My interests are in statistical methodology and applications to investigate phenomena on natural events which evolve over space and time. Of particular interest are natural hazards, environmental variables and diseases. The statistical problems are wide rannging and complex. My immediate interests fall into the following categories-

1. Modelling of spatial and temporal stochastic dependence structures.
2. Efficient computation of big spatio-temporal dependence matrices.
3. Applications involving the above.
4. Interface of maximum likelihood and interpretable machine learning algorithms for streaming data.

If you wish to pursue a PhD with me or want to discuss opportunities please contact me with your CV at sourav.das@jcu.edu.au. I am particularly keen to hear from students with background in statistical analysis of time series, applied stochastic process, multivariate statistical methods, mixed effects modelling or spatial statistics.

Teaching

• MA1580: Foundations of Data Science (Level 1; CNS & TSV)
• MA5800: Foundations for Data Science (Level 5; CNS & ONL)
• MA5810: Introduction to Data Mining (Level 5; CNS, ONL & TSV)

Interests

Research

• Algorithms for streaming data monitoring - land displacement, EEG, ECG, Seismic signals. Statistical models for environmental events - floods, precipitation, cyclones. Spatial and environmental epidemiology for mental health and infectious diseases.

Experience

• 2019 to present - Lecturer, Statistics and Data Science, James Cook University (Cairns, Australia)
• 2017 to 2019 - Clinical Biostatistician, Royal Melbourne Hospital/ University of Melbourne (Melbourne, Australia)
• 2015 to 2017 - Post Doctoral Research Associate, University of Bristol (Bristol, UK)
• 2012 to 2015 - Research Fellow, National University of Singapore (Singapore)
• 2007 to 2011 - PhD, University of Manchester (Manchester, UK)

Research Disciplines

• Statistics (4905)

Socio-Economic Objectives

• Specific population health (2005)

These are the most recent publications associated with this author. To see a detailed profile of all publications stored at JCU, visit ResearchOnline@JCU. Hover over Altmetrics badges to see social impact.

Journal Articles

• Das S, Subba Rao S and Yang J (in press) Spectral methods for small sample time series: a complete periodogram approach. Journal of Time Series Analysis, , DOI:10.1111/jtsa.12584.
• Wibawa P, Matta G, Das S, Eratne D, Farrand S, Desmond P, Velakoulis D and Gaillard F (in press) Bringing psychiatrists into the picture: automated measurement of regional MRI brain volume in patients with suspected dementia. Australian and New Zealand Journal of Psychiatry, , DOI:10.1177/0004867421998444.
• Das S, Subba Rao T and Boshnakov G (2020) An asymptotically unbiased weighted least squares estimation criterion for parametric variograms of second order stationary geostatistical processes. Communications in Statistics: simulation and computation, 49 (7), pp. 1839-1854, DOI:10.1080/03610918.2018.1508698.
• Das S and Tordesillas A (2019) Near real-time characterization of spatio-temporal precursory evolution of a rockslide from radar data: integrating statistical and machine learning with dynamics of granular failure. Remote Sensing, 11 (23), Article: 2777, DOI:10.3390/rs11232777.
• Wallbridge P, Parry S, Das S, Law C, Hammerschlag G, Irving L, Hew M and Steinfort D (2018) Parasternal intercostal muscle ultrasound in chronic obstructive pulmonary disease correlates with spirometric severity. Scientific Reports, 8, Article: 15274, DOI:10.1038/s41598-018-33666-7.
• Das S, Cook A, Wah W, Win K, Chee C, Wang Y and Hsu L (2017) Spatial dynamics of TB within a highly urbanised Asian metropolis using point patterns. Scientific Reports, 7, Article: 36, DOI:10.1038/s41598-017-00081-3.
• Das S and Nason G (2016) Measuring the degree of non-stationarity of a time series. Stat, 5 (1), pp. 295-305, DOI:10.1002/sta4.125.
• Rao T, Das S and Boshnakov G (2014) A frequency domain approach for the estimation of parameters of spatio-temporal stationary random processes. Journal of Time Series Analysis, 35 (4), pp. 357-377, DOI:10.1111/jtsa.12069.
• Wah W, Das S, Earnest A, Lim L, Chee C, Cook A, Wang Y, Win K, Ong M and Hsu L (2014) Time series analysis of demographic and temporal trends of tuberculosis in Singapore. BMC Public Health, 14 (1), Article: 1121, DOI:10.1186/1471-2458-14-1121.

Current and recent Research Funding to JCU is shown by funding source and project.

Advisory Accreditation: I can be on your Advisory Panel as a Secondary Advisor.

These Higher Degree Research projects are either current or by students who have completed their studies within the past 5 years at JCU. Linked titles show theses available within ResearchOnline@JCU.

Current

• Using Weather Radars to Inform Data-Driven Irrigation Practices (Masters , Secondary Advisor)

The map shows research collaborations by institution from the past 7 years.
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