SCHOOL OF NATURAL SCIENCES
NATURAL SCIENCES
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Faculty
Department of Mathematics
Suma Ghosh
Assistant Professor,
Department of Mathematics,
School of Natural Sciences
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Education Details
Suma did her M.Sc in Mathematics from University of Burdwan and Ph.D. from University of Calcutta.
Professional Experience
She had Professional experiences as
Research Associate, Mathematics, Indian Institute of Science (June 2008 - Dec 2008)
Postdoctoral fellow, Mathematics and Statistics, York University, Canada (2009 - 2010)
Postdoctoral fellow, Mathematics and Biology, University of Utah, USA (2011 - 2012)
Postdoctoral fellow, Center for Infectious Disease Dynamics, Pennsylvania State University, USA (2013 – June 2015)
Research Interests
Suma’s research interests are focused at the interface between Mathematics, Statistics and Biology, in particular nonlinear dynamics and optimal control theory to improve understanding biological systems. She develops Biologically motivated Mathematical and Computational models to understand the mechanisms of infection and its transmission and control at multiple scales of biological organizations. Integrating empirical data and mathematical / statistical theories, specifically she is interested in scaling within-host parasite dynamics to between-host transmission dynamics, modelling higher-order interactions and the indirect effect among species in shaping disease transmission, spatiotemporal dynamics of infectious diseases and its optimal control at the metapopulation level.
Selected Publications
Ghosh S. and Heffernan J.M. (2015). Long term potential of imperfect seasonal flu vaccine in presence of natural immunity, BIOMAT Proceedings

Suma Ghosh, Jessica L Waite, Dale H Clayton and Fredrick R Adler (2014). Can antibodies against flies alter malaria transmission by changing vector behavior? J. Theoretical Biology, 358: 93-101

Suma Ghosh and Samit Bhattacharyya (2013). Spatiotemporal dynamics of insect pest population under viral infection, Mathematical Biosciences, 244(1):13–21.

Ghosh S. and Bhattacharyya S. (2011). A two-patch prey-predator model with food- gathering activity, J. Applied Mathematics and Computing, 37:497–521.

Ghosh S. and Heffernan J.M. (2010). Influenza Pandemic Waves under Various Mitigation Strategies with 2009 H1N1 as a case study. PLoS ONE. 5(12):e14307

Ghosh S., Rangarajan G. and Sinha S. (2010). Stability of synchronization in a multi-cellular system. Europhysics Letters, 92:40012. doi:10.1209/0295-5075/92/40012

Ghosh S. and Bhattacharya D.K. (2010). Optimization in microbial pest control: An integrated approach, Applied Mathematical Modelling, 34:1382–1395
National and International Recognition
CSIR-UGC NET fellowship

WBCSC SLET fellowship

Manuscript Reviewer: Mathematical Biosciences, Journal of Theoretical Biology, Ecological Complexity, Ecological Modelling, Journal of Biological System, PLoS ONE

Invited speakers: University of Guelph Canada, York University Canada, Field Institute Canada, Center for Infectious Disease Dynamics, Penn State University, USA, Mathematical Biosciences Institute in Ohio State University, USA, University of Tennessee, USA, IISER Pune.
Executive Summary
Dr. Suma Ghosh started her Mathematical Biology research career modelling the population dynamics of microbial pest control and its optimal management in Ph.D. In past few years her research extended across different scales of biological organizations in modelling the host-pathogen interaction to understand the transmission dynamics of microparasitic, macroparasitic and vector-borne diseases like influenza, helminthiasis, malaria from within-host to between-host level.

She applies qualitative approach of dynamic modelling such as multi-scale compartmental models, spatial models, state-space models, stochastic models, metapopulation models (coupled map lattice) along with quantitative approach such as data analysis and statistical inferences that together reveals the dynamic patterns of infection and possible within-host / between-host mechanisms generating such trends. Her study helps to characterize the heterogeneity of infection transmission and its control across scales.
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