PhD Student in Applied Mathematics| Machine Learning|Uncertainty Quantification|
Université Polytechnique Hauts-de-France (UPHF) and Ecole Des Mines de Sainte-Etienne (EMSE)
Welcome to my personal website! I am a PhD candidate in Applied Mathematics with a specialization in Machine Learning at the Université Polytechnique Hauts-de-France (UPHF), in collaboration with the École des Mines de Saint-Étienne (EMSE).
My research focuses on Gaussian processes (GPs) and their extensions to multi-task learning and structured modeling. I develop probabilistic models and advanced kernel methods to analyze complex mechanical systems, integrating physical constraints and uncertainty quantification.
This work bridges theoretical advancements and practical applications, contributing to cutting-edge solutions in simulation, optimization, and uncertainty quantification for mechanical and computational models. Through Gaussian process models, I aim to improve the efficiency, interpretability, and predictive capabilities of machine learning methods in engineering and physics-driven problems.
Campus Mont Houy
Département de Mathématiques (DMATHS)
Bât. Abel de Pujol 2
59313 Valenciennes Cedex 9, France
Email: RazakChristophe.SabiGninkou@uphf.fr
Email: razsabigninchrist@gmail.com
Email: sabigninkou.razakchristophe@imsp-uac.org
LinkedIn: linkedin.com/in/razak-christophe-sabi-gninkou
GitHub: github.com/SABI-GNINKOU
ResearchGate: researchgate.net/your-profile
PhD in Applied Mathematics (Machine Learning Specialization)
Research focus: Development of advanced probabilistic and algorithmic methods for modeling complex mechanical systems.
Master's in Statistics and Machine Learning (PGSM Scholarship recipient of FSMP).
Specialization: Mathematical statistics, machine learning, and data science.
Master's in Statistics-Probability
Research-oriented program with CEASMA Scholarship. Developed expertise in statistical techniques and Bayesian methods.
Université Nationale des Sciences, Technologies, Ingénieries et Mathématiques (UNSTIM), Benin.
Acquired foundational skills in programming, statistics, and numerical optimization.
Organization: EDF Systems Department, Paris Saclay
Focus: Bayesian inference for estimating reliability parameters of electrical equipment using MCMC methods to analyze Weibull models with censored data.
Delivered Python algorithms for automating analyses and authored detailed reports.
Organization: IMSP, Benin
Focused on integer-valued time series analysis with heteroscedasticity and periodicity. Enhanced forecasting accuracy by addressing seasonality and complex data structures.
Organization: CERFIG, Conakry, Guinee
Institution: IMSP, Benin
Conducted Python and R workshops, focusing on practical programming skills and data analysis techniques.
Topic: Gaussian Process Modeling of Mechanical Random Fields: A Comprehensive Study from Simulation to Identification
Supervisors: I am working under the supervision of Rodolphe Le Riche, Yacouba Boubacar Maïnassara, Andres Lopez-Lopera, Franck Massa, and Lucas Reding.
Funding: Supported by the ANR JCJC GAME program.
Below is a list of certifications I have completed, covering topics in deep learning, AI, and scientific writing.