PhD Candidate · Biostatistics

Md Salek Miah

Health Data Scientist & Research Assistant at Shahjalal University of Science and Technology. Published in BMC Women’s Health, Health Science Reports, JAD Reports. Advancing spatial ML, reproductive health equity, and causal inference for LMICs.

Spatial Epidemiology Explainable AI (SHAP/XAI) Reproducible Science Global Mental Health Peer Reviewer (Cambridge UP)

Research Identity & Mission

Md Salek Miah profile

Md Salek Miah

B.Sc. Statistics (Honours) · Shahjalal University of Science and Technology
Major GPA: 3.50-4.00/4.00 (final year)

Sylhet, Bangladesh · ORCID: 0009-0005-5973-461X

I am a biostatistician and health data scientist determined to translate complex epidemiological data into policy-relevant insights. My research agenda focuses on spatial epidemiology, maternal mental health, and explainable machine learning for global health disparities — especially in low-resource settings.

I currently serve as a Research Assistant at Biostatistics, Epidemiology & Public Health Research Group (SUST) and collaborate with ELITE Research Lab (Generative AI & XAI) and Cognitive Solution Bangladesh. I am a peer reviewer for Cambridge University Press & Assessment and have facilitated international workshops on DHS data analysis (R/RStudio).

With 6+ peer-reviewed papers (including first-author in Health Science Reports, JAD Reports), I aspire to pursue a fully-funded PhD in Biostatistics / Epidemiology to advance data-driven health equity using causal inference and spatial ML.

Peer-Reviewed Publications

Selected works from global health surveys (DHS, MICS) — reproducible code and open science principles.

Academic Appointments & Service

Research Assistant (SUST)

Biostatistics, Epidemiology & Public Health Group · Multi-country DHS analysis (Bangladesh, Nepal, Lesotho). Developed spatial ML workflows.

Invited Peer Reviewer

Cambridge University Press & Assessment (Global Mental Health). Verified via Web of Science Reviewer Recognition.

Workshop Facilitator

BIIHR International Free Workshop 2026: “Epidemiological data analysis with R & DHS” (3h bilingual session).

ELITE Research Lab

Research Assistant (XAI, Generative AI, Computer Vision). Contributing to interpretable AI for clinical risk prediction.

Invited Talks & Conferences

BSA International Conference 2025 — Dhaka, Bangladesh. “Machine Learning for Depression Prediction: Evidence from BDHS” (Oral).
ISCB RSG-Bangladesh Symposium — Winner of DNA Day Writing Contest 2025, invited speaker on reproducible research.
DataKothon Research Conclave 2025 — Poster presentation: “Spatial heterogeneity in maternal healthcare access.”
International Workshop on Applied Epidemiology (BIIHR, May 2026) — Lead facilitator: DHS data analysis using R and survey weighting.

Awards & Professional Development

Top 5 Performer

Data Hackathon, IT Fest 2024, Comilla University — excellence in data science & analytics.

1st Place, DNA Day Writing Contest

ISCB RSG-Bangladesh 2025, scientific writing in computational biology.

Data Science & ML with Python

Coursera · IBM Data Analysis with R · SQL for Analytics · Cloud Foundation.

Research Methodology Certification

Field-Based Research (BARD, 2026) · Research Training Program (MKCRD).

Statistical Computing & AI

R / TidyversePython (Pandas, Scikit-learn) STATA / SPSSSASXGBoost / Random Forest SHAP / LIMEArcGIS ProGit/GitHub R Shiny / Hugging FaceLaTeX / RMarkdown

Selected Interactive Projects

Water Quality Intelligence Platform

R Shiny app for Buriganga River monitoring (WQI, spatial hotspots). Live Demo →

MovieLens Recommendation Engine

Collaborative filtering deployed on Hugging Face Spaces.

Statistical Calculator Suite

Hypothesis tests, regression, probability distributions — Shiny app.

Open for PhD Supervision & Collaboration

I am actively seeking funded PhD positions in Biostatistics, Spatial Epidemiology, or Global Health Data Science. Feel free to reach out.