Publications
My Google Scholar Profile.
(An * indicates a student author whom I mentored in some capacity)
- Lovekar, K.*, Sengupta, S., Paul, S., (2025). Testing for the network small-world property. Electronic Journal of Statistics. 19(1): 1453-1506.
- Nath, S., Warren, K., Paul, S., (2024). Identifying Peer Influence in Therapeutic Communities Adjusting for Latent Homophily. The Annals of Applied Statistics. 19(1): 529-565.
- Paul, S., Chen, Y. (2024+). Orthogonal symmetric non-negative matrix factorization under the stochastic block model. Statistica Sinica (in press).
- Xie, J.*, Jung, K.J., Allen, C., Chang, Y., Paul, S., Li, Z., Ma, Q. and Chung, D., 2024. Analysis of community connectivity in spatial transcriptomics data. Frontiers in Applied Mathematics and Statistics, 10, p.1403901.
- Howard-Varona, C., Lindback, M., Fudyma, J. D., Krongauz, A.*, Solonenko, N., Zayed, A., Andreopoulos, B., Olson, H.M., Kim, Y., Kyle, J.E., Rio, T.J., Adkins, J.N., Tfaily, M.M, Paul, S., Sullivan, M.B., Duhaime, M.B. (2024) Environment-specific virocell metabolic reprogramming. The ISME Journal.
- Paul, S., Milenkovic, O., Chen, Y. (2023). Higher-Order Spectral Clustering under Superimposed Stochastic Block Model. Journal of Machine Learning Research, 24 (320) :1−58.
- Psychometrika. Paul, S., De Boeck, P., (2023). Joint latent space model for social networks with multivariate attributes.
- Soliman, H.*, Zhao, L.*, Huang, Z.*, Paul, S., Xu, K. (2022). The Multivariate Community Hawkes Model for Dependent Relational Events in Continuous-time Networks. International Conference on Machine Learning (ICML 2022).
- Huang, Z.*, Soliman, H.*, Paul, S., Xu, K. (2022). A Mutually Exciting Latent Space Hawkes Process Model for Continuous-time Networks. Conference on Uncertainty in Artificial Intelligence (UAI 2022).
- Paul, S., Chen, Y. (2022). Null models and community detection in multi-layer networks. Sankhya A. Code available here.
- Minich, D., Madden, C., Navarro, M., Glowacki, L.*,… Paul, S., …, Hale V., (2022). Gut microbiota and age shape susceptibility to clostridial enteritis in lorikeets under human care. Animal Microbiome volume 4, Article number: 7.
- Nicol, P. B.*, Coombes, K. R., Deaver, C., Chkrebtii, O. A., Paul, S., Toland, A. E., Asiaee, A. (2021). Oncogenetic Network Estimation with Disjunctive Bayesian Networks: Learning from Unstratified Samples while Preserving Mutual Exclusivity Relations. Computational and Systems Oncology, 1(2), e1027.
- Paul, S., Chen, Y. (2020). Spectral and matrix factorization methods for consistent community detection in multi-layer networks. The Annals of Statistics, 48 (1), 230-250. Code available here. [Additional Supplement]
- Paul, S., Chen, Y. (2020). A random-effects stochastic block model for joint community detection in multiple networks with applications to neuroimaging. The Annals of Applied Statistics, Volume 14, Number 2, pages 993-1029. Code available here.
- Advances in Neural Information Processing Systems (NeurIPS 2020) Code at GitHub. Paul, S., Xu, K. (2020). CHIP: A Hawkes Process Model for Continuous-time Networks with Scalable and Consistent Estimation.
- Howard-Varona, C., Lindback, M., Bastien, G., Solonenko, N., Zayed, A., Jang, H.B., Andreopoulos, B., Brewer, H., Glavina del Rio, T., Adkins, J., Paul, S., Sullivan, M.B., & Duhaime, M. (2020). Phage-specific metabolic reprogramming of virocells. The ISME Journal, 14 (4), 881-895.
- Zimmerman, B.J., Finnegan, M.K., Paul, S., Schmidt, S.A., Tai, Y., Roth, K.A., Chen, Y. and Husain, F.T. (2019). Functional Brain Changes During Mindfulness-Based Cognitive Therapy Associated with Tinnitus Severity. Frontiers in Neuroscience, 13, p.747.
- Paul, S., Chen, Y. (2016). Consistent community detection in multi-relational data with restricted multi-layer stochastic blockmodel. Electronic Journal of Statistics, vol. 10, no. 2, 3807–3870 (Winner of Student Paper Competition for JSM 2015 by ASA’s section on Statistical Learning and Data Mining).
- Paul, S., Basu, A. (2015). On second order efficient robust inference. Computational Statistics and Data Analysis, 88C, 187–207 (Best Student Paper in Theory and Methods Award at the IISA Conference 2013).
- Kiviniemi T.O., Yegutkin G.G., Toikka J.O., Paul S., Aittokallio T., Janatuinen T., Knuuti J., Rönnemaa T., Koskenvuo J.W., Hartiala J.J., Jalkanen S., Raitakari O.T. (2012). Pravastatin-induced improvement in coronary reactivity and circulating ATP and ADP levels in young adults with type 1 diabetes. Frontiers in Physiology, 3, 338.
Preprints and Submitted:
- Wang S.S.*, Powla P., Sweet T., Paul, S., (2023+). The co-varying ties between networks and item responses via latent variables. Major revision from Psychometrika. arXiv.
- Chang, J.H.*, Russo, M., Paul, S., (2024+). Heterogeneous transfer learning for high dimensional regression with feature mismatch. Submitted. Preprint at arXiv
- Chang, J.H.*, Paul, S., (2024+). Embedding Network Autoregression for time series analysis and causal peer effect inference. Submitted. Preprint at arXiv.
- Paul, S., Nath, S., (2023+). Spatial autoregressive model with measurement error in covariates. Submitted. Preprint at arXiv
- Zhao, L.*, Soliman, H.*, Xu, K. S., Paul, S., (2023+). Spectral clustering with dependent excitations for temporal networks. Submitted.
Grants
- OSU Presidential Research Excellence Accelerator Grant (PI) on “Heterogeneous Transfer And Federated Learning For Digital Twin In Unmanned Aerial Vehicles,” 2024-2025.
- OSU College of Arts and Sciences (NMS) Exploration Grant (PI) on “Transfer, Federated, and Private Statistical Learning for Trustworthy AI,” 2024-2025.
- NSF DMS and NGIA joint grant DMS 1830547 (PI) under the program “Algorithms for Threat Detection” for the project on “Spatio-Temporal Data Analysis with Dynamic Network Models,” 2018-2022.
Graduated PhD and MS Students
Kartik Lovekar (PhD, graduates 2024, Data Scientist at Intel)
Lingfei Zhao (PhD, graduated 2022, Research Scientist at Meta)
Prateek Sasan (PhD, co-advised with Vincent Q. Vu, graduated 2022, Data Scientist at JP Morgan and Chase)
Selena Shuo Wang (PhD, co-advised with Paul De Boeck, graduated 2022, Assistant Professor at Indiana University)
Azriel Kronguaz (MS, graduated 2020, Data Analysts at US Department of Homeland Security)