My research interests span statistical methodology and machine learning, with an emphasis on developing tools that can be applied across a range of scientific disciplines.
J. Richland, A. Strang. Shared-endpoint correlations and hierarchy in random flows on graphs. Results in Applied Mathematics, 26, 100549. 2025. [DOI]
J. Richland, T. Kiiskinen, W. Wang, S. Lu, B. Narasimhan, T. Hastie, M. Rivas, R. Tibshirani. Univariate-Guided Sparse Regression for Biobank-Scale High-Dimensional Omics Data. arXiv, 2025. [arXiv]
T. Kiiskinen, J. Richland, W. Wang, S. Lu, B. Narasimhan, T. Hastie, M. Rivas, R. Tibshirani. CuGen: A GPU-accelerated framework for large-scale genomics. medRxiv, 2026. [medRxiv]
J. Richland, T. Kiiskinen, W. Wang, S. Lu, B. Narasimhan, T. Hastie, M. Rivas, R. Tibshirani. Univariate-Guided Sparse Regression for Biobank-Scale High-Dimensional Omics Data. European Society of Human Genetics (ESHG), Gothenburg, Sweden. June 2026.