Curriculum Vitae
Full CV available upon request · d.kramekadurha@vu.nl
Education
Nov 2025 — Nov 2029
PhD in Applied Probability and Network Optimization
VU Amsterdam, Netherlands
Optimizing weather-resilient grid operations within the VIDI project
Power Network Optimization in the Age of Climate Extremes,
supervised by Alessandro Zocca and Sandjai Bhulai.
Research in sequential optimization under uncertainty, stochastic modelling, and machine learning for sustainable energy systems.
Sep 2024 — Aug 2025
MSc in Mathematical Sciences
University of Edinburgh, Scotland, UK
Specialization in Operational Research with Data Science.
Courses: Optimization Under Uncertainty, Integer & Combinatorial Optimization,
Reinforcement Learning, Algorithmic Game Theory, Machine Learning & Pattern Recognition.
Sep 2023 — Jun 2024
MSc in Mathematical Sciences
African Institute for Mathematical Sciences (AIMS), Cameroon
Major in Data Science. Courses: Mathematical Modeling, Machine Learning, Deep Learning,
NLP, Bayesian Statistics, High-Dimensional Data Analysis.
Oct 2016 — Dec 2022
Bac+6 in Computer Engineering
Université Libre des Pays des Grands-Lacs (ULPGL), DR Congo
Artificial Intelligence, Data Mining, Distributed Systems, Computer Architecture.
Experience
Nov 2025 — Present
Teaching Assistant
Vrije Universiteit Amsterdam, Netherlands
Mathematical Optimization, Dynamic Programming and Reinforcement Learning,
Project in Big Data. Tutorials, lab exercises, and grading.
Jan 2023 — Sep 2025
Teaching Assistant (Part Time, Remote)
Université Libre des Pays des Grands-Lacs, DR Congo
Co-supervised final-year students. Assisted with complex analysis, algebra, and real analysis.
Oct 2019 — Present
Researcher & Consultant
Centre de Recherche et d'Expertise Scientifique, DR Congo
AI project consulting and teaching artificial intelligence and Python to junior researchers.
Technical Skills
Mathematical Optimization
Optimization Under Uncertainty, Stochastic Modelling, Integer & Combinatorial Optimization, Reinforcement Learning, Decision-Focused Learning, Game Theory
Machine Learning & Deep Learning
PyTorch (4+ years), Transformers, NLP, time series forecasting, physics-informed neural networks, hybrid optimization-ML for energy scheduling
Data Analysis & Statistics
Bayesian statistics, inferential statistics, high-dimensional data analysis, R (1.5 years), statistical modeling
Programming & Tools
Python, Julia, R, Xpress Solver, TensorFlow, Keras, Flask, REST APIs, Git, Linux, Gunicorn, NGINX