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Personal profile

Research interests

My core research is at the intersection of statistics, machine learning and optimisation methods. My current research is focussed on modelling data with complex high dimensional network structure and provide methodology for estimating the corresponding structure using tools from nonparametric statistics, graphical models and high dimensional inference. The emphasis is placed on developing new theoretical techniques and computational tools for network problems and applying the corresponding methodology in many fields, including biomedical and social science research, where network modelling and analysis plays an exceedingly important role.

As a mathematical Statistician I am also interested in high dimensional Inference in regression models and understanding the theoretical insights in the modern "big data" framework. The development of novel algorithms  along with concrete theoretical results would enable practitioners to use them in many complex real world problems. I have a recent interest also in different optimization methods and especially understanding distributed/parallel computing with large heterogeneous data. These also include fast choice of tuning parameters in optimization algorithms and their implications in the proposed inference.

Education/Academic qualification

Statistics, Doctor of Science, University of Michigan

Statistics, Master in Science, Indian Statistical Institute, Kolkata

Statistics, Bachelor of Science, University of Calcutta

Fingerprint Dive into the research topics where Sandipan Roy is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Divide-and-conquer Algorithm Mathematics
Likelihood Inference Mathematics
Change Point Mathematics
Gaussian Model Mathematics
Graphical Models Mathematics
State-space Model Mathematics
Bayesian inference Mathematics
Covariates Mathematics

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Projects 2019 2020

Research Output 2012 2019

  • 3 Article
  • 1 Conference contribution
Divide-and-conquer Algorithm
Likelihood Inference
Social Networks
6 Citations (Scopus)
29 Downloads (Pure)

Change-Point Estimation in High-Dimensional Markov Random Field Models

Roy, S., Atchade, Y. & Michailidis, G., 1 Sep 2017, In : Journal of the Royal Statistical Society: Series B - Statistical Methodology. 79, 4, p. 1187 - 1206 20 p.

Research output: Contribution to journalArticle

Open Access
6 Citations (Scopus)
28 Downloads (Pure)

Bayesian Inference in Nonparametric Dynamic State-Space Models

Ghosh, A., Mukhopadhyay, S., Roy, S. & Bhattacharya, S., 1 Nov 2014, In : Statistical Methodology. 21, p. 35 - 48 14 p.

Research output: Contribution to journalArticle

Open Access
State-space Model
Bayesian inference
Random Function
Dynamic Model
Markov Chain Monte Carlo

ISIS and NISIS: New bilingual dual-channel speech corpora for robust speaker recognition

Pal, A., Bose, S., Mitra, M. & Roy, S., 1 Dec 2012, Proceedings of the 2012 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2012: Volume 2. p. 936-939 4 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Identification (control systems)