My work develops statistically reliable machine learning methods and applies them to climate, environmental, epidemiological, and other complex scientific systems. Links below point to papers or archival records when publicly available.

Preprints and manuscripts under review

  1. Nill, C., Harris, T., & Adams, J. (2026). Manifold Constrained Conformal Prediction for Spatial Events. Preprint. arXiv

  2. Harris, T. (2026). Flow-Based Conformal Predictive Distributions. NeurIPS, in review. arXiv · Code

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

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

  5. Zhao, S., Kuo, C. L., Lenze, E., Wetherell, J., Haynes, L., El-Ahmad, P., Fortinsky, R., Kuchel, G., Harris, T., & Diniz, B. A Deep-Learning Based Biomarker of Systemic Cellular Senescence Burden to Predict Mortality and Health Outcomes. Nature Communications, in review. Preprint

  6. Greiffenstein, E., Harris, T., & Smith, B. (2025). Forecasting West Nile Virus with Deep Graph Encoders. Annals of Applied Statistics, in review. arXiv

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

Peer-reviewed and accepted publications

  1. Li, B., & Harris, T. Statistical Methods in Climate Science. Annual Review of Statistics and Its Application, accepted.

  2. Wang, M., Yan, S., Harris, T., Shand, L., & Li, B. (2025). Evaluating Fingerprint of Mt. Pinatubo Eruption on Stratospheric Temperatures with Spatial Functional Changepoints. Journal of Agricultural, Biological and Environmental Statistics, accepted.

  3. 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

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

  5. 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

  6. 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

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

  8. 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.

  9. 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.

  10. 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.

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

  12. 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.

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

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

Technical report

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.