I'm
Victor MAYAUD
Data scientist, AI Engineer, Product Manager, Data engineer, Manager High-Tech
I am a 22-year-old student in my second year at EURECOM, studying data science. I'm passionate about new technologies and sciences. Determination and hard work best define me.
Lycée Etienne Mimard | Claude Fauriel | 2019 - 2022
This course was part of the French "Classes Préparatoires aux Grandes Écoles" (CPGE), specifically the PCSI (Physics, Chemistry, and Engineering Science) followed by PSI (Physics and Engineering), which are intensive programs designed to prepare students for competitive exams to enter engineering schools. This foundational program emphasized advanced scientific and mathematical concepts.
EURECOM | 2022 - 2024
Pursued a Master’s degree focusing on Data Science, which involved rigorous training in statistical methods, machine learning, and data processing technologies. This program aimed to develop skills necessary to analyze, interpret, and create data-driven solutions.
EDHEC Business School | 2024 - 2027
Enrolled in a Master’s program centered on Management, which is designed to combine advanced business and management strategies with leadership skills, preparing students to take on executive roles in various industries.
SKK Graduate School of Business | 2025
Haas School of Business | 2026 - 2027
Freelance | 2022 - 2023
Engaged in one-on-one tutoring sessions, focusing on enhancing students’ mathematical skills across various levels, tailoring educational approaches to individual needs.
Metal Design Concept | July 2023 - October 2023 (4 months)
Participated in the development of software capable of transforming images into precise models for the manufacturing of perforated decorative metal plates.
The "Machine Learning and Intelligent System" course, led by Maria A. Zuluaga, equips students with foundational Machine Learning techniques
Project 1 | Project 2 | Project 3The "Deep Learning" course, instructed by Pietro Michiardi, introduces a powerful approach within Machine Learning, particularly effective in areas like Computer Vision and Natural Language Processing
The "Image & Video Compression" course, taught by Jean-Luc Dugelay, focuses on critical compression techniques essential for efficient multimedia storage and transmission.
The "Basics on Reinforcement Learning" course, led by Fotios Stavrou, introduces the fundamental principles of Reinforcement Learning (RL), a notable technique in modern machine learning characterized by trial-and-error learning from feedback.
Project 1The "Semantic Web and Information Extraction Technologies" course, taught by Raphaël Troncy, explores the Semantic Web, an extension of the World Wide Web where web information and services are semantically defined.
Lab 1The "Algorithmic Machine Learning" course, instructed by Pietro Michiardi, focuses on providing a practical, algorithmic foundation for designing and using scalable machine learning algorithms, especially within the MapReduce programming model.
Project 1 | Project 2 | Project 3The "Mobile Application and Services" course, led by Navid Nikaein, explores the principal mobile platforms—Android, iOS, and PhoneGap/Web OS—and their ecosystems.
The "IoT Application Protocols" course, taught by Roberto Morabito, focuses on the specialized application-level protocols designed for the Internet of Things (IoT), considering the limited battery and CPU capacities of IoT devices.
Lab 1 | Lab 2 | Lab 3he "Database Management System Implementation" course, instructed by Paolo Papotti and Jean Flavien Bussotti, dives into the core aspects of database system implementation such as data storage, indexing, querying, query optimization, concurrency control, and transaction management.
Lab 1 | Lab 2The "Distributed Systems and Cloud Computing" course, led by Raja Appuswamy offers a comprehensive exploration of current trends and topics in distributed systems and cloud computing.
The "Digital Image Processing" course, taught by Jean-Luc Dugelay, focuses on equipping students with the fundamental skills necessary to utilize computer algorithms for processing digital images.
The semester project titled "Beyond the Smile: Capturing Micro Expressions with Event-based Vision" explores the utilization of event-based vision systems to detect and analyze micro-expressions. Leveraging high temporal precision of event cameras, the project integrates these with advanced machine learning algorithms to enhance the accuracy and speed of micro-expression recognition. The findings suggest significant potential for applications in fields like psychology, security, and human-computer interaction, offering a deeper understanding of human emotions beyond traditional methods.
Report Semester Project
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