Papers are grouped by publication status. The complete record is also available in my CV.

Manuscripts under review

  1. Zheng, M., Harris, T., & Zhu, S. (2026). Decision-Focused Calibration with Adaptive Conformal Predictive Distributions. ICLR, under review.

  2. Nill, C., Harris, T., & Adams, J. (2026). Manifold Constrained Conformal Prediction for Spatial Events. ICLR, under review. arXiv

  3. Yang, J., Harris, T., Park, C., Lopez, K., Harbison, J., Clifton, M. E., Irwin, P., & Smith, R. (2026). Evaluating the Causal Effect of Transition of Larvicides on Culex Mosquito Abundance in the Chicago Metropolitan Area. American Journal of Epidemiology, under review.

  4. Harris, T., & Liu, Y. (2025). Locally Adaptive Conformal Inference for Operator Models. Transactions on Machine Learning Research, under review. arXiv · Code

  5. Garrett, R., Harris, T., Wang, Z., & Li, B. (2025). Sliced Elastic Distance for Evaluating Amplitude and Phase Differences in Precipitation Models. Technometrics, under review. arXiv

Peer-reviewed and accepted publications

  1. Harris, T. (2026). Flow-Based Conformal Predictive Distributions. NeurIPS, accepted. arXiv · Code

  2. Zhao, S., Kuo, C. L., Lenze, E. J., Wetherell, J. L., Haynes, L., El-Ahmad, P., Fortinsky, R., Kuchel, G., Harris, T., & Diniz, B. S. (2026). A Deep-Learning Based Biomarker of Systemic Cellular Senescence Burden to Predict Mortality and Health Outcomes. Aging Cell, 25(10), e70737. Article

  3. Li, B., & Harris, T. (2026). Statistics for Climate Science: Differentiation and Integration. Annual Review of Statistics and Its Application, 14. Advance online publication. Article

  4. Abdi, A. A., Almeida, R., Harris, T., Magalhaes, T., Juarez, J. G., & Hamer, G. L. (2026). Forgotten in the Tropics: Research on Culex Mosquitoes Is Overshadowed in Malaria and Dengue-Endemic Regions. Parasites & Vectors, 19, 248. Article

  5. Wang, M., Yan, S., Harris, T., Shand, L., & Li, B. (2026). Evaluating the Fingerprint of the Mt. Pinatubo Eruption on Stratospheric Temperatures with Spatial Functional Changepoints. Journal of Agricultural, Biological and Environmental Statistics. Advance online publication.

  6. Abdi, A. A., Juarez, J. G., Harris, T., Magalhaes, T., & Hamer, G. L. (2026). Systematic Review of Aedes aegypti Control Trials Suggests Publication Bias Related to Author Disclosure of Conflicts of Interest. PLOS Neglected Tropical Diseases, 20(1), e0013914. Article

  7. Harris, T., & Sriver, R. (2024). Quantifying Uncertainty in Climate Projections with Conformal Ensembles. Annals of Applied Statistics, accepted. arXiv · Code

  8. Garrett, R., Harris, T., Wang, Z., & Li, B. (2024). Validating Climate Models with Spherical Convolutional Wasserstein Distance. Advances in Neural Information Processing Systems, 37. Spotlight. Paper · Code

  9. Tonks, A., Harris, T., Li, B., Brown, W., & Smith, R. (2024). Forecasting West Nile Virus with Graph Neural Networks: Harnessing Spatial Dependence in Irregularly Sampled Geospatial Data. GeoHealth, 8(7), e2023GH000784. Article

  10. Harris, T., Li, B., & Sriver, R. (2023). Multimodel Ensemble Analysis with Neural Network Gaussian Processes. Annals of Applied Statistics, 17(4), 3403-3425.

  11. Fimbres-Macias, J., Harris, T. A., Hamer, S., & Hamer, G. (2023). Phenology and Environmental Predictors of Triatoma sanguisuga Dispersal in East-Central Texas, United States. Acta Tropica, 240, 106862.

  12. Wang, M., Harris, T., & Li, B. (2023). Asynchronous Changepoint Estimation for Spatially Correlated Functional Time Series. Journal of Agricultural, Biological and Environmental Statistics, 28(1), 157-176.

  13. Carmody, D., Mazzarello, M., Santi, P., Harris, T., Lehmann, S., Abbiasov, T., Dunbar, R., & Ratti, C. (2022). The Effect of Co-Location on Human Communication Networks. Nature Computational Science, 2(8), 494-503.

  14. Harris, T., Li, B., & Tucker, J. D. (2022). Scalable Multiple Changepoint Detection for Functional Data Sequences. Environmetrics, 33(2), e2710.

  15. Harris, T., Li, B., Steiger, N. J., Smerdon, J. E., Narisetty, N., & Tucker, J. D. (2021). Evaluating Proxy Influence in Assimilated Paleoclimate Reconstructions: Testing the Exchangeability of Two Ensembles of Spatial Processes. Journal of the American Statistical Association, 116(535), 1100-1113.

  16. Harris, T., Tucker, J. D., Li, B., & Shand, L. (2021). Elastic Depths for Detecting Shape Anomalies in Functional Data. Technometrics, 63(4), 466-476.

  17. Harris, T., & Li, B. (2014). Kriging. Wiley StatsRef: Statistics Reference Online, 1-11.

Manuscript in preparation

Yan, S., Harris, T., Lall, U., & Li, B. Neural Estimation of Conditional Tail Dependence in Global Precipitation Extremes. To be submitted to the Annals of Applied Statistics.

Workshops and other publications

  1. Zhao, S., & Harris, T. (2026). Latent Dissipative Neural ODEs for Probabilistic Climate Projection. NeurIPS Workshop on Climate Change.

  2. Harris, T. (2026). Discussion of “A Bayesian Mixed Data Denoising Diffusion Probabilistic Model for Synthetic Tabular Data Generation”. ASA Discoveries.

  3. Greiffenstein, E., Harris, T., & Smith, B. (2025). Forecasting West Nile Virus with Deep Graph Encoders. arXiv. Preprint

  4. Ringer, R. J., Yoon, H., Kadeethum, T., & Harris, T. (2022). Machine Learning Applications for Estimation of Greenhouse Gas Emissions Using Multiple Satellite Images (SAND2022-16609C). Sandia National Laboratories.