Blondelle Melina Atsafack
Experienced Data Scientist
KN 134, Kigali, Rwanda
PROFESSIONAL SUMMARY
Researcher and data analyst specializing in Internet of Things (IoT) and Machine Learning for predictive maintenance and industrial monitoring systems.
Currently pursuing a PhD in Internet of Things and Embedded Computing Systems at the University of Rwanda – African Centre of Excellence in Internet of Things (ACEIoT).
My research focuses on AI-driven predictive maintenance and real-time monitoring of hydropower plants, integrating IoT sensors, time-series analysis, and machine learning models to improve reliability, efficiency, and sustainability of energy systems.
Strong experience in:
- Industrial data analytics
- Time-series anomaly detection
- Hydropower plant monitoring
- IoT-enabled smart infrastructure
Committed to advancing data-driven energy systems for sustainable development in Sub-Saharan Africa.
WORK EXPERIENCE
Data Scientist Researcher – Predictive Maintenance.
January 2024 – September 2025
Kavumu Hydropower Plant
Kigali, Rwanda
Responsibilities:
- Developed data-driven monitoring systems for hydropower plant operations
- Implemented real-time health indicators for hydraulic turbine units
- Designed remote supervision frameworks using IoT data streams
- Applied machine learning models for anomaly detection in turbine time-series data
- Conducted data analysis and visualization for operational performance monitoring
IT Assistant Lecturer
March 2020 – September 2022
Inter-States University, Congo-Cameroon
Sangmelima, Cameroon
Responsibilities:
- Taught programming and coding fundamentals
- Introduced students to Internet of Things devices and applications
- Assisted in curriculum development for technology courses
- Mentored students on industrial integration and technical projects
EDUCATION
PhD in Internet of Things – Embedded Computing Systems
September 2022 – May 2026
University of Rwanda – African Centre of Excellence in Internet of Things (ACEIoT)
Kigali, Rwanda
Research focus:
- Predictive maintenance of hydropower plants
- Machine learning for industrial monitoring
- IoT-enabled smart energy systems
Visiting PhD Scholar
September 2024 – September 2025
Worcester Polytechnic Institute (WPI)
Worcester, Massachusetts, USA
Research activities:
- Hydropower plant data analysis
- Advanced machine learning methods for anomaly detection
- Industrial IoT systems
Master of Science in Computer Science
2017
University of Ngaoundere
Cameroon
Specialization:
- Distributed systems and software environments
- Network security
- Network configuration and communication
SKILLS
Programming & Development
- Python (data analysis, machine learning, Flask)
- Arduino
- Raspberry Pi
Data & Databases
- SQL databases
- Data preprocessing
- Data visualization
- Time-series data analysis
Machine Learning & AI
- Anomaly detection
- Predictive maintenance models
- LSTM-based approaches
- Time-series forecasting
Industrial Systems
- PLC fundamentals
- SCADA fundamentals
- RTU systems
- LabVIEW (GUI design and supervision)
Scientific Tools
- LaTeX (Overleaf)
- Technical documentation
- Academic writing
Design & Communication
- Pixelmator Pro
- Scientific presentations
Productivity Tools
- Microsoft Office Suite
SOFTWARE
- Python
- MATLAB / Simulink
- LabVIEW
- GitHub
- Heroku (Flask deployment)
- AWS (Fundamentals)
- SQL Databases
PUBLICATIONS
- Atsafack, B. M., Nzanywayingoma, F., Kabiri, C., & Rushingabigwi, G. (2024). Remote Monitoring of Micro-Hydropower Plants Using Python. International Conference on Green Energy, Computing and Sustainable Technology (GECOST). DOI: 10.1109/GECOST60902.2024.10475070
- Atsafack, B. M., Kabiri, C., & Rushingabigwi, G. (2025). A multi-model predictive framework for unsupervised anomaly detection in univariate time-series data from hydraulic turbine units. Energy Reports, 14, 4701–4709.
- Atsafack, B. M., Kabiri, C., & Rushingabigwi, G. (2025). Predictive Maintenance for Hydraulic Turbine Units: A Comparative Deep Learning Approach Using IoT Data in Real Time. IEEE Access, vol. 13.
AWARDS AND HONORS
PASET Regional Scholarship and Innovation Fund (RSIF) PhD Scholarship
2022
Doctoral scholarship awarded for research in ICT, Artificial Intelligence, and Renewable Energy Systems.
LANGUAGES
- French – Native / Fluent
- English – Professional proficiency