J. Chen*, J. Zhang*, D. Peng*, Yu. Song*, A. Ruan, Y. Li, D. Li, Large-scale spatial variable gene atlas for spatial transcriptomics, arXiv: 2510.07653, 2025.
S. Hawke*, E. Zhang*, J. Chen*, D. Li, Contrastive Dimension Reduction: A Systematic Review, arXiv: 2510.11847, 2025.
H. Niu, J. Bryan, X. Li, D. Li, Incorporating LLM Embeddings for Variation Across the Human Genome, arXiv: 2509.20702, 2025.
J. Chen, A. Halder, Y. Li, S. Banerjee, D. Li, The Nearest-Neighbor Derivative Process: Modeling Spatial Rates of Change in Massive Datasets, arXiv: 2509.02752, 2025.
E. Zhang, M, Love, D. Li, Contrastive CUR: Interpretable Joint Feature and Sample Selection for Case-Control Studies, arXiv: 2508.11557, 2025
S. Yang, C. Chen, D. Li, Lower Ricci Curvature for Hypergraphs, arXiv: 2506.03943, 2025
J. Bryan, H. Niu, D. Li, Incorporating LLM-Derived Information into Hypothesis Testing for Genomics Applications, bioRxiv, 2025.
M. Jetsupphasuk, D. Li, M. Hudgens, Estimating causal effects using difference-in-differences under network dependency and interference, arXiv: 2502.03414, 2025.
A. Halder, D. Li, S. Banerjee, Bayesian Spatiotemporal Wombling, arXiv:2407.17804, 2024.
J. Chen, C. Xiong, Q. Sun, Y. Song, G. Wang, G. Gupta, A. Halder, Y. Li, D. Li, Investigating spatial dynamics in spatial omics data with StarTrail, bioRxiv:, 2024.
J. Bryan, H. Zhou, D. Li, Subscedastic weighted least squares estimates, arXiv: 2404.00753, 2024.
T. Wang, Y. Huang, D. Li, From the Greene--Wu Convolution to Gradient Estimation over Riemannian Manifolds, arXiv:2108.07406, 2021.
K. Wang, H. Niu, Y, Wang, D. Li, Deep Generative Models: Complexity, Dimensionality, and Approximation, JMLR , 2025.
B. Su, J. Zhang, N. Collina, Y. Yan, D. Li, K. Cho, J. Fan, A. Roth, W. Su, Analysis of the ICML 2023 Ranking Data: Can Authors' Opinions of Their Own Papers Assist Peer Review in Machine Learning? JASA (Discussion Paper), 2025.
Y. Park, D. Li, Lower Ricci curvature for efficient community detection, TMLR, 2025.
D. Li, A. Jones, S. Banerjee, B. Engelhardt, Bayesian Multi-Group Gaussian Process Models for Heterogeneous Group-Structured Data, JMLR, 2025.
A. Qaqish, D. Li, Identifiability for Gaussian Processes with Holomorphic Kernels, ICLR, 2025.
E. Zhang, D. Li, Contrastive functional principal component analysis, AAAI, 2025.
B. Zhang. S. Nyquist, A. Jones, BE. Engelhardt, D. Li, Contrastive linear regression, AoAS, 2025.
W. Mu*, J. Chen*, E. Davis, K. Reed, D. Phanstiel, MI. Love, D. Li, Gaussian process for time series with lead-lag effects with applications to biology data, Biometrics, 2025.
S. Hawke, Y. Ma, H. Luo, D. Li, Contrastive inverse regression for dimension reduction, NEJSDS, 2025.
A. Mandyam, D. Li, A. Jones, D. Cai, BE. Engelhardt, KD-BIRL: Kernel Density Bayesian Inverse Reinforcement Learning, TMLR, 2024.
J. Chen, M. Zhou, W. Wu, J. Zhang, Y. Li, D. Li, STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics, NeurIPS (DB), 2024.
202,000+ downloads as of Nov 5, 2025.
S. Hawke, Y. Ma, D. Li, Contrastive dimension reduction: When and how? NeurIPS, 2024.
H. Niu, M. Troester, D. Li, Spatial Clustering for Carolina Breast Cancer Study, PSB, 2024.
J. Bryan, D. Li, Comments on Contemporary Uses of Machine Learning for Electronic Health Records, NC Medical Journal, 2024.
H. Luo, J. Purvis, D. Li, Spherical Rotation Dimension Reduction with Geometric Loss Functions, JMLR, 2024.
A. Jones*, D. Cai*, D. Li, BE. Engelhardt, Optimizing the design of spatial genomic studies, Nature Communication, 2024.
D. Li*, A. Jones*, B. Engelhardt, Probabilistic Contrastive Principal Component Analysis, AoAS, 2024.
D. Li*, P. Nguyen*, Z. Zhang, DB. Dunson, Tree Representations of Brain Structural Connectivity via Persistent Homology, Frontiers in Neuroscience, 2023.
J. Chen, W. Mu, Y. Li, D. Li, On the Identifiability and Interpretability of Gaussian Process Models, NeurIPS, 2023.
D. Li, W. Tang, S. Banerjee, Inference for Gaussian processes with Matérn covariogram on compact Riemannian manifolds , JMLR, 2023.
A. Jones, FW. Townes, D. Li, BE. Engelhardt, Alignment of spatial genomics and histology data using deep Gaussian processes, Nature Methods, 2023.
E. Chevalier, D. Li, Y. Lu, DB. Dunson, Exponential-Wrapped Distributions on Symmetric Spaces, SIAM Journal on Mathematics of Data Science, 2022.
D. Li, M. Mukhopadhyay, DB. Dunson, Efficient manifold approximation with spherelets, JRSSB, 2022.
A. Jones, FW. Townes, D. Li, BE. Engelhardt, Contrastive latent variable modeling with application to case-control sequencing experiments , AoAS 2022.
D. Li, DB. Dunson, Classification via local manifold approximation, Biometrika, 2020.
M. Mukhopadhyay*, D. Li*, DB. Dunson, Estimating Densities with Non-Linear Support by Using Fisher–Gaussian Kernels, JRSSB 2020.
Li Lab members
* Equally contributing authors.