🎓About Me
I am a PhD candidate in Applied Mathematics working on probabilistic modeling and surrogate learning for complex mechanical systems.
My thesis is carried out at UPHF and EMSE, within the ANR JCJC GAME project.
🎓 My PhD focuses on Gaussian Process Modeling of Mechanical Random Fields: A complete study from simulation to identification.
Key Highlights:
- ✔ Develop machine learning algorithms, specifically Gaussian processes, for modeling and identifying mechanical random fields.
- ✔ Design specialized covariance kernels tailored to the physics of mechanical systems.
- ✔ Implement and optimize complex computational codes for large-scale simulations and real-world applications.
- ✔ Apply these innovations to engineering challenges, bridging data-driven methods and physical models.
This research advances the integration of machine learning and computational mechanics, improving the accuracy and efficiency of simulations in engineering.
✉️ Contact
Université Polytechnique Hauts-de-France
Département de Mathématiques (DMATHS), Bât. Abel de Pujol 2
59313 Valenciennes Cedex 9, France
Email: RazakChristophe.SabiGninkou@uphf.fr
Other: razsabigninchrist@gmail.com / sabigninkou.razakchristophe@imsp-uac.org
📄 Curriculum Vitae
Full CV available on request or downloadable version coming soon.
🔀 PhD Thesis Information
Title: Gaussian Process Modeling of Mechanical Random Fields: A complete study from simulation to identification
Funding: ANR JCJC GAME
Research Interests
- Gaussian Processes, Machine Learning, Multi-task learning, Functional Data Analysis, Uncertainty Quantification, Inverse Problems.
📖 Publications & Talks
CIROQUO Scientific Days — Poster Presentation
Location: IFPEN, Paris — 13–14 November 2025
I participated in the CIROQUO Scientific Days, an event bringing together academic and industrial partners working on optimization and uncertainty quantification for computationally expensive numerical simulations. More information is available on the official website: https://ciroquo.ec-lyon.fr/evenements.html . During the event, I presented a poster showcasing my research on Multitask Gaussian Processes for scalable modeling of complex systems with functional covariates.
📚 Teaching
Université Polytechnique Hauts-de-France
- 2025–2026 – Discrete Probability and Statistics (Bachelor 2, Computer Science)
→ Preparation of exercises, supervision of tutorials, and evaluation of students.
Institut National des Sciences Appliquées (INSA Hauts-de-France)
- 2025–2026 – Probability and Statistics (Engineering students)
→ Practical sessions, data analysis projects, and applied statistics guidance.
🏅Certifications
- Improving Deep Neural Networks – DeepLearning.AI | Verify
- Structuring Machine Learning Projects – DeepLearning.AI | Verify
- Neural Networks and Deep Learning – DeepLearning.AI | Verify
- Responsible AI: Applying AI Principles – Google Cloud | Verify
- Introduction to Generative AI – Google Cloud | Verify
- Introduction to Responsible AI – Google Cloud | Verify
- Introduction to Large Language Models – Google Cloud | Verify
- How to Write and Publish a Scientific Paper – École Polytechnique | Verify