Multi modal streams of information arise naturally in many engineering contexts. Rough path theory is an area of mathematics that fuses the control theory of Sussmann, Brockett and Fleiss with the analysis of Young to form a calculus that can efficiently describe the interaction and evolution of complex oscillatory systems.
This presentation will showcase recent advancements in micro-robotic systems, focusing on the innovative application of non-contact optical manipulation using Optical Tweezers (OT). OTs are highly effective for precisely handling microscale objects, which is crucial for various biomedical applications. However, this technology encounters challenges, such as accurately localizing transparent microrobots in three-dimensional space. Moreover, controlling their rotation motions in non-parallel directions to the optical plane is challenging.
We are excited to invite you to the second edition of I-X Breaking Topics in AI conference sponsored by Schmidt Sciences. The conference will serve as a platform for sharing cutting-edge knowledge, discussing emerging trends, and fostering collaborative efforts to advance the field further. Our speakers will give overview talks outlining what they consider to be the exciting breakthroughs and future challenges in their area. The conference will also feature Flash Talks and Research Poster competitions.
Operator Learning is an emerging field at the intersection of machine learning, physics and mathematics, that aims to discover properties of unknown physical systems from experimental data. Popular techniques exploit the approximation power of deep learning to learn solution operators, which map source terms to solutions of the underlying PDE.
