AI-based Discovery and Innovation

Goals

This VIP team aims to develop systematic AI approaches, particularly manifold-learning techniques, to uncover hidden governing rules across disciplines such as physics, biomedicine, psychology, art, and finance. Their research focuses on two main thrusts: (1) designing innovative devices and systems using nanotechnology for diverse engineering challenges, and (2) creating intelligent learning algorithms to extract valuable knowledge from large datasets, including images, spectra, and dynamic variations. These efforts seek transformative impacts in applications ranging from medical imaging, brain probing, and quantum information processing to software for detecting subtle patterns in biomarkers, financial markets, and social media data.

Issues Involved or Addressed

A wide range of research topics are investigated including new manifold learning (and other AI-based) approaches for 1) understanding the dynamics and designing nanodevices and systems for several applications (e.g., medical sensing and imaging, LiDAR, optical computing, and quantum information processing), 2) for learning patterns in data in a wide range of disciplines (e.g., healthcare, financial markets, social media). The resulting knowledge will be used to fabricate and test new optical and bioengineered systems as well as intelligent data-processing software.