Title: The “Fatal Flaw” in AI Policy & Governance, and a Simple Yet Strategic Framework that May Help Abstract Much of policy and governance for AI can be divided into three broad categories. There are “soft law” mechanisms, such as ethics frameworks and guidelines. There are calls for and efforts toward creating new regulations or […]
Title: A Surface-based Approach to Soft Robotics Abstract Typical robots are designed to achieve a single function in a controlled environment and lack the ability to generalize to new tasks. In their quest to build more capable robots, engineers have explored many avenues, including artificial intelligence, reconfigurable robots, and leveraging deformable materials that naturally absorb […]
Title: Data-driven Optimization of HVAC Systems to Balance Airborne Infection Risk and Energy Use Abstract During the COVID-19 global pandemic, significant attention was paid to how the operation of building ventilation systems contributes to airborne transmission of pathogens via respiratory aerosols. Via increased filtration, outdoor-air ventilation, and other mechanisms, the effective residence time of these […]
The Richard and Carol Pletcher Seminar Series and TrAC host Lucy Zhang Title: Non-intrusive Coupling Strategies for Multiphysics Simulations Abstract In this talk, I will discuss computational strategies for multiphysics systems. Multiphysics involve multiple physical behaviors to be coupled for inter-related responses. To obtain stable, effective, and accurate coupled numerical solutions is not trivial. Traditional […]
Title: Nonlocal Operator Learning is All You Need Abstract During the last 20 years there has been a lot of progress in applying neural networks (NNs) to many machine learning […]
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 […]
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 […]
