Summary

Machine Learning researcher with interdisciplinary training in Physics and Artificial Intelligence, focusing on scientific AI systems for biomedical imaging, biosensing, and large-scale spatiotemporal modeling.

Education

• Computer Engineering — Artificial Intelligence & Machine Learning
  National Advanced School of Engineering of Yaoundé (ENSPY)

  GPA: 3.0/4.0

  Courses: Deep Learning, Computer Vision, NLP, Distributed Systems, Software Engineering
• Physical Sciences (M2 in progress)
  University of Dschang

  GPA:
• Physics — Computational Physics & Numerical Simulation
  University of Dschang

  GPA: First Class Honours

  Courses: Quantum Mechanics, Electromagnetism, Statistical Physics, Numerical Methods, Scientific Computing

Work Experience

• SI Engineer / Data Scientist

  2025-11-01 -
  Orange Cameroon

  Leading data and analytics workstream for NextGen, a large-scale migration of the Orange Money platform from Tango to Huawei Mobile Money (HMM).

  • Designed and governed end-to-end data migration strategies ensuring data integrity, consistency, and regulatory compliance
  • Defined data models, transformation rules, and reconciliation frameworks for customer, transaction, wallet, and settlement data
  • Developed data quality controls, validation pipelines, and anomaly detection mechanisms for high-volume financial data
  • Provided technical leadership on data architecture, analytics, and decision-support use cases
• Lead Machine Learning Engineer

  2025-01-01 - 2025-10-01
  DME Systems

  Built GPU-accelerated recommender systems and multi-agent ML pipelines for a sports betting platform.

  • Built GPU-accelerated recommender systems using NVIDIA Merlin delivering personalised event and odds recommendations in real time
  • Architected end-to-end ML pipeline: data ingestion, feature engineering, model training, deployment, and real-time inference
  • Designed multi-agent systems to optimise live betting decision-making via real-time analytics and predictive modelling
  • Led cross-functional team of 2 Data Scientists; established best practices for model deployment and CI/CD pipelines
• Machine Learning Engineer — Public Procurement Fraud Detection

  2024-07-01 - 2024-12-01
  AI Technologies for Africa (AITECAF)

  Designed and deployed GNN models to identify collusive bidding and anomalies in Cameroon's public procurement system.

  • Designed and deployed GNN models (GCN, GAT, R-GCN) to identify collusive bidding and anomalies in public procurement
  • Modelled heterogeneous graphs with nodes representing suppliers, contracts, and government agencies
  • Built robust ETL pipelines integrating ePPP, CPPA, and corporate registry data; performed entity resolution on 30%+ missing data
  • Collaborated with Cameroon's Supreme Audit Institution to co-design an AI-driven auditing assistant
• Lead Machine Learning & Computer Vision Engineer

  2023-01-01 - 2024-07-01
  SmartDS

  Led development of deep learning systems for real-time video analysis and autonomous drone delivery.

  • Led development of deep learning framework enabling real-time video stream analysis; improved surveillance capabilities by 40%
  • Deployed production system handling 1,000 requests/second with <100ms response time using Docker and Kubernetes
  • Engineered autonomous drone delivery system with advanced computer vision navigation; reduced delivery times by 30%
  • Established CI/CD pipelines for ML model deployment; mentored junior developers and data scientists

Skills

Publications

• Leveraging Machine Learning for Enhanced Financial Inclusion: Revolutionizing Agricultural Banking in Central Africa

  2025
  OpenReview

  Proposed a credit scoring model using alternative data (mobile money transactions, crop yields, weather, demographics) for rural farmers in Central Africa. Compared ML approaches against logistic regression baselines; demonstrated significantly higher loan approval rates, lower default risk, and improved operational efficiency.

  View Publication

Languages

• French

  Native proficiency
• English

  Professional working proficiency

Interests

• Physics-Informed Machine Learning
• Biomedical AI & MRI Synthesis
• Climate AI & Earth System Modelling
• Edge AI & Resource-Constrained Systems
• Uncertainty Quantification

References

• Prof. David YEMELE

  Vice Dean, Faculty of Science, Dept. of Physics, University of Dschang. Email: dyemele@yahoo.fr
• Prof. Thomas B. BOUETOU

  Head of Department, Computer Engineering, ENSP, University of Yaoundé I. Email: tbouetou@gmail.com
• Prof. Georges E. KOUAMOU

  Professor, Department of Computer Engineering, ENSP, University of Yaoundé I. Email: georges.kouamou@gmail.com