I am an Assistant Professor in Department of Statistics, Oregon State University. Before joining Oregon State University in Spring 2015, I was a post-doctoral research scholar in Department of Statistics, University of California, Berkeley. I am also involved in projects with Life Sciences Division, Lawrence Berkeley National Laboratory. I completed my PhD in Statistics from University of California, Berkeley in 2013 under supervision of Prof. Peter J. Bickel. Before that, I completed B.Stat and M.Stat from Indian Statistical Institute, Kolkata.
PhD in Statistics, University of California at Berkeley, 2013.
M.Stat, Indian Statistical Institute, Kolkata, 2008.
B.Stat, Indian Statistical Institute, Kolkata, 2006.
- Statistics on Graphs and Networks
- Statistical Application in Neuroscience
- Statistical Genetics: Formation and Analysis of Biological Networks
- High-dimensional Structured Density Estimation and Anomaly Detection
- Unsupervised Learning especially Clustering and Manifold Learning
- Application of Statistics in Astronomy and Astrophysics
- Multiple Hypothesis Testing
- Semiparametric and Nonparametric Statistical Techniques and Time-series Analysis
Research AreaData Science
- Bhattacharyya, Sharmodeep; Bickel, Peter J. Subsampling bootstrap of count features of networks. Ann. Statist. 43 (2015), no. 6, 2384–2411.
- Bhattacharyya, Sharmodeep, and Peter J. Bickel. "Spectral Clustering and Block Models: A Review And A New Algorithm." arXiv preprint arXiv:1508.01819 (2015).
- Bhattacharyya, Sharmodeep, and Peter J. Bickel. "Community detection in networks using graph distance." arXiv preprint arXiv:1401.3915 (2014).
- Bhattacharyya, Sharmodeep, and Peter J. Bickel. "Adaptive Estimation in Elliptical Distributions with Extensions to High Dimensions." (2013)
- Bhattacharyya, Sharmodeep, and Peter J. Bickel. "Detecting Number of Clusters by Testing Block Diagonal Behavior of Similarity Matrix." (2011)
- Bhattacharyya, Sharmodeep, et al. "Identification of Outliers Through Clustering and Semi-supervised Learning for All Sky Surveys." Statistical Challenges in Modern Astronomy V. Springer New York, 2012. 483-485.