Shayegani Bruno Family Faculty Fellow
Department of Biological Statistics and Computational Biology
Department of Statistical Science
I am broadly interested in developing statistical machine learning methods for structure learning and prediction of complex, high-dimensional systems arising in biological and social sciences. I am currently working in two areas: (a) network modeling of high-dimensional time series; and (b) detecting high-order interactions in complex biological systems using randomized tree ensembles. I also work closely with scientists and economists on a wide range of problems including prostate cancer progression, large scale metabolomics, and systemic risk monitoring in financial markets.
My research is supported in part by a three-year grant from the National Science Foundation (NSF DMS-1812128).
Before joining Cornell, I was a postdoctoral scholar (2014-2016) in the Department of Statistics, UC Berkeley and the Biosciences Division, Lawrence Berkeley National Laboratory . I received my PhD (2014) from the Department of Statistics, University of Michigan , and my bachelors (2006) and masters (2008) in Statistics from Indian Statistical Institute, Kolkata .
Publications and Preprints
- Hamutal Arbel, Sumanta Basu , William W. Fisher, Ann S. Hammonds, Kenneth H. Wan, Soo Park, Richard Weiszmann, Benjamin W. Booth, Soile V. Keranen, Clara Henriquez, Omid Shams Solari, Peter J. Bickel, Mark D. Biggin, Susan E. Celniker, and James B. Brown (2018). Exploiting regulatory heterogeneity to systematically identify enhancers with high accuracy, Proceedings of the National Academy of Sciences , in press. [ link ]
- Sumanta Basu *, Xianqi Li* and George Michailidis (2018). Low Rank and Structured Modeling of High-dimensional Vector Autoregressions, IEEE Transactions on Signal Processing , in press. [ Arxiv ]
- Kara Karpman and Sumanta Basu (2018). Learning Financial Networks using Quantile Granger Causality. Proceedings of the Fourth International Workshop on Data Science for Macro-Modeling with Financial and Economic Datasets (DSMM 2018) in ACM SIGMOD 2018 . [ link ]
- Sumanta Basu *, Karl Kumbier*, James B. Brown and Bin Yu (2018). iterative Random Forests to discover predictive and stable high-order interactions, Proceedings of the National Academy of Sciences . [ CRAN , github , link , PNAS Commentary ]
- Ines Wilms, Sumanta Basu , Jacob Bien and David S. Matteson (2017). Interpretable Vector AutoRegressions with Exogenous Time Series, NIPS 2017 Workshop on Interpretable Machine Learning Symposium Proceedings . [ link ]
- Sumanta Basu *, William Durren*, Charles R. Evans, Charles F. Burant, George Michailidis and Alla Karnovsky (2017). Sparse network modeling and Metscape-based visualization methods for the analysis of large-scale metabolomics data, Bioinformatics , 33(10): 1545-1553 . [ link , software ]
- Jiahe Lin*, Sumanta Basu *, Moulinath Banerjee and George Michailidis (2016). Penalized Maximum Likelihood Estimation of Multi-layered Gaussian Graphical Models, Journal of Machine Learning Research , 17(146):1-51, 2016 . [ link ].
- Sumanta Basu and George Michailidis (2015). Regularized estimation of sparse high-dimensional time series models. Annals of Statistics , 43(4), 1535-1567. [ link ]
- Sumanta Basu , Ali Shojaie and George Michailidis (2015). Network Granger causality with inherent grouping structure. Journal of Machine Learning Research , 16, 417-453. [ link ]
- Akash K Kaushik, Shaiju K Vareed, Sumanta Basu , Vasanta Putluri, Nagireddy Putluri, Katrin Panzitt, Christine A Brennan, Arul M Chinnaiyan, Ismael A Vergara, Nicholas Erho, Nancy L Weigel, Nicholas Mitsiades, Ali Shojaie, Ganesh Palapattu, George Michailidis and Arun Sreekumar (2014). Metabolomic profiling identifies biochemical pathways associated with castration-resistant prostate cancer. Journal of proteome research , 13(2), 1088-1100. [ link ]
- Ali Shojaie, Sumanta Basu and George Michailidis (2012). Adaptive thresholding for reconstructing regulatory networks from time-course gene expression data. Statistics in Biosciences , 4(1), 66-83. [ link ]
Yiming Sun, Yige Li, Amy Kuceyeski and Sumanta Basu (2018). Large Spectral Density Matrix Estimation by Thresholding. [ Arxiv ]
Karl Kumbier, Sumanta Basu , James B. Brown, Susan Celniker and Bin Yu (2018). Refining interaction search through signed iterative Random Forests. [ Arxiv ]
Liao Zhu, Sumanta Basu , Robert Jarrow and Martin T. Wells (2018). High-dimensional Estimation and Multi-factor Models. [ Arxiv ]
Ines Wilms*, Sumanta Basu *, Jacob Bien and David S. Matteson (2017). Sparse Identification and Estimation of Large-Scale Vector AutoRegressive Moving Averages. [ Arxiv ]
- Sumanta Basu , Sreyoshi Das, George Michailidis and Amiyatosh Purnanandam. A system-wide approach to measure connectivity in the financial sector. [ SSRN ]
[*]: equal contribution
- Spring 2019: BTRY 6520/STSCI 6520 Computationally Intensive Statistical Methods
- Fall 2018: BTRY 6010/ILRST 6100 Statistical Methods I
- Spring 2018: STSCI 7190 Advanced Multivariate Statistics
- Fall 2017: BTRY 6010/ILRST 6100 Statistical Methods I
- Spring 2017: BTRY 6520/STSCI 6520 Computationally Intensive Statistical Methods
1192 Comstock Hall
Ithaca, NY 14853
Phone: (607) 255-9813