Special Session “SMCs-DAY: Data-Driven Control for Human-Machine Systems”

The rapid advancement of sensor technologies, machine learning, and computational power is enabling a paradigm shift in the control of Human-Machine Systems (HMS), moving from model-based approaches toward data-driven methodologies. This special session focuses on data-driven control strategies tailored for HMS, where human operators interact with and influence complex, adaptive systems.

Topics of interest include adaptive control, system identification, and reinforcement learning techniques that learn control policies directly from interaction data. Emphasis is placed on safety, interpretability, and real-time adaptability in human-in-the-loop and shared autonomy settings. The session welcomes contributions that explore theoretical developments, algorithmic innovations, and real-world applications spanning domains such as collaborative robotics, intelligent vehicles, assistive technologies, and cyber-physical human systems.

The goal is to foster interdisciplinary discussion and present cutting-edge approaches to enabling intelligent, cooperative, and trustworthy control in data-rich human-machine systems.

The topics of interest include:

      Data-Driven Control

      Human-Machine Interaction

      Human-in-the-Loop Systems

      Adaptive Control

      System Identification

      Reinforcement Learning

      Shared Autonomy

      Human-Robot Collaboration

      Intelligent Decision Support

      Safety-Critical Control

      Trust and Interpretability in AI

      Online Learning Systems

      Cognitive Feedback Loops

      AI in Control Systems 

Papers or Abstract must be submitted electronically for peer review through EasyChair by June 2025. 

Important: During abstract submission on the Automatica.it 2025 platform, please make sure to select the checkbox “IEEE SMC Italy Chapter” under the track type,  as well as at least one of the other four categories (Systems Analysis and Control, Applications in Control Engineering, Networked Systems, Robotics and Automotive) to facilitate selection of reviewers at submission stage.

Contributions should consist of an extended abstract of no more than 2 pages (format compliant to conference requirements), including figures and references.

Contributions can be original works, previously published works, or concise reports on research conducted in recent years that are accessible to the entire community. Submissions may also summarize the results of recently concluded or ongoing research projects or illustrate specific experimental applications of theoretical results.

Laura Giarré, Università di Modena e Reggio Emilia – Italy.
E-mail: laura.giarre@unimore.it

Giancarlo Fortino, Università della Calabria – Italy.
E-mail: giancarlo.fortino@unical.it

Graziana Cavone, Università degli Studi Roma Tre – Italy.
E-mail:  graziana.cavone@uniroma3.it

Giuseppe D’Aniello, Università degli Studi di Salerno – Italy.
E-mail: gidaniello@unisa.it