IES is proud to sponsor the IEEE IES Industrial Innovation Conclave 2025 in Hyderabad, India. With the theme “AI Frontiers: Pioneering Intelligent Solutions in Industry,” this conclave will explore the transformative impact of artificial intelligence on industrial applications.

Power Up conference served as a platform for experts and innovators to explore the latest trends in sustainable technology. Held in April 2024 in Tunisia, it celebrated cutting-edge advancements while highlighting the significant contributions of women in these fields.

INDIN 2025 will take place 12-15 July 2025 in Kun Ming, China. The 23rd IEEE International Conference on Industrial Informatics will provide a forum for presentation and discussion of the state-of-art and future perspectives of industrial information technologies.

This paper proposes an adaptive event-triggered output feedback fault-tolerant control scheme for a class of uncertain nonlinear systems with unknown actuator faults. The proposed mechanism reduces both the communication and the computation burdens.

This paper introduces an aggregated swing equation model tailored for heterogeneous grid-forming and grid-following converter systems. The proposed model is able to provide useful insights into their transient dynamics and interaction mechanisms. 

By Victor Huang, K. Gopakumar, Shihua Li, Leila Parsa, Juan Jose Rodriguez Andina – 18 Oct 2023

This panel was presented at IECON 2023 in Singapore (Video duration: 0:54)

Wednesday 19 March 2025 at 4:00 PM PKT, 12:00 PM CET, 6:00 AM EST

By Hadeed Ahmed Sher, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Pakistan

This webinar will examine the challenges and limitations of current technologies to identify line-to-line and line-to-ground faults in solar photovoltaic (PV) arrays, and propose methods to detect, classify, and localize faults without requiring the disconnection of the PV array.

Friday 4 April 2025 at 2:00 PM CET, 8:00 AM EST

By Rodica Mihai (NORCE Norwegian Research Centre, Norway)

Automation and autonomous decision-making in critical operations through AI systems have a huge potential to improve efficiency and safety of these operations. Key learnings to be presented include description of needs, challenges and current gaps in complex AI systems in critical operations based on the experience from the associated use case considered.