Ongoing Researches: Department of Mathematical and Physical Sciences

• Plasma Physics
• Applied Mathematics

• Plasma Physics:   Dusty plasma physics is a specialized branch of plasma physics that focuses on plasmas containing electron, ions and charged less dust particles suspended in the ionized gas. These dust particles interact with the surrounding plasma through electrostatic forces, leading to unique behaviors and phenomena. Dusty plasmas are found in many natural environments, such as in space and  in cometary tails, and are also found in laboratory. The study of dusty plasmas provides insights into fundamental plasma dynamics, as well as practical applications in materials science, space exploration, and industrial processes involving plasma-based technologies.
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• Cloud Electrification: Cloud electrification refers to the process by which clouds accumulate electrical charges, leading to the development of lightning and thunder. This phenomenon occurs primarily in convective clouds, such as thunderclouds, where the movement of supercooled water droplets, ice crystals, and snow particles causes collisions that transfer electrical charge. As a result, different regions of the cloud acquire positive or negative charges, creating an electric field strong enough to trigger lightning discharges, either within the cloud, between clouds, or to the ground. Understanding cloud electrification is essential for predicting and mitigating the effects of thunderstorms and lightning-related hazards. 

• Dusty Plasma Physics
• Applied Mathematics

• Computational Fluid Dynamics (CFD, Heat and Mass Transfer, Turbulent Flow).
• Mathematical Modeling,

Robust methods of estimation, Outlier detection, Regression diagnostics, Data mining and statistical machine learning, Multivariate analysis, Statistical computing and graphics, Econometrics methods, Simulation and bootstrapping techniques.

Porous Materials for Environmental Remediation

-Synthesis of porous materials such as Metal-organic fameworks (MOFs), Zeolites, Nickle phosphate molecular sieves.

-Rapid synthesis of porous materials with microwave and ultrasound irradiation.

-Functionalization/modification of MOFs for targeted applications.

Adsorption/separation/Purification

–Adsorptive removal of hazardous materials, including Sulfur Containing Compound (SCC), Nitrogen Containing Compounds (NCC), Pharmaceuticals and Personal Care Products (PPCPs), Contaminants of Emrrging Concerns (CECs).

-Gas phase adsorption of arometics.

Heterogeneous Catalysis

-Acid catalysis with nano porous materials.

-Conversion of biomass into chemical intermediates via dehydration

-Reduction and photocatlysis of organic pollutants

1. Highly porous materials

- Synthesis/Application of porous materials (MOFs, zeolites, carbons, AlPOs)

- MOF- or organic polymer-derived carbons (highly porous, ordered and having various functionalities) adsorption/storage, catalysis and electrical energy storage.

-Rapid/continuous synthesis of porous materials with microwave and ultrasonics

- Functionalization/Modification of MOFs for selective adsorption of hazardous compounds

2. Adsorption/separation

- CO₂ capture with porous adsorbents 

- Fuel purification (removal of S- and N- containing compounds)

- Water purification (removal of pharmaceuticals, personal care products, pesticides, dyes)

- Adsorption/separation of hydrocarbons

- Adsorption/storage of gases

3. Heterogeneous catalysis

- Acid catalysis with porous materials (dehydration, isomerization, alkylation)

- Conversion of biomass into chemical intermediates with dehydration

4. Electrochemistry

-Supercapacitor

-Sensor

1. "Environmental Petroleomics", "Natural organic matter", "Microplastic degradation", and "Plant metabolites" using Mass spectrometry: Investigating the molecular-level impact of crude oil spills using ultrahigh-resolution mass spectrometry (UHR-MS to understand the fate, behavior, and environmental consequences of spilled oils, contributing to effective response strategies and minimizing health risks.
2. Heavy metal contamination using Atomic absorption spectroscopy: Studying the sources, distribution, and environmental impact of heavy metals in soil, sediment, and water systems, particularly in coastal and industrial regions. Using advanced techniques like atomic absorption spectrometry (AAS) and geographical information systems (GIS), this research seeks to identify contamination sources and support remediation efforts to protect public health.
3. Sustainable environmental practices: Exploring green chemistry approaches for environmental remediation, including the development of alternative adsorbents and bioremediation techniques to treat contaminated water and soil sustainably, supporting long-term environmental and public health.
4. Environmental pollution and monitoring.
5. Public health and environmental safety: Examining the intersection of environmental pollution and public health, with a focus on the long-term effects of exposure to heavy metals and other contaminants. This research provides insights into mitigating health risks and improving community health outcomes.
6. Nutritional interventions for health inequality mitigation: Investigating the role of targeted nutritional programs in reducing health disparities exacerbated by crises like the COVID-19 pandemic. This includes assessing how improved nutrition can enhance immune function and overall health in vulnerable populations, such as children and pregnant women, to address and prevent health inequalities.

• Dynamical System
• Differential Geometry

• Astrophysics:
  Gravitational lensing, large-scale structure of the universe, General Theory of Relativity, cosmic structures, ray tracing methodology, N-body simulations, dark matter, dark energy, and implementing machine learning approaches to deal with big datasets.

• Plasma Physics:
  Electrostatic waves and their nonlinear structures in various plasma systems, space and astrophysical plasmas, multi-ion plasmas, degenerate quantum plasmas, nonextensive plasmas, strongly coupled plasmas, and dusty/complex plasmas.

• Theoretical and Computational Mathematics

• Polymer Chemistry
• Food Chemistry
• Natural Product Chemistry

My research focuses on the synthesis and characterization of nanomaterials, with a particular emphasis on two-dimensional (2D) materials for applications in energy, environmental, and electronic devices.

• Statistical Modeling
• Time Series Analysis
• Stochastic Processes
• Analysis of Longitudinal Data
• Bayesian Analysis
• Public Health

• Research Interest

  Shamima Hossain’s research focuses on Bayesian Statistics, spatio-temporal modeling, and machine learning, with applications in public health, epidemiology, and climate data analysis. She is particularly interested in developing Bayesian Neural Networks (BNNs) and predictive models to address societal challenges through data-driven solutions.

Area of Specialization

Shamima Hossain specializes in Bayesian Statistics, Generalized Linear Models (GLMs), and Spatio-Temporal Modeling, with extensive expertise in applying advanced statistical methodologies to solve real-world problems. Her focus areas include epidemiology, public health analytics, and climate data modeling, with a particular interest in developing robust Bayesian Neural Networks (BNNs) for high-dimensional data analysis. She is also proficient in statistical software such as R, Python, SPSS, and STATA, enhancing her capabilities in computational statistics and predictive modeling. Through her academic and research endeavors, she has contributed significantly to understanding societal challenges, including public health crises and women's empowerment, using statistical frameworks.

Research Projects:

World Bank-Funded HEQEP Project: Research Team Member -“Covariate Dependent Models for Correlated Outcomes in    Longitudinal Data Analysis, 2014 to 2017.