Background
Recent advances in computational intelligence are reshaping the development of robotics,
sensing, and intelligent physical systems. Deep learning, machine learning, generative
AI, computer vision, neural networks, and swarm intelligence provide new methods for
perception, decision-making, adaptation, and interaction in complex environments. At the
same time, intelligent physical systems increasingly rely on the integration of sensing,
data-driven models, and computational methods to operate effectively in dynamic
real-world settings. This symposium will provide a forum for discussing current progress
at the intersection of computational intelligence and physical systems, with particular
attention to approaches that connect intelligent perception and learning with robotic,
sensing, and interactive applications. It will also support exchange across related
areas of electrical engineering, computing, and intelligent system research.
The symposium, which serves as a specialized session of the 6th
International Conference on Computing Innovation and Applied Physics (CONF-CIAP 2027),
will focus on computational intelligence and applications.
Goal/Rationale
The symposium aims to bring together researchers working on computational intelligence,
robotics, sensing, and related intelligent systems to exchange recent advances and
identify common technical challenges. Particular attention will be given to how
learning-based and data-driven approaches can improve perception, decision-making,
adaptability, robustness, and interaction in physical or sensor-rich environments. The
symposium will encourage discussion of methods that bridge algorithmic development and
practical system implementation, including deep learning, machine learning, generative
AI, computer vision, neural networks, and swarm intelligence. By providing a focused
setting for research presentation and discussion, the symposium seeks to promote
interdisciplinary exchange, facilitate communication among researchers working across
related areas, and explore emerging directions for computational intelligence in
robotics, sensing, and intelligent physical systems.
Scope
Participants are invited to contribute work related to computational intelligence and
its applications in robotics, sensing, and intelligent physical systems. Relevant themes
may include deep learning and machine learning methods; neural networks and swarm
intelligence; computer vision and image processing; intelligent sensing and perception;
robotic perception, control, and decision-making; generative AI for intelligent systems;
pattern recognition; adaptive and autonomous systems; multimodal sensing and data
fusion; and human-machine or human-computer interaction in intelligent physical
environments. Contributions addressing algorithmic methods, system design, experimental
applications, or interdisciplinary integration are welcome, particularly where
computational intelligence is used to improve the capability, adaptability, efficiency,
or interaction of physical and sensing systems.
Computational Intelligence for Robotics, Sensing,