Our goal is to address social problems based on innovative interdisciplinary approaches.

At ACSAD (Advanced Cognitive Systems and Data Science Research Group), we are committed to addressing concrete societal challenges through transdisciplinary research. Our work bridges the gap between academic knowledge and industrial innovation, using Artificial Intelligence (AI) as a key tool to develop solutions that directly impact the well-being of society.

What is our research focus?

We focus on real-world problems across various applications, from healthcare and energy to aerospace and drone operations. By integrating AI into these sectors, we strive to enhance efficiency, safety, and sustainability within critical infrastructures. Our approach leverages AI to address complex challenges, improving operational performance and optimizing systems to create innovative, safer, and more sustainable solutions across various industries.

Our mission is to promote transdisciplinary research and education, by creating new knowledge, and practical and innovative solutions in the fields of health, industry, energy, etc.

We define Advanced Cognitive Systems and Data Sciences as the applied research arena encompassing Industrial and Research Projects.

How we conduct our research

Our group operates through a collaborative approach, combining expertise from both universities and industry partners. This mixed method allows us to generate innovative, practical solutions that drive technological progress and contribute positively to society. We are committed to not only pushing the boundaries of AI but also ensuring that its applications serve the broader community by improving the quality of life and promoting sustainable development.

Ongoing projects

AI4HyDrop
  • An AI-based Holistic Dynamic Framework for a safe Drone’s Operations in restricted and urban areas. A SESAR3 Joint Undertaking project under grant agreement No 101114805 under European Union’s Horizon Europe research and innovation programme. Project webpage

Past projects

USEPE - U-space Separation in Europe  

 

  • A co-funded project by the EU under the H2020 Research and Innovation Programme, through the SESAR Joint Undertaking (grant agreement No 890378). Project webpage

logo usn usepe

 

“Identifying Network Failures in Large Network Topologies Using Machine Learning"
"Machine Learning for proximity sensors"
  • "Machine Learning for proximity sensors" In collaboration with IPR, Germany
"How to manage Technical Knowledge in High Tech growing SME"
  • “How to manage Technical Knowledge in High Tech growing SME” in collaboration with EDF, Induction

 

Calendar

Group leader

Cooperation with

  • Assist. Prof. Dr. Rina Komatsu
  • Nguyen Xuan Phuc Phan