Niaussat Victor


Personal Information

  • Name: Niaussat Victor
  • Position/Title: AI systems Engineer
  • Department: Thales AVS FLX SAS

Professional Background

  • Briefly describe your professional background and area of expertise:

    I hold a Master’s degree in Data Science & Artificial Intelligence from Ecole Centrale de Lille, along with a Master’s in Mathematics from the University of Lille. 

    I have a background in artificial intelligence and data science, specializing in aerospace applications. Currently, I work as an AI Systems Engineer at Thales AVS, where I develop and industrialize machine learning and AI algorithms to enhance flight safety and efficiency. My expertise includes physiological state detection, data analysis, and human factor research.

  • What inspired you to pursue a career in this related field, e.g.,aviation etc?

    The intersection of AI and aerospace fascinated me because of its potential to enhance safety, efficiency, and human-machine collaboration in critical environments.

    Working in this field allows me to combine AI research with real-world applications that have a direct impact on flight safety and the future of aviation technology.

"My work directly contributes to the EPIIC project’s overall goal of developing next-generation fighter aircraft technologies by enhancing pilot safety and cognitive awareness through AI-driven physiological monitoring."

Role in EPIIC

  • What is your role in the EPIIC project?

    In the EPIIC project, I work in Work Package 7 (WP7) for Thales AVS, focusing on research related to four physiological states: spatial disorientation, mind wandering, mind blanking, and loss of consciousness. I am reviewer in Work Package 8 (WP8).

    Through this work, I aim to enhance pilot safety and situational awareness using advanced AI-driven monitoring solutions.

  • How does your work contribute to the overall goals of the EPIIC project?

    My work directly contributes to the EPIIC project’s overall goal of developing next-generation fighter aircraft technologies by enhancing pilot safety and cognitive awareness through AI-driven physiological monitoring. 

    By researching spatial disorientation for example, I help improve pilot state detection and real-time monitoring.

  • Can you describe your main responsibilities and tasks?

    My work includes:

    • Defining experimental protocols for studying these physiological states.
    • Identifying relevant sensors and physiological markers for accurate detection.
    • Collecting and analyzing data, ensuring ethical compliance and human protection throughout the process.
    • Designing AI-based detection models, working on feature extraction from physiological signals and developing machine learning (ML) and deep learning (DL) models.
    • Contributing to the architecture of the Crew Monitoring System (CMS) for next-generation fighter aircraft by defining the necessary system components and integration strategies.

"One significant milestone our team has achieved is the development of models for detecting mind wandering, mind blanking, and loss of consciousness, which have shown very promising performance metrics for future applications."

Project Insights

  • What do you find most exciting about working on the EPIIC project?

    What excites me most about working on the EPIIC project is the opportunity to have the privilege of collaborating with the biggest contributors in aviation and military aviation in Europe. Being part of a project that will define the future of combat aviation motivates me to innovate and contribute to making flying more efficient.

  • What has been the most challenging aspect of your work on this project?

    The most challenging aspect of my work on the EPIIC project has been designing an effective experimental protocol to ensure high-quality data collection. This requires planning to anticipate every step necessary for accurate data labeling and defining the ground truth for the physiological and cognitive states we are studying.

    It also involves determining reliable methods to induce these states in controlled environments and ensuring proper synchronization and data integrity during the collection process. Balancing these technical and methodological challenges is critical to developing robust AI models for pilot monitoring.

  • Can you share a significant milestone or achievement your team has reached so far?

    One significant milestone our team has achieved is the development of models for detecting mind wandering, mind blanking, and loss of consciousness, which have shown very promising performance metrics for future applications. Additionally, our data collection efforts related to spatial disorientation have been particularly successful, as we have managed to induced this complex state effectively in controlled environments. This dataset holds great potential for advancing our understanding and improving detection capabilities in real-world aviation scenarios.

"What excites me most about working on the EPIIC project is the opportunity to collaborate with the biggest contributors in aviation and military aviation in Europe. Being part of a project that will define the future of combat aviation motivates me to innovate and contribute to making flying more efficient.."

Personal Experience

  • What have you learned during your time working on EPIIC?

    This experience has helped me develop stronger communication skills, enabling me to work on complex ideas more clearly and collaborate more efficiently with multidisciplinary teams.

  • How has this project influenced your professional development?

    Since this is my first job, working on the EPIIC project has been incredibly enriching for my professional development. It has given me the opportunity to collaborate with leading partners in the European aerospace industry and to contribute to a project that plays a key role in shaping the future of fighter aircraft.