Research

Publications 

My Google Scholar Profile.

(An * indicates a graduate student author whom I advised)

  1. 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.
  2. 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.
  3. Wang, S. S.*, Paul, S., De Boeck, P., (2023). Joint latent space model for social networks with multivariate attributes.  Psychometrika.
  4. 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).
  5. 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).
  6. Paul, S., Chen, Y. (2022). Null models and community detection in multi-layer networks.  Sankhya A. Code available here.
  7. 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.
  8. 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.
  9. 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]
  10. 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.
  11. Arastuie, M., Paul, S., Xu, K. (2020). CHIP: A Hawkes Process Model for Continuous-time Networks with Scalable and Consistent Estimation.  Advances in Neural Information Processing Systems (NeurIPS 2020)  Code at GitHub.
  12. 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.
  13. 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.
  14. 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).
  15. 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).
  16. 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:

  1. Nath, S., Paul, S., Warren, K., (2023+). Identifying Peer Influence in Therapeutic Communities. Major Revision from The Annals of Applied Statistics. Preprint at arXiv: 2203.14223. Code is available in Github repository Homophily-Network-Influence. 
  2. Lovekar, K.*, Sengupta, S., Paul, S., (2023+). Testing for the network small-world property. Major Revision from Electronic Journal of Statistics. Preprint at arXiv.
  3. Chang, J.H.*, Paul, S., (2024+). Embedding Network Autoregression for time series analysis and causal peer effect inference. Submitted. Preprint at arXiv.
  4. Paul, S., Nath, S., (2023+). Spatial autoregressive model with measurement error in covariates. Submitted. Preprint at arXiv
  5. Zhao, L.*, Soliman, H., Xu, K. S., Paul, S., (2023+). Spectral clustering with dependent excitations for temporal networks. Submitted.
  6. Wang S.S.*, Powla P., Sweet T., Paul, S., (2023+). The co-varying ties between networks and item responses via latent variables. Submitted. arXiv.
  7. Paul, S., Chen, Y. (2016+). Orthogonal symmetric non-negative matrix factorization under the stochastic block model. Preprint at arXiv:1605.05349. Submitted.

 

 

Grants

My research is supported by NSF-NGIA grant DMS 1830547  under the program “Algorithms for Threat Detection” for the project on “Spatio-Temporal Data Analysis with Dynamic Network Models”.

 

Current PhD Students

Olivia Cleymaet

Kartik Lovekar

Past PhD and MS Students

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, Postdoctoral Scholar at Yale University)

Azriel Kronguaz (MS, graduated 2020, Data Analysts at US Department of Homeland Security)