NSF Workshop on
Real-time Learning and Decision Making iN Dynamical Systems
February 12-13, 2018
Welcome to the NSF workshop on Real-time Learning and Decision Making in Dynamical Systems
The goal of the workshop is to have a group of leading experts that have complementary background (in the area of control, signal processing, machine learning, communication, power and energy, autonomous systems, etc.) to cross the bridge among various research areas and shape the research paradigm that arises from many real-time data-driven dynamical systems. Specifically, we have identified the following data-rich dynamical engineering systems:
- Power and Energy Systems
- Autonomous Systems
- Information Systems
The new NSF headquarters in Alexandria, VA
Topics for discussions include various real time learning approaches for the engineering systems (such as deep learning architectures, model-based learning, model-free learning, reinforcement learning, etc.), the data representation for the engineering systems (including the research problems in feature extraction, graphical models, real time unsupervised learning, etc.), and the potential solutions for closing the loop around data. The workshop will examine control, signal processing, machine learning, communication, power and energy, transportation, etc.
Participation in this workshop is by invitation only.