Résumé
Guided by a profound curiosity for science and the mysteries of the universe, I am a PhD candidate with a commitment to exploring transformative technologies that address complex, real-world challenges. With experience across software engineering and data science, I strive to bridge knowledge with innovation, motivated by the belief that technology, when thoughtfully applied, holds the potential to elevate our shared world. My work is driven by a desire to learn, adapt, and contribute meaningfully, embracing each challenge as a step toward a more interconnected, sustainable future.
Expériences professionnelles
Cifre phd candidate
Savoye , Dijon - THESE
De Mai 2024 à Aujourd'hui
Phd candidate
Savoye
Depuis le 02 novembre 2024
PhD Candidate on "Embedded AI and Distributed Learning Systems in a Predictive Maintenance Context"
Developing cutting-edge predictive maintenance solutions for Savoye’s robotic logistics systems through embedded AI and distributed learning. This research, focuses on real-time anomaly detection, federated learning architectures, and probabilistic AI models. By integrating hardware-based AI at the edge, the project aims to reduce downtime, optimize costs, and improve sustainability in automated warehousing.
Artificial intelligence researcher
Savoye
De Mai 2024 à Octobre 2024
Probabilistic AI on Predictive Maintenance
Data and software engineer
Digitalised
De Février 2023 à Août 2023
Developed DigiScore, a comprehensive benchmarking tool evaluating digital marketing performance across key areas like SEO, social media, and advertising. Using 300+ metrics from APIs, websites, and unconventional sources, DigiScore leverages automation, web scraping, and machine learning to provide actionable insights.
Implemented multi-layer scoring logic and min-max normalization for fair metric aggregation, allowing real-time competition analysis. Reduced analysis time from hours to minutes through optimized dataflows, while ensuring a modular architecture for scalability and long-term adaptability. DigiScore combines rigorous methodology with technology, translating complex data into clear strategy recommendations for businesses.
Formations complémentaires
Master of Science
Université de technologie de Compiègne - Machine Learning and Optimization of Complex Systems
2022 à 2023
Master of Science
Polytechnic University Of Tirana - Computer Engineering
2021 à 2023
Bachelor
Polytechnic University Of Tirana - Electronic Engineering
2018 à 2021
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