Title: Data-driven Verification for Safe Autonomy: Reachability, Entropy, and Perception Contracts Abstract Todays verification technologies for autonomous and cyber-physical systems require detailed models which is one of the barriers that keep them from being widely used. In this talk, I will first present the basic idea of data-driven reachability analysis for systems with both black and white-box […]
Title: A Graph Neural Network Surrogate for Epitaxial Crystal Growth Abstract Predicting grain (crystal) formation and growth during alloy solidification is of great importance in additive manufacturing (AM) as it one of the key factors in determining the final microstructure and the mechanical properties of the printed part. Numerical simulations of grain formation involve moving […]
Title: Living Scenes: Creating and updating digital twins of evolving indoor scenes Abstract Buildings are like living organisms, i.e., they evolve over time due to interaction with natural phenomena and humans. How can we realistically maintain their digital twins throughout their lifespan? Or else, how can we maintain a living building model as the space is […]
Title: Transforming AI Practices: From Data Generation to Automated MLOps Abstract Agility enables swift adaptation to changing market needs and new technologies. Moreover, mature AI utilization necessitates a strategic shift, focusing on incorporating AI into core business operations to boost efficiency and drive innovation. Increasing agility and harnessing the power of mature AI, this presentation […]
Title: Operator learning for data-driven closure models of complex dynamical systems Abstract Closure models are widely used in simulating complex multiscale dynamical systems such as turbulence and Earth’s climate, for which direct numerical simulation that resolves all scales is often too expensive. For those systems without a clear scale separation, deterministic and local closure models […]
Detail Date: September 18, 2024 Time: 11:00 AM - 12:00 PM CST Location: https://iastate.zoom.us/j/95263587232?pwd=K1BVcURvWExFb3pUT000NlRwdFZsZz09 Title: Deep learning enabled computer vision metrology: from strain estimation to form measurement Abstract The embryo of Industry 4.0 has been transforming manufacturing into an autonomous, adaptive, and responsive paradigm while setting a higher standard for efficiency, accuracy, and reliability. These […]
Detail Date: October 9, 2024 Time: 11:00 am - 12:00 pm CST Location: 2004 Black Engineering or https://iastate.zoom.us/j/95263587232?pwd=K1BVcURvWExFb3pUT000NlRwdFZsZz09 Title: Understanding Reaction Mechanisms of Ammonia Synthesis through the Combination of Deep Reinforcement Learning and Density Functional Theory Abstract The Haber–Bosch (HB) process is the foundation of industrial ammonia (NH₃) production, essential for manufacturing nitrate-based fertilizers and […]
Detail Date: October 23, 2024 Time: 11:00 am - 12:00 pm CST Location: https://iastate.zoom.us/j/95263587232?pwd=K1BVcURvWExFb3pUT000NlRwdFZsZz09 Title: Economic Designs of Large Language Models Abstract Large Language Models (LLMs) are transforming many of aspects of the technology world and, importantly, also their commercial applications. Unlike standard machine learning technology development, enabling the use of LLMs in the e-commerce […]
Detail Date: November 6, 2024 Time: 11:00 AM - 12:00 PM CST Location: 2019 Morrill Hall or https://iastate.zoom.us/j/95263587232?pwd=K1BVcURvWExFb3pUT000NlRwdFZsZz09 Title: Deep Learning Meets Numerical PDEs: A Neural Differentiable Physics Approach for Predictive Modeling Abstract Predictive modeling and simulation play a critical role in understanding, predicting, and controlling complex physical processes across numerous engineering disciplines. Traditional numerical […]
Detail Date: November 20, 2024 Time: 11:00 AM - 12:00 PM Location: https://iastate.zoom.us/j/95263587232?pwd=K1BVcURvWExFb3pUT000NlRwdFZsZz09 Title: A Foray into Topological Learning from an Engineering Perspective Abstract Topological learning (TL), referring to a […]
