Available for Collaboration · 2026

Md. Abu Bokkor
Shiddik

Researcher · Machine Learning · Explainable AI · Global Health Analytics

Dept. of Statistics, BRUR · Rangpur, Bangladesh

✉ abubokkor.brur60@gmail.com 📞 +880 1874 001360 📍 Rangpur, Bangladesh
🌐 Portfolio in LinkedIn 🎓 Scholar ✦ ORCID {} GitHub
↓ Download CV View Publications →
12+
Publications
18
Peer Reviews
26
Certifications
8
Institutions
Published in Nature / Scientific Reports BMJ Open Springer Elsevier MDPI Wiley
Md. Abu Bokkor Shiddik
Open to Collaborate
12+ Publications
Dept. of Statistics Begum Rokeya University
Rangpur, Bangladesh

Research Profile

I am a researcher with 12+ peer-reviewed publications in high-impact international journals including Scientific Reports, BMJ Open, Global Epidemiology, and International Journal of Health Geographics. My research covers global disease modeling, dengue early warning systems, and climate-health interactions.

My work integrates machine learning, explainable AI (SHAP, LIME), Bayesian deep learning, and spatial analysis to support evidence-based decision-making in public health — across 194 countries using large-scale multi-source datasets.

Research Interests

🤖
Machine Learning in Public Health
🔍
Explainable AI (XAI)
📊
Epidemiological Modeling
🗺
Spatiotemporal Analysis
🦠
Disease Prediction Systems
🌡
Climate & Health

Technical Skills

Core Methods
Machine LearningSHAPLIMEStatistical ModelingCausal AI
Programming & Tools
RPythonSPSSLaTeXGit / GitHub
Advanced Analytics
ARIMA / SARIMASpatial AnalysisBayesian ModelingDeep LearningXGBoost
Application Domains
EpidemiologyClimate-HealthDisease PredictionHealth Geographics

Selected Publications

View all 12 →
Scientific Reports2025OA

Utilizing AI to predict socioeconomic, environmental, and healthcare factors driving tuberculosis globally

View paper →
Health Science Reports2025OA

Dengue Early Warning System and Outbreak Prediction Tool in Bangladesh Using Interpretable Tree-Based ML Model

View paper →
Global Epidemiology2025OA

Explainable AI for predicting dengue outbreaks in Bangladesh using eco-climatic triggers

View paper →
Scientific Reports2025OA

Unraveling global malaria incidence and mortality using machine learning and AI-driven spatial analysis

View paper →
Int. J. Health Geographics2025OA

Leveraging explainable AI and spatial analysis for communicable diseases in Asia (2000–2022)

View paper →
Trop. Med. & Infect. Dis.2026OA

District-Level Dengue Early Warning System in Bangladesh Using Hybrid Explainable AI and Bayesian Deep Learning

View paper →

Open Data & Code Lab

Explore →
🦟
Dengue District
64 Districts · 2017–2024
🦟
Dengue EWS
National · 2000–2024
🌍
Global TB
194 Countries · 2000–2022
🌍
Global Malaria
106 Countries · 2000–2022

Projects

See all →
🗺
Dengue Dashboard
Interactive district-level early warning visualization for dengue outbreaks across all 64 districts of Bangladesh.
📋
Systematic Review Tool
Automated literature screening and data extraction workflow designed for health and epidemiology research.
📦
R Package
Open-source R package for epidemiological time-series modeling, SHAP analysis, and visualization.

Latest Insights

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Threshold
Machine Learning
Threshold selection in outbreak prediction models
📅 10 April 2026
 GATHER
Public Health
Understanding GATHER and making health estimates transparent
📅 6 April 2026
 Normalization
Machine Learning
Normalization vs. Standardization in data preprocessing
📅 6 April 2026

Recent Courses & Training

See all 26 →
Gen AI in Research Workflow
Elsevier Researcher Academy · 2026
Technical Writing Skills
Elsevier Researcher Academy · 2026
Practical Time Series Analysis
State University of New York · 2025
Machine Learning with Python
IBM · 2024
Climate Risk Informed Decision Analysis
UNESCO · 2024
Data Visualization with R
IBM · 2024

Academic Service

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Peer ReviewerBMJ Global Health
Peer ReviewerPLOS Digital Health
Peer ReviewerHealth Science Reports
Peer ReviewerBMJ Public Health