Industrial AI Lab
School of Mechanical Engineering,
Chung-Ang University
중앙대학교 산업 인공지능 연구실
Industrial AI Lab
School of Mechanical Engineering, Chung-Ang University
중앙대학교 산업 인공지능 연구실
NEWS
Recent News at IAI Lab
NEWS
Recent News
at IAI Lab
OUR VISION
Engineering Meets AI,
AI Meets Engineering.
The overarching objective of the IAI Lab is to pioneer AI-driven advancements by leveraging the strength of engineering background. By integrating the knowledge of diverse engineering disciplines ranging from mechanical engineering, physics, and computer science, we harness the full potential of artificial intelligence (AI) in redefining engineering processes and outcomes. We are dedicated to developing advanced AI methods based on engineering and data-driven insights, enabling us to model the complexities of various engineering systems well. Our strategies extend beyond conventional and existing approaches by empowering AI-enabled engineering, thereby facilitating unprecedented analysis, decision-making, optimization, and so on. Through this synergy of engineering and AI, the IAI Lab strives to pioneer a new wave of AI innovation, elevating the engineering landscape and further making the future industry smarter and more efficient.
RESEARCH THRUST
Towards Seamless Industrial AI
IAI Lab conducts extensive research to seamlessly integrate artificial intelligence (AI) across various industrial aspects, from physical phenomena to manufacturing processes, aiming to enhance efficiency, predictability, and intelligent functionality.
Generative/Agentic AI for Engineering
Collaborative and exploratory AI-driven decision-making for autonomous engineering process
AI for Future Manufacturing
AI-enabled intelligent and autonomous manufacturing enabling adaptive, efficient, and resilient production
Extended Physical AI (E-PAI)
Physical intelligence with mechanistic understanding and knowledge integration for generalizable real-world interaction
CORE APPLICATIONS
AI+X Impacts
OUR VISION
The overarching objective of the IAI Lab is to pioneer AI-driven advancements by leveraging the strength of engineering background. By integrating the knowledge of diverse engineering disciplines ranging from mechanical engineering, physics, and computer science, we harness the full potential of artificial intelligence (AI) in redefining engineering processes and outcomes. We are dedicated to developing advanced AI methods based on engineering and data-driven insights, enabling us to model the complexities of various engineering systems well. Our strategies extend beyond conventional and existing approaches by empowering AI-enabled engineering, thereby facilitating unprecedented analysis, decision-making, optimization, and so on. Through this synergy of engineering and AI, the IAI Lab strives to pioneer a new wave of AI innovation, elevating the engineering landscape and further making the future industry smarter and more efficient.
RESEARCH THRUSTS
IAI Lab conducts extensive research to seamlessly integrate artificial intelligence (AI) across various industrial aspects, from physical phenomena to manufacturing processes, aiming to enhance efficiency, predictability, and intelligent functionality.
CORE APPLICATIONS
AI+X Impacts
MOMENTS
Lab Activities
Prof. Sooyoung Lee gives an invited seminar at the Korean Society for Noise and Vibration Engineering (유망과학자 세션).
Title: "AI Innovations in Noise and Vibration Engineering"
Abstract: This seminar explores the latest advancements of artificial intelligence (AI) in the field of noise and vibration engineering, highlighting how AI-driven technologies are transforming the ways in which noise and vibration are analyzed, controlled, and mitigated across diverse scientific and engineering disciplines. The presentation will mainly focus on a series of case studies demonstrating the novel development and integration of AI, aimed at establishing more effective prediction models, enhancing conventional signal processing methods, and accelerating the design of novel materials and structures. It will particularly emphasize physics-guided and mechanism-inspired AI approaches as innovative perspectives in AI-aided engineering, designed to enhance generalization and predictive capabilities tailored for noise and vibration challenges. We believe that participants will gain valuable insights and explore future prospects in harnessing AI methodologies to address a broad spectrum of applications within the noise and vibration domains.