Sena Özgünay Hakverdi

* PhD student of ANITI at LAAS-CNRS and Toulouse Mathematics Institute in industrial collaboration with Aumovio (Continental Automotive) Toulouse. * Representative of ANITI phd students and postdocs. Thesis subject: Robust anomaly detection in dynamic manufacturing environments. Objectives: - Study of defects or malfunctions in production lines of electronic components for automotive systems. - Anomaly detection and diagnosis in heterogeneous data flows using Graph Neural Networks (GNNs). - GNN Explainability.

Apprenticeship in data science: - Big data exploration & analysis. - Anomaly detection in the production lines of electronic components in automotive systems. - Unsupervised anomaly detection methods (One-Class SVM, Isolation Forest, Local Outlier Factor).

Project "MySpade" of SogetiLabs: an innovative project to promote the integration and inclusion of new employees within the Capgemini group. - CV recommendation systems - Use of machine learning algorithms in Python - Natural Language Processing - Text classification - Agile Methods - AzureDevOps

Project TEMOG, Galatasaray University For further information: https://sites.google.com/view/temog/ana-sayfa

MApI3 Master's program is based on a complementary approach and combines knowledge of statistics, analysis, numerical calculus, optimization, and algorithms. This is to meet the current needs of industry and services that require the use of mathematical tools and methods at all levels of design, production, and management of goods and services. It's a strong formation in various areas of applied mathematics with a major focus on data science: - Data Science / Mathematics of Machine Learning / Big Data - Partial differential equations (PDEs) / Numerical methods for PDEs. - Algorithmic and scientific calculus - Optimization / Operational Research / Image, Signal, and Simulations - Probability / Simulation of randomness / Statistics - Gaussian processes and sensitivity analysis for computer experiments - Python / R - C++ / High-Performance Computing

A strong background in pure mathematics with a solid background in Python: - Linear algebra / Abstract algebra - Partial differential equations - Differential-Algebraic-Analytical geometry - Analysis of one variable / Multivariate analysis - Functional analysis / Theory of complex functions - Physics - Probability - Topology - Applied mathematics - Programming with Python

Erasmus+ Student Exchange Programme in the fifth semester of undergraduate studies. Attended courses: - Integration and Probability - Differential and Integral Calculus - Techniques of Numerical Analysis, - Statistics - Python / R / C++