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SUMMARY:Gen AI Application for Industrial Automation
DESCRIPTION:The live presentation of this event has already taken place. \nPlease view the PDF slides here or watch the video recording below: \nWebinar details\nGenerative AI is transforming industrial automation by enabling intelligent systems that not only optimize existing processes but also generate adaptive solutions in real time. By integrating large language models (LLMs) and multi-modal AI frameworks with industrial control systems\, organizations can automate complex decision-making\, enhance predictive maintenance\, and improve production efficiency. Applications include intelligent process optimization\, automated report generation\, failure prediction\, and contextual response systems that adapt to real-time data from sensors\, machines\, and enterprise systems. These capabilities reduce downtime\, lower operational costs\, and support continuous process improvement across manufacturing and industrial operations. \nThe webinar will explore practical implementations of Gen AI in industrial automation\, focusing on how technologies such as Retrieval-Augmented Generation (RAG)\, reinforcement learning\, and model distillation are deployed to build scalable\, efficient\, and interpretable AI solutions. Emphasis will be placed on use cases such as real-time monitoring\, automated quality control through computer vision\, and dynamic workflow optimization. Technical considerations including data integration\, edge deployment\, model reliability\, and safety in automated environments will also be addressed. This session aims to provide a clear understanding of how Gen AI can drive innovation and operational excellence in industrial settings. \n\nThe webinar will be recorded and will be sent out to registered attendees afterwards.\nA certificate of attendance will be provided to attendees who request one near the end of the live webinar session.\nPlease note: the time stated on this event is in UTC. You will need to convert this to your own time zone.\n\nKey takeaways from this webinar\n\nUnderstand how Generative AI technologies can be applied to optimize and automate industrial processes in real-time.\nLearn about the integration of large language models\, sensor data\, and edge computing for predictive maintenance and dynamic workflow management.\nGain insights into deploying scalable and interpretable Gen AI solutions within existing industrial automation infrastructure.\n\nRelated courses\nThis webinar/topic relates to our school of Industrial Automation\, Instrumentation and Process Control and is particularly found in the following courses: \n\n52886WA Advanced Diploma of Industrial Automation Engineering\n52872WA Advanced Diploma of Robotics and Mechatronics Engineering\nOnline – Bachelor of Science (Industrial Automation Engineering)\nGraduate Certificate in Industrial Automation and Machine Learning\nGraduate Diploma of Engineering (Industrial Automation)\nOnline – Master of Engineering (Industrial Automation\n\nTo learn more about tuition fees\, please click here. \nAbout the presenter\n \nDr. Krutika Shahabadkar\, EIT Lecturer\, Swinburne Lecturer and Tutor and Gen AI Research Engineer in Studiosity \nDr. Krutika Shahabadkar is an AI Engineer and Researcher with a strong foundation in developing end-to-end machine learning and Generative AI systems across healthcare\, industrial domains\, and academic research. Her work centers on integrating large language models (LLMs)\, Retrieval-Augmented Generation (RAG)\, and real-time sensor data to create intelligent\, scalable solutions that support enhanced decision-making in complex and dynamic environments. \nDr. Shahabadkar brings expertise in fine-tuning LLMs\, applying reinforcement learning with human feedback (RLHF)\, and deploying AI models across both cloud and edge infrastructures. She is dedicated to designing systems that are not only technically sound but also aligned with real-world needs\, with a particular focus on low-resource and high-impact settings. \nBeyond her research and engineering contributions\, Dr. Shahabadkar has taught postgraduate courses in Data Analytics\, Machine Learning\, and Artificial Intelligence. She has mentored students in both theoretical and applied aspects of AI\, fostering the next generation of data scientists and engineers. Her collaborative work spans interdisciplinary teams including clinicians\, engineers\, and policymakers\, with an emphasis on delivering ethical and impactful AI solutions. \nHer technical skill set includes proficiency with tools and platforms such as AWS SageMaker\, Azure\, TensorFlow\, PyTorch\, Hugging Face\, Docker\, and CI/CD pipelines. Passionate about responsible AI\, Dr. Shahabadkar is committed to building systems that deliver measurable value while advancing equitable access to technology.
URL:https://www.eit.edu.au/event/gen-ai-application-for-industrial-automation/
LOCATION:Online
CATEGORIES:Technical Engineering Topics Webinar
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