Bayesian Computation (for example, MCMC, Perfect Simulation).
Applications of Bayesian methodologies to challenging scientific issues, for example, Environment, Palaeoclimatology, Astronomy, Machine Learning, Ecology etc.
Awards and Achievements
Ambarnath-Shantilata Travel Grant of worth £700 from Indian Statistical Institute for attending International Society for Bayesian Analysis (ISBA) World Meetings, Benidorm, Spain, 2010.
Five Year fellowship of National Eligibility Test conducted by Council of Scientific Industrial Research, Govt. of India, 2010.
Prize in On Spot Essay Writing Competition organised by Central Statistical Organisation, Ministry of Statistics and Program Implementation, Govt. of India, 2007.
Swami Lokeswarananda Memorial Award (2003) for allround performance from Ramakrishna Mission Residential College, Narendrapur, 2003.
Mukhopadhyay. S, Bhattacharya. S, Dihidar. K, 2011, On Bayesian “Central Clustering”: Application To Landscape Classification Of Western Ghats, Annals of Applied Statistics, Vol. 5, No. 3, 1948-1977.
Mukhopadhyay. S, Roy. S, Bhattacharya. S, Fast and Efficient Bayesian Semi-Parametric Curve-Fitting and Clustering in Massive Data, 2012, Sankhy ̄a Series B, Vol. 74, Issue 1, 77–106.
Mukhopadhyay. S, Bhattacharya, Perfect Simulation for Mixtures with Known and Unknown Number of Components, 2012, Bayesian Analysis, Vol. 7, No. 3, 675–714.
Mukhopadhyay. S, Bhattacharya. S, Cross-validation based assesment of a new Bayesian paleoclimate model, 2013, Environmetrics, Vol. 24, Issue 8, 550–568.
Lee. D, Mukhopadhyay. S, Rushworth. A, Sahu. S, A Rigorous Statistical Framework for Spatio-temporal Pollution Prediction and Estimation of its Long-term Impact on Health, 2017, Biostatistics, Vol. 18, No. 2, 370–385.
Pannullo. F, Lee. D, Neal. L, Dalvi. M, Agnew. P, O’ Connor. F, Mukhopadhyay. S, Sahu. S and Sarran. C, Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England, 2017, Environmental Health, 16–29, DOI 10.1186/s12940-017-0237-1.
Mukhopadhyay. S, Sahu. S, A Bayesian spatio-temporal model to estimate long term exposure to outdoor air pollution at coarser administrative geographies in England and Wales, 2018, Journal of the Royal Statistical Society, Series A, Vol. 181, Issue 2, 465–486, selected for webinar discussion at Royal Statistical Scoiety on 21st February, 2018.
C, C++, R, Matlab, Minitab.
Operating systems like XP, Vista,Windows–7.
LATEX, BIBTEX, Microsoft Office and common productivity packages in Windows and Linux operating systems.
Presented paper on Bayesian state-space modelling for population dynamics of wildlife and livestock populations at Tanzania Wildlife Research Institute Meeting, Arusha, Tanzania, 2017.
Presented poster on A flexible Bayesian state-space modelling for population dynamics of wildlife and livestock popu- lations 13th World Meeting of International Society for Bayesian Analysis, 2016, Bari, Italy.
Presented paper on Modelling long term effect of air-pollution of UK at Royal Statistical Society Annual Conference, 2014, Sheffield, UK.
Presented paper on Modelling long term effect of air-pollution of England and Wales at 12th World Meeting of Interna- tional Society for Bayesian Analysis, 2014, Cancun, Mexico.
Presented paper on Paleoclimatic reconstruction at 8th International Triennial Calcutta Symposium on Probability and Statistics, 2012, Calcutta, India.
Presented paper on Paleoclimatic reconstruction at 11th International Society for Bayesian Analysis, 2012, Kyoto, Japan.
Presented paper on Bayesian clustering at ISI-ISM-ISSAS Joint Conference, 2012, Tokyo, Japan.
Poster presentation at Valencia 9 conference, 2010, held in Benidorm, Spain, on Bayesian Clustering and Curve-fitting.
Presented paper on Fast and Efficient Bayesian Semi-Parametric Curve-Fitting and Clustering in Massive Data at 7th International Triennial Calcutta Symposium on Probability and Statistics, 2009, Calcutta, India.
Research Fellow, University of Hohenheim, Since 2015.
Research Fellow, University of Southampton, 2013–2015.