Turing Patterns in Biology
Pattern formation in epidemic models with media coverage, cancer networks with sub-diffusion, and reaction–diffusion systems under stochastic forcing.
Assistant Professor · Mathematics & Statistics · BUBT
I study how spatial patterns emerge in biological systems — Turing patterns in epidemic models and cancer networks, super- and sub-diffusion, stochastic forcing and neural field models of the brain — and build fast spectral methods to simulate them.
Reaction–diffusion · Turing patterns
About
I am an Assistant Professor in the Department of Mathematics and Statistics at Bangladesh University of Business and Technology (BUBT), Dhaka. I earned my Ph.D. in Mathematics from South Asian University, New Delhi, supported by the SAARC India Silver Jubilee Scholarship, and my B.Sc. and M.Sc. in Mathematics from Jahangirnagar University.
My research uses reaction–diffusion theory, weakly nonlinear analysis and spectral methods to understand pattern formation in epidemics, cancer networks and neural fields. Alongside research I have taught university mathematics since 2012 and build interactive tools for my students.
Bangladesh University of Business and Technology (BUBT), Dhaka
South Asian University, New Delhi, India · SAARC India Silver Jubilee Scholarship
Bangladesh University of Business and Technology (BUBT)
Jahangirnagar University, Savar, Bangladesh
Research
My work sits at the intersection of dynamical systems, spatial pattern formation, scientific computing and nature-inspired optimization.
Pattern formation in epidemic models with media coverage, cancer networks with sub-diffusion, and reaction–diffusion systems under stochastic forcing.
Super-diffusive SI epidemic and Leslie–Gower predator–prey models, stability analysis and the spatial spread of interacting populations.
Corticothalamic neural field theory and spatial spectral signatures across states of consciousness.
Chebyshev collocation and exponential time-differencing (ETDRK4) schemes for stiff, nonlinear and stochastic PDEs with machine-precision benchmarks.
Generic set-based Artificial Bee Colony and Whale Optimization algorithms for combinatorial problems.
Bayesian model calibration, causal inference on technology adoption, and data-driven models of environmental systems such as CO2 emissions in Dhaka.
Publications
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Teaching
Hands-on visualisers and practice pages I build for my students. Open one and play with the parameters.
Step through row operations and watch a system reduce to row-echelon form.
Interactive drills on vector addition, scaling, dot products and projections.
See how the unit ball changes shape as p moves from 1 to ∞.
Techniques of integration with worked examples and practice problems.
Explore ellipses, parabolas and hyperbolas by adjusting their parameters live.
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Contact
Open to research collaborations, student supervision and invited talks.