My professional portfolio has moved

Visit godwineakpan.com →

My current professional profile, selected projects, engineering case studies, experience and credentials are now at godwineakpan.com.

The Analytics-GIS-GeoAI-Portfolio repository remains active as the supporting library for code, notebooks, technical documentation, project outputs and the portfolio PDF.

This GitHub Pages presentation is retained as an earlier portfolio overview. Its descriptions and learning statuses may differ from the current website; please use the new website for current professional information.

Earlier portfolio overview

Godwin Etim Akpan

Data Analytics | Data Engineering | Enterprise GIS | GeoAI | Machine Learning

Building secure, explainable, and practical data systems that transform complex information into trusted intelligence.

I am a GIS, data analytics, and data engineering professional with more than 10 years of experience transforming complex spatial, public-health, and enterprise data into trusted intelligence for informed decision-making.

My work combines data analytics, data engineering, enterprise GIS, spatial analysis, GeoAI, machine learning, cloud computing, explainable AI, and secure software engineering to develop practical, scalable, and governance-aware systems. These systems support public health, emergency management, humanitarian response, infrastructure planning, and organisational decision-making.

MSc Big Data Technologies Candidate · M.Tech. Geoinformation Science and Remote Sensing · 10+ years of professional experience · 10+ peer-reviewed publications

Professional Portfolio (PDF) | Live GeoAI Dashboard | LinkedIn | Email

Impact at a Glance

Measure Impact
Experience 10+ years across GIS, data analytics, public-health intelligence, and spatial decision support
Delivery 6,000+ maps, dashboards, and analytical products
Capacity building 400+ professionals trained in GIS, spatial analysis, and digital data collection
Research 10+ peer-reviewed scientific publications
Public service National-level public-health surveillance and emergency-response support in Liberia

Flagship Project

Privacy-Preserving GeoAI Health Surveillance System

A working research prototype that transforms aggregated district-level data into outbreak-risk classifications, spatial intelligence, explainable model outputs, and dashboard-based public-health decision support.

GeoAI Health Surveillance Dashboard

Implemented Capabilities

Technology stack: Python GeoPandas PySAL Scikit-learn XGBoost SHAP FastAPI Streamlit Folium Docker AWS JWT RBAC

Data architecture: PostgreSQL/PostGIS supported spatial data management during development and evaluation. The public demonstration uses CSV and GeoJSON datasets for reproducibility and privacy-aware distribution.

Explore the project:

This system is an academic research prototype. It is not intended for clinical diagnosis or operational public-health deployment without further validation, security hardening, governance review, and institutional approval.

What I Build

Explore the Portfolio

1. Data Engineering, Big Data, and Machine Learning

Spark, Hive, PySpark, NLP, streaming analytics, machine-learning pipelines, cybersecurity analytics, and location intelligence.

Intrusion Detection with Big Data Analytics

2. Public Health GeoAI and Spatial Epidemiology

Disease forecasting, outbreak-risk intelligence, hotspot analysis, spatial epidemiology, privacy-aware surveillance, and peer-reviewed research.

Privacy-Preserving GeoAI Health Surveillance System

3. GIS, Spatial Data Science, and Remote Sensing

Enterprise GIS, spatial modelling, cartography, hazard exposure, remote sensing, geospatial quality assurance, and GIS automation.

Wake County Flood Exposure Mapping

4. Cloud Computing and Security Engineering

AWS, Azure, GCP, cloud laboratories, identity and access management, cryptography, distributed computing, and infrastructure concepts.

5. Data Analytics and Data Engineering

ETL/ELT, analytics engineering, data modelling, lakehouse patterns, Microsoft Fabric learning, and reproducible data workflows.

6. Automation, Reliability, and Secure Systems

Python automation, monitoring, reporting, APIs, secure file handling, and reliability workflows.

Technical Expertise

Data Analytics and Engineering: Python SQL Pandas NumPy PostgreSQL PostGIS ETL/ELT Data Validation Feature Engineering Spark PySpark Hive

GeoAI and Enterprise GIS: ArcGIS Pro ArcGIS Online QGIS GeoPandas PySAL Spatial Statistics Moran's I LISA Getis-Ord Gi* Cartography Remote Sensing

Machine Learning and Explainable AI: Scikit-learn XGBoost Random Forest Logistic Regression SHAP Model Evaluation Spatial Machine Learning Responsible AI

Cloud, APIs, and Secure Systems: FastAPI REST APIs Docker AWS Streamlit Git/GitHub JWT RBAC Audit Logging API Security Privacy-Preserving Analytics

Professional Background

Over the past decade, I have supported enterprise GIS, spatial data management, public-health surveillance, emergency response, and analytics across research and operational environments.

My professional work includes:

Featured Research and Academic Background

MSc Big Data Technologies — Candidate

University of East London / UNICAF
Final award pending

Dissertation: Design and Evaluation of a Privacy-Preserving GeoAI Health Surveillance System Using a Hybrid Cloud Architecture

Using Design Science Research, I designed, implemented, and evaluated a governance-aware GeoAI public-health surveillance artefact across predictive performance, spatial intelligence, explainability, security and governance, usability, and decision-support value.

Master of Technology (M.Tech.) in Geoinformation Science and Remote Sensing

Federal University of Technology, Akure (FUTA), Nigeria / UN-ARCSSTEE

Specialised training in geographic information systems, remote sensing, spatial analysis, geospatial data management, cartography, and environmental modelling.

Publications and Research

I have authored and co-authored 10+ peer-reviewed publications covering infectious-disease surveillance, spatial epidemiology, GIS, GeoAI, and public-health intelligence.

Google Scholar · ORCID · ResearchGate

My research complements my engineering work by translating analytical methods into practical, reproducible GeoAI and decision-support solutions.

Current Learning Focus

Open to Opportunities and Collaboration

I am open to professional opportunities and collaborations involving data analytics, data engineering, enterprise GIS, GeoAI, spatial data science, machine learning, explainable AI, privacy-aware analytics, public-health intelligence, and secure decision-support systems.

Committed to building secure, explainable, and practical data solutions that create measurable impact.

© 2026 Godwin Etim Akpan