Thursday 15 May 2025 at 8:30 AM EDT, 10:30 PM AEST, 02:30 PM CEST  By Daswin De Silva (La Trobe University, Australia) and Milos Manic (Virginia Commonwealth University, USA) Joint webinar with IES Young Professionals Committee Register now using the link below: https://attendee.gotowebinar.com/register/4923257274036950111 Abstract: Join us for an insightful webinar on "Harnessing AI and GenAI for Smarter Industrial Systems: Use Cases and Future Trends." The integration of Artificial Intelligence (AI) and Generative AI (GenAI) is transforming the industrial landscape, optimizing operations, enhancing productivity, and improving safety. By leveraging AI’s capability to analyze vast datasets and GenAI’s ability to create innovative solutions, industries can develop smarter, more efficient, and safer systems. This session will cover two key areas of application. First, we will explore the use of Deep Neural Networks for developing anomaly detection systems in vehicle communication systems. These cutting-edge systems, utilizing state-of-the-art transformer neural networks, proactively identify potential threats, ensuring secure and reliable vehicle communications. Next, we will dive into the latest advancements in GenAI, discussing how these tools are being effectively used in industrial applications. We will explore the opportunities and challenges GenAI presents, examining real-world use cases and the future potential of this technology in transforming industries ...

Tuesday 27 May 2025 at 2:00 PM CET, 8:00 AM EST By Waldemar Bauer and Jerzy Baranowski (AGH University of Kraków) Register now using the link below: https://attendee.gotowebinar.com/register/1086876486643438940 Abstract: In the increasingly complex landscape of industrial processes, the ability to diagnose faults and model degradation is critical for maintaining efficiency and reducing downtime. This webinar, titled "Applying Statistical Methods in Industrial Process Diagnostics and Degradation Modelling," will explore the state of the art in this field and address key challenges, such as data scarcity, the lack of robust benchmarks, and the pervasive uncertainty in industrial environments. We will discuss the advantages of applying advanced statistical methods, highlighting approaches like Bayesian modeling, functional data analysis, Monte Carlo computation, and Bayesian neural networks. These methodologies offer powerful tools for enhancing diagnostic accuracy and predictive modeling. Furthermore, the webinar will introduce the Laboratory for Investigation of Fault Diagnosis and Degradation, a hub for cutting-edge research, and provide an overview of upcoming benchmark datasets that will serve as crucial resources for the community. This session is designed for professionals and researchers looking to deepen their understanding of statistical methods in industrial diagnostics and to stay at the forefront of this rapidly evolving field ...