CV

Academic CV of Dr. Yaé Ulrich Gaba — education, experience, skills, and publications.

Contact information

Name Yaé Ulrich Gaba
Professional title Research · Teaching · Consulting
Email gabayae2@gmail.com
Location Kigali, Rwanda

Professional summary

Topologist and AI researcher. I develop mathematical methods for machine learning, teach them at the graduate level, and consult with organizations that need rigorous thinking applied to hard problems. As Head of R&D at a technology startup, I lead applied research initiatives that bridge methodological innovation and operational deployment, with cross-industry experience in banking, energy, insurance, IT, and retail.

Experience

  • 2025 - present

    Kigali, Rwanda

    Head of R&D · AI Research & Innovation Lead
    AIRINA Labs
    Leading applied research initiatives that bridge methodological innovation and operational deployment. Cross-industry experience applying statistical modeling and machine learning to complex problems across different industries.
    • Applied research with a focus on interpretability, robustness, and validation
    • Statistical modeling and ML across banking, energy, insurance, IT, and retail
    • AI research and innovation for the African continent
    • Data Science Makers community building and ML workshops
  • 2020 - present

    Yaoundé, Cameroon

    Research Affiliate
    African Centre for Advanced Studies (ACAS)
    • Research in topology, data science, and machine learning
    • Mentoring African graduate students and early-career researchers
  • 2021 - 2024

    Kigali, Rwanda

    Research Associate
    Quantum Leap Africa (QLA) | AIMS-RIC
    Research at the intersection of topology, data science, and quantum computing.
    • Topological methods in machine learning and data analysis
    • Workshop on Computational Topology & Quantum Computing (WoComToQC) organizer
  • 2017 - 2019

    South Africa

    Postdoctoral Researcher
    North-West University
    • Research in fixed point theory and generalized metric spaces
    • Published in Topology and its Applications, JMAA, and Quaestiones Mathematicae
  • 2018 - 2020

    Dangbo, Bénin

    Assistant Professor
    IMSP (Institut de Mathématiques et de Sciences Physiques)
    • Teaching graduate courses in topology and analysis
    • Supervising MSc students in pure mathematics

Education

  • 2013 - 2017

    Cape Town, South Africa

    PhD
    University of Cape Town (UCT)
    Topology
    • Thesis on asymmetric topology and fixed point theory in generalized metric spaces
    • Quasi-pseudo metric spaces and η-cone metric structures
  • 2011 - 2013

    Abuja, Nigeria

    MSc
    African University of Science and Technology (AUST)
    Pure & Applied Mathematics
    • Advanced studies in pure mathematics, topology, and analysis

Publications

Skills

Mathematics (Expert): Asymmetric Topology, Fixed Point Theory, Generalized Metric Spaces, Topological Data Analysis, Persistent Homology
Machine Learning & AI (Expert): Geometric Deep Learning, Deep Reinforcement Learning, Graph Neural Networks, TDA, Manifold Learning
Statistical Modeling (Expert): Regression, Time Series, Bayesian Methods, Model Validation, Interpretability, Risk Modeling
Programming (Advanced): Python, R, PyTorch, TensorFlow, scikit-learn, GUDHI, Ripser, SQL
Tools & Platforms (Advanced): Git, Docker, LaTeX, Linux, Jupyter, MLflow, GitHub Actions
Industry Domains (Advanced): Banking, Energy, Insurance, IT, Retail, Quantitative Finance

Languages

French : Native speaker
English : Fluent

Interests

Research: Asymmetric Topology, Topological Data Analysis, Geometric Deep Learning, Reinforcement Learning, Quantitative Finance
Community: Data Science Africa, Data Science Makers, AI for Africa, Mentoring, Workshop Organization

Projects

  • Workshop on Computational Topology & Quantum Computing (WoComToQC)

    Organized an interdisciplinary workshop bringing together researchers in computational topology and quantum computing.

  • The Shape of Data (No Starch Press)

    Co-authored a book on geometry-based machine learning and data analysis in R.

  • Data Science Makers

    Open-source ML teaching and outreach initiative for African universities and research communities.