selected publications academic article Laha, N., & Mukherjee, R. (2023). On Support Recovery With Sparse CCA: Information Theoretic and Computational Limits. IEEE TRANSACTIONS ON INFORMATION THEORY. 69(3), 1695-1738. Laha, N., Moodie, Z., Huang, Y., & Luedtke, A. (2022). Improved inference for vaccine-induced immune responses via shape-constrained methods. Electronic Journal of Statistics. 16(2), 5852-5933. Laha, N., Miao, Z., & Wellner, J. A. (2021). Bi-s*-Concave Distributions. Journal of Statistical Planning and Inference. 215, 127-157. Hahn, G., Lutz, S. M., Laha, N., Cho, M. H., Silverman, E. K., & Lange, C. (2021). A fast and efficient smoothing approach to Lasso regression and an application in statistical genetics: polygenic risk scores for chronic obstructive pulmonary disease (COPD). Statistics and Computing. 31(3), 35. Laha, N. (2021). Adaptive estimation in symmetric location model under log-concavity constraint. Electronic Journal of Statistics. 15(1), conference paper Burkholz, R., Laha, N., Mukherjee, R., & Gotovos, A. (2021). On the Existence of Universal Lottery Tickets institutional repository document Koner, S., De Sarkar, N., & Laha, N. (2024). False discovery rate control: Moving beyond the BenjaminiHochberg method Koner, S., De Sarkar, N., & Laha, N. (2023). Discovery of new deregulated miRNAs in gingivo buccal carcinoma using Group Benjamini Hochberg method: a commentary on A quest for miRNA bio-marker: a track back approach from gingivo buccal cancer to two different types of precancers Laha, N., Sonabend-W, A., Mukherjee, R., & Cai, T. (2021). Finding the Optimal Dynamic Treatment Regime Using Smooth Fisher Consistent Surrogate Loss Laha, N., Huey, N., Coull, B., & Mukherjee, R. (2021). On Statistical Inference with High Dimensional Sparse CCA Sonabend-W, A., Laha, N., Ananthakrishnan, A. N., Cai, T., & Mukherjee, R. (2020). Semi-Supervised Off Policy Reinforcement Learning Hahn, G., Lutz, S. M., Laha, N., & Lange, C. (2020). A framework to efficiently smooth L1 penalties for linear regression Laha, N., Miao, Z., & Wellner, J. A. (2020). Bi-$s^*$-Concave Distributions Hahn, G., Lutz, S. M., Laha, N., Cho, M. H., Silverman, E. K., & Lange, C. (2020). A fast and efficient smoothing approach to Lasso regression and an application in statistical genetics: polygenic risk scores for chronic obstructive pulmonary disease (COPD) Huey, N., Dutta, D., & Laha, N. De-biased sparse canonical correlation for identifying cancer-related trans-regulated genes software Laha, N. R-Package: SDNNtests Laha, N. R-Package: Support.CCA Laha, N. R-Package: de.bias.CCA Laha, N. R-Package: log.location thesis Laha, N., Huey, N., Coull, B., & Mukherjee, R. (2023). On statistical inference with high-dimensional sparse CCA
teaching activities STAT408 Intro To Linear Models Instructor STAT620 Asymptotic Statistics Instructor STAT685 Directed Studies Instructor STAT691 Research Instructor
education and training Ph.D. in Statistics, University of Washington - (Seattle, Washington, United States) 2019 M.S. in Statistics, Indian Statistical Institute - (Kolkata, India) 2014
awards and honors ADVANCE NCFDD Faculty Success Fellow, conferred by Texas A&M University - (College Station, Texas, United States), 2023