Dr. Sandipan Roy
Dr. Sandipan Roy

Associate Professor in Statistics

University of Bath

About Me

Sandipan is a Associate Professor of Statistics at the Department of Mathematical Sciences at University of Bath. His research interests include graphical models, Statistical modelling of networks and high dimensional statistical inference. He is a co-director of the Mathematics and Data for Algorithms (MAD) group at Bath which focusses on promoting research lying at the interaction of statistics, machine learning and optimization.

Interests
  • Graphical Models
  • Statistical Modelling of Networks
  • Differential Privacy
  • High Dimensional Estimation and Inference
Education

  • PhD Statistics

    University of Michigan, Ann Arbor, USA

  • Mstat Statistics

    Indian Statistical Institute, West Bengal, India

  • BSc Statistics

    Presidency University (Previously Presidency College), West Bengal, India

Peer Reviewed and Preprints
Robert T Olender, Sandipan Roy, Hamish a Jamieson, Sarah N Hilmer, Prasad S Nishtala (2024). Drug Burden Index is a Modifiable Predictor of 30-Day-Hospitalization in Community-Dwelling Older Adults with Complex Care Needs: Machine Learning Analysis of InterRAI Data. The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences.
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Sandipan Roy (2024). Foundations of Statistics for Data Scientists with R and Python. Oxford University Press UK (book review).
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Tichawona Chinzowu, Te-Yuan Chyou, Sandipan Roy, Hamish Jamieson, Prasad S Nishtala (2023). Antibiotic utilisation and the impact of antimicrobial resistance action plan on prescribing among older adults in New Zealand between 2005 and 2019. medRxiv.
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Robert T Olender, Sandipan Roy, Prasad S Nishtala (2023). Application of machine learning approaches in predicting clinical outcomes in older adults--a systematic review and meta-analysis. BMC geriatrics.
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Thomas E Bartlett, Swati Chandna, Sandipan Roy (2023). Stochastic networks theory to model single-cell genomic count data. arXiv preprint arXiv:2303.02498.
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See all publications
People
Dan Miles (2020-)
Dan Miles (2020-)

Dan is working on developing multiple graphical structure estimation methods for data with network structure and covariates. Dan is based within the SAMBa Centre for Doctoral Training. He is co-supervised by Vangelis Evangelou.

Aug 16, 2024

Jordan Taylor (2019-)
Jordan Taylor (2019-)

Jordan is working on developing machine learning and network methods for high dimensional genetic data. Jordan is based within the SAMBa Centre for Doctoral Training. He is co-supervised by Matt Nunes and Lauren Cowley.

Aug 16, 2024

Josh Inoue (2020-)
Josh Inoue (2020-)

Josh is working on developing novel approaches to problems arising in spatio-temporal modelling. Josh is part of the Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa CDT) and is co-supervised by Matt Nunes.

Aug 16, 2024

Ruchen Liu (2021-)
Ruchen Liu (2021-)

Rucehen is working on developing novel approaches to differential privacy, motivated by problems arising in the healthcare setting. Ruchen is part-funded by the Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa CDT), a University of Bath Global Doctoral Scholarship and Novartis (Basel, Switzerland).

Aug 16, 2024

Xinle Tian (2021-)
Xinle Tian (2021-)

Xinle is working on sparse statistical modelling and inference in high-dimensional situations. The application of interest in the project will be neuroscience, in particular detecting changes in structure in developmental and post-rehabilitation data.

Aug 16, 2024