Mugume Twinamatsiko Atwine

Mugume Twinamatsiko Atwine, MSc

Data Scientist

Research institutions and healthcare organizations across Africa are sitting on goldmines of critical health data - millions of patient records, genomic sequences, epidemiological surveys, and clinical trial results - yet this treasure trove remains largely untapped. These organizations face a perfect storm: rapidly growing datasets from digital health initiatives, limited local expertise in advanced analytics, inadequate infrastructure for large-scale data processing, and urgent health challenges that require immediate, evidence-based solutions...

Meanwhile, critical decisions about disease prevention, treatment protocols, and resource allocation are still being made with incomplete information, while the answers lie buried in their own data warehouses.

AI solutions designed for African realities - systems that work with limited connectivity, respect diverse cultural health practices, handle multiple local languages, and integrate with existing infrastructure without requiring massive overhauls. These solutions must also navigate complex ethical considerations around data sovereignty, ensuring that communities contributing their data are the primary beneficiaries of AI-driven insights.

I design and deploy machine learning pipelines for real-world challenges. At Uganda Virus Research Institute, I lead data catalog development and FAIR assessment initiatives. Through my work with ACE Bioinformatics, I've built scalable ML solutions for health data analytics while teaching next-generation data scientists. My projects span from clinical decision support systems to pandemic preparedness platforms - always with a focus on responsible AI implementation.

Research teams move from weeks of waiting for analysis to real-time insights. The eLwazi work helps enable seamless data sharing across institutions, while my work in predictive models for HIV risk assessment, Cryptococcal Meningitis detection, and COVID-19 misinformation analysis directly support clinical decision-making and public health strategies. Health chatbots provide instant access to critical information, decision support systems streamline clinical workflows, and FAIR assessment work ensures datasets remain accessible for cross-institutional collaboration - multiplying research impact while training the next generation of African data scientists.

Core Technologies: Python | R | Machine Learning | NLP | Data Visualization | Statistical Analysis | Cloud Computing | Ensemble Models

MSc Computer Science | Uganda Virus Research Institute | ACE Bioinformatics | Published Researcher | Ethical AI Advocate

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Services

  • Data Strategy & Roadmapping
  • Machine Learning & AI Solution Development
  • Data Engineering & Pipeline Automation
  • Health Data Analytics & Visualization
  • Training & Capacity Building
  • Odoo Development & Configuration
  • Software Development

Work Experience

Data Science Specialist

Uganda Virus Research Institute (UVRI)

September 2021 - Present

Project: eLwazi Open Data Science Platform(ODSP)

Project Co-Lead: Data Work Group
  • Leadership & Management: Spearheaded diverse teams focusing on Catalog Development, RedCap Integration, and FAIR Assessment
  • Strategic Oversight: Orchestrated regular update meetings and presented progress reports to management
Project Lead: Data Portals
  • Content Curation: Directed metadata collection strategies
  • Team Leadership: Managed cross-functional team of over five members
  • Technical Supervision: Guided development and deployment of data catalogue

Data Scientist | Data Analyst Consultant

Africa Center of Excellence in Bioinformatics and Data Intensive Sciences (ACE)

December 2019 - Present

  • Designed and built scalable machine learning pipelines, optimizing each phase from data preprocessing to model deployment
  • Performed comprehensive data explorations with advanced visualizations to uncover key insights
  • Utilized state-of-the-art AI tools to develop prototypes rapidly, accelerating innovation
  • Specialized in ensemble models and linear models for enhanced predictive accuracy

Assisting Lecturer Big Data Analytics

Africa Center of Excellence in Bioinformatics and Data Intensive Sciences (ACE)

January 2020 - Present

  • Designed and delivered lectures for Ph.D. and Master's programs in Bioinformatics
  • Taught Linear Algorithms, Non-Linear Algorithms, and Tree-Based Algorithms in Machine Learning
  • Integrated practical competitions like Kaggle challenges into teaching

Data Scientist | Natural Language Consultant

Infectious Diseases Institute (IDI) - ACADEMY

November 2021 - October 2023

Project: Decision Support System

  • Orchestrated comprehensive data preparation and analysis
  • Engineered and optimized end-to-end machine learning pipelines
  • Implemented ethical frameworks for responsible AI use

Education

Master of Computer Science

Limkokwing University of Creative Technology Malaysia

Cyberjaya, Malaysia

2013

Honors, First Class

Area: Computer Networks

Bachelor of Science in Computer Science

Mbarara University of Science and Technology

Mbarara, Uganda

2011

Second Class

Professional Certifications

Data Science & Machine Learning (DataCamp)

  • Python Programming (Basic to Advanced)
  • Data Analysis & Manipulation with Pandas
  • Machine Learning (Supervised & Unsupervised)
  • Data Visualization (Matplotlib & Seaborn)
  • Statistical Analysis in Python

Database & SQL

  • Data Analyst with SQL (DataCamp) - Including SQL Server, Relational Databases, and Time Series Analysis

Theoretical Foundations

  • Big Data Theory and Computational Thinking - University of South Australia (Adelaide-X), 2017

Publications

Analysis of Cloud Computing Models Based on Common Factors

Atwine Mugume Twinamatsiko, Ali Naser, Jugal Joshi, Behrang Parhizkar

2012

Dynamic Workload Performance Optimization Model For Multiple-Tenancy In Cloud Systems

Atwine Mugume Twinamatsiko, Jugal Harshvadan Joshi, Ali Naser Abdulhussein Abdulhussein, Arash Habibi Lashkari, Mohammad Sadeghi

IJCSI Journal, Volume 10 Issue 6

November 2013

An Enhanced Quality Model for IaaS Provider with Non-quantifiable Key Performance Indicators

Jugal Harshvadan Joshi, Atwine Mugume Twinamatsiko, Ali Naser Abdulhussein Abdulhussein, Arash Habibi Lashkari, Mohammad Sadeghi

3rd International Conference on Information Computer Application (ICICA 2014)

Barcelona, Spain

2014

An Efficient Load Balancing Algorithm for Virtualized Cloud Data Centers

Ali Naser Abdulhussein Abdulhussein, Jugal Harshvadan Joshi, Atwine Mugume Twinamatsiko, Arash Habibi Lashkari, Mohammad Sadeghi

The 2014 International Conference on Circuits, Systems, Signal Processing, Communications and Computers (CSSCC14)

Italy

2014

Technical Skills

Programming & Tools

  • Python (Anaconda)
  • R (R-studio)
  • Weka (Java Workbench)

Machine Learning

  • Ensemble Models
  • Linear Models
  • Deep Learning
  • Natural Language Processing

Data Science

  • Data Modeling
  • Data Harmonization
  • Statistical Analysis
  • Data Visualization

Research Interests & Collaboration Areas

AI & Machine Learning

  • Deep Learning Architectures
  • Natural Language Processing
  • Computer Vision
  • Reinforcement Learning

Healthcare & Bioinformatics

  • Health Informatics
  • Clinical Decision Support Systems
  • Biomedical Data Analysis
  • Pandemic Preparedness

Data Science & Analytics

  • Big Data Analytics
  • Distributed Computing
  • Data Harmonization
  • Predictive Analytics

Emerging Technologies

  • Edge Computing
  • Federated Learning
  • Ethical AI
  • Cloud Computing