MDPI’s Journal Cluster of Mechanical Manufacturing and Automation Control Webinar | The Convergence of Foundation Models and Autonomous Systems
Meet Our Speakers
Prof. Dr. Joaquim de Curtò i Díaz
Department of Computer Applications in Science & Engineering, BARCELONA Supercomputing Center, 08034 Barcelona, Spain, Escuela Técnica Superior de Ingeniería (ICAI), Universidad Pontificia Comillas, 28015 Madrid, Spain, Estudis d'Informàtica, Multimèdia i Telecomunicació, Universitat Oberta de Catalunya, 08018 Barcelona, Spain;
Prof. Dr. De Curtò is a tenured Recognised Researcher in the Department of Computer Applications in Science & Engineering, Group of Dual Technologies, of the BARCELONA Supercomputing Center, he is also a Professor (Profesor Asociado Colaborador - Doctor) at the School of Engineering (ICAI), in the department of Electronics, Control Systems and Communications at Universidad Pontificia Comillas in Madrid. He holds a PhD in Computer Science from Universitat Politècnica de València (2023), an MSc in Multimedia Information Technology (EE Dept.) from City University of Hong Kong (2015), and an MSc in Telecommunication Engineering from Universitat Autònoma de Barcelona / Universitat Politècnica de Catalunya (2013).
He has more than 40 articles published in indexed journals and internationally recognized conferences, on topics of Vehicular Technologies, IoT, AI and Space Mission Design. His h-index is 14 and his works have been cited around 800 times according to Google Scholar.
Journal Cluster-6
The Convergence of Foundation Models and Autonomous Systems
This webinar provided a valuable forum on the convergence of foundation models and autonomous systems. The presentations addressed both resilient reinforcement learning for fail-operational systems and the integration of foundation models with UAV-IoT technologies for smart city applications, including traffic optimization and cooperative perception. Together, the talks highlighted important research directions for building more adaptive, reliable, and intelligent autonomous systems.
The invited MDPI webinar featured contributions from two speakers on foundation models for smart city applications. Prof. Dr. J. de Curtò (BSC-CNS / ICAI Comillas) presented research on LLM-driven UAV-IoT traffic optimization, demonstrating congestion and CO₂ reductions in urban simulations through real-time LLM integration with a microscopic traffic simulator, before connecting these results to LLM-based social influence in multi-agent systems and foundation model cybersecurity for IoT networks, as well as touching on multimodal sensor fusion with LLMs and adaptive wireless communications guided by foundation models.
In this section, you will find the recordings of this webinar to watch, re-watch and share with your colleagues!
Emerging Paradigms in AI, Autonomous Systems, and Intelligent Technologies
Edited by Florian Ion Tiberiu Petrescu, Liviu Marian Ungureanu, Iulian Sorin Munteanu and Péter Galambos
Deadline for manuscript submissions: 1 April 2026
Advances in Autonomous Underwater Drones: 2nd Edition
Edited by Daxiong Ji, Asiya Khan, Dena Bazazian and Mohd Hisham Bin Nordin
Deadline for manuscript submissions: 28 May 2026
Advances in Networks for Transport Infrastructure Management and Safety
Edited by Apostolos Anagnostopoulos, Nawaf Alnawmasi and Athanasios (Akis) Theofilatos
Deadline for manuscript submissions: 31 July 2026
Emerging Trends in Air Traffic Flow and Airport Operations Control
Edited by Lei Yang, Yan Xu and Yutong Chen
Deadline for manuscript submissions: 31 August 2026
Emerging Approaches to Intelligent and Autonomous Systems
Edited by Emmanouil Tsardoulias and Andreas L. Symeonidis
Deadline for manuscript submissions: 30 November 2026
Reinforcement Learning for Fail-Operational Systems with Disentangled Dual-Skill Variables
by Taewoo Kim and Shiho Kim
Technologies 2025, 13(4), 156; https://doi.org/10.3390/technologies13040156
by Álvaro Moraga , J. de Curtò, I. de Zarzà and Carlos T. Calafate
Drones 2025, 9(4), 248; https://doi.org/10.3390/drones9040248
Automation in Intelligent Transportation Systems
Edited by Chen Lv
MDPI’s cluster of mechanical manufacturing and automation control aims to publish cutting-edge research in the field of aerospace, automation, drones, machinery, manufacturing, robotics, and advanced technologies, including integrated AI, IoT, and advanced control systems. These journals will collaborate to offer the scientific community the latest research advances and discoveries within the field of automation, Industry 4.0, smart manufacturing, robotics, and aerospace technologies. Find more.