Ongoing Researches

Primary Research Interest: Diabetology & Insulin Resistance, ROS, Ion Channels, Cardiology, Cell Signaling & MMDA

Secondary Research Interest: Public Health

• Particle Physics, String Theory and Phenomenology
• Machine Learning Applications to Theoretical Physics

Computer Vision, Natural Language Processing(NLP), Large Language Models(LLM), Semantic Web, Blockchain technology

• Stem Cell Biology
• Regenerative Medicine
• Cancer
• Neurogenetics
• Molecular Genetics

• Phytochemistry & Public health

• Bayesian Network and modelling
• Bio-statistics, epidemiology  and Statistical Computation
• Statistical Modeling, Longitudinal Data Analysis, causal Inference, Povarty issue analysis

Cybersecurity, Trust, ML/AI, IoT

• Explainable Deep Learning and Computer Vision for Medical Imaging
• Machine Learning Frameworks for Time-Series and Energy Forecasting
• Wireless Networks & Protocols

• Microbiology and Clinical survey

• 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.

• Cybersecurity
• Artificial Intelligence
• Cloud Computing
• Blockchain
• Internet of Things (IoT)

AP-Spatial Atomic Layer Deposition, nano film fabrication & it's morphology, Gas sensor on FET

• Pharmacology and Toxicological studies
• Phytopharmacology
• Anticancer drug evaluation
• Computational Biology

My research focus lies at the intersection of advanced photonics, VLSI design, and biosensing technologies. Specific areas include:

VLSI & Circuit Design: Linearity analysis of CSR-VCO for RF applications and low-power approximate adders for DSP.

Nanotechnology: Impact of asymmetric salt concentration on nanopore properties and particle translocation.

IoT & Automation: Development of smart monitoring systems and industrial robotics.

Photonics & Bio-sensing: Design of Photonic Crystal Fibers (SPR-PCF) for medical diagnostics (e.g., prostate cancer detection).