Tech Stack
Python
R
React
FastAPI
JavaScript
HTML
CSS
Git
Power BIAI Researcher · Data Scientist · Statistician
Building intelligent systems that connect climate variability, agricultural data, and AI to real-world impact. PhD researcher at Leeds Beckett University — working on causal, predictive, and proactive AI for sustainable food security in Sub-Saharan Africa.
01 — About
I'm Chinedu Matthew Uzim — an AI Researcher, Data Scientist, and Statistician based in the UK, building intelligent systems that address real-world challenges in food security, healthcare, and sustainability.
Currently pursuing a PhD at Leeds Beckett University, my research focuses on causal, predictive, and proactive AI for sustainable agriculture in Sub-Saharan Africa — designing systems that go beyond forecasting to recommend actionable interventions for policymakers.
I'm a published researcher, creator of SmartSkan (Skannr's AI-powered medical scan recommendation system), and passionate about transforming complex data into real-world impact across Africa and beyond.
Causal, predictive & proactive AI for sustainable food security — connecting climate variability to policy in Sub-Saharan Africa.
Built Skannr's intelligent symptom-to-scan AI system — hybrid medical rules + Google Gemini AI. Featured in Skannr's press spotlight.
Python, R, SQL, Power BI — from statistical modelling and GIS analysis to machine learning pipelines and dashboards.
02 — Skills
Tech Stack
PythonRReactFastAPIJavaScriptHTMLCSSGitPower BI04 — Projects
An intelligent symptom-to-scan recommendation system combining structured medical rules with Google Gemini AI — integrated with Skannr's provider network for instant scan booking.
PhD research — a five-layer AI system connecting climate variability and agricultural data to actionable policy recommendations for Sub-Saharan Africa.
Co-authored research developing a Personalized Geospatial Information System for rice production optimisation in Ebonyi State, Nigeria — using Sentinel-1 SAR data and spatial analysis.
Machine learning model built in R (XGBoost, LSTM, SVR, Decision Tree) with an interactive Shiny web application for real-time house price prediction.
Scraped and analysed 5,000+ car listings from The AA and Cinch using R — rvest, httr, and tidyverse pipelines — uncovering pricing and depreciation trends.
05 — Press & Features
Skannr spoke with Chinedu about developing SmartSkan — balancing AI innovation with patient safety and building a seamless experience connecting users to real scan providers.
06 — Publications
International Journal of Innovative Science and Research Technology (IJISRT) · Vol. 11, Issue 5, pp. 154–174 · DOI: 10.38124/ijisrt/26may211
This study develops a PGIS framework integrating Sentinel-1 SAR remote sensing, geospatial mapping, and agricultural statistics to provide site-specific recommendations for optimising rice production in Ebonyi State, Nigeria — addressing soil fertility degradation, climate variability, and resource inefficiency through precision agriculture and evidence-based decision making.
More publications in progress · View full profile on ResearchGate →
07 — Education
08 — Contact
Open to research collaborations, academic partnerships, AI consulting, data science projects, and speaking opportunities. Feel free to reach out.