ICML | A least squares formulation for canonical correlation analysis. | Liang Sun, Shuiwang Ji, Jieping Ye |
| 2008 | KDD | Learning subspace kernels for classification. | Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Mingrui Wu, Jieping Ye |
| 2008 | KDD | Extracting shared subspace for multi-label classification. | Shuiwang Ji, Lei Tang, Shipeng Yu, Jieping Ye |
| 2008 | KDD | Hypergraph spectral learning for multi-label classification. | Liang Sun, Shuiwang Ji, Jieping Ye |
| 2007 | ICML | Discriminant kernel and regularization parameter learning via semidefinite programming. | Jieping Ye, Jianhui Chen, Shuiwang Ji |
| 2007 | KDD | Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming. | Jieping Ye, Shuiwang Ji, Jianhui Chen |