Position Opening: Cyber-Physical Systems Program Director (CISE/CNS)

Position Announcement

The National Science Foundation (NSF) is seeking a qualified candidate for an Interdisciplinary (Cyber-Physical Systems Program Director) position within the Directorate for Computer and Information Science and Engineering (CISE), Division of Computer Network Systems (CNS) in Alexandria, VA.

Please find out more here: https://www.usajobs.gov/job/777342600

This position is open for a Rotational IPA assignment. Applications will be accepted from all US citizens who meet citizenship and eligibility requirements. 

IEEE SMARTCOMP 2024

Submitted by Amy Karns on

International Conference on Smart Computing (SMARTCOMP) is the premier conference on smart computing. Smart computing is a multidisciplinary domain based on the synergistic influence of advances in sensor-based technologies, Internet of Things, cyber-physical systems, edge computing, big data analytics, machine learning, cognitive computing, and artificial intelligence.

CPS:DFG Joint: Medium: Collaborative Research: Data-Driven Secure Holonic control and Optimization for the Networked CPS (aDaptioN)
Lead PI:
Anurag Srivastava
Co-PI:
Abstract

The proposed decentralized/distributed control and optimization for the critical cyber-physical networked

Performance Period: 01/01/2020 - 04/30/2022
Institution: Washington State University
Sponsor: National Science Foundation
Award Number: 1932574
Career: Learning-Enabled Medical Cyber-Physical Systems
Lead PI:
James Weimer
Abstract

Safety critical medical systems increasingly aim to incorporate learning-enabled components that are devel

Performance Period: 04/01/2024 - 03/31/2029
Institution: Vanderbilt University
Sponsor: National Science Foundation
Award Number: 2339637
CAREER: Game Theoretic Models for Robust Cyber-Physical Interactions: Inference and Design under Uncertainty
Lead PI:
David Fridovich-Keil
Abstract
The long-term goal of this project is to build flexible models and efficient algorithms for large-scale, multi-agent, and uncertain cyber-physical systems. In settings such as traffic management, for example, practitioners face fundamental challenges due to complex dynamics, hierarchical influence, noncooperative actors, and hard-to-model uncertainty. Strong simplifying assumptions have become essential: for instance, many theoretical models of road networks take the form of static, deterministic, and/or aggregative games.
Performance Period: 01/15/2024 - 12/31/2028
Institution: University of Texas at Austin
Sponsor: National Science Foundation
Award Number: 2336840
CPS: Small: Controlling Sub- and Supersynchronous Oscillations in Inverter-dominated Energy CPS
Nilanjan Ray Chaudhuri
Lead PI:
Nilanjan Ray Chaudhuri
Co-PI:
Abstract
This NSF project aims to solve the problem of oscillations faced by power grids with high penetration of renewable energy that are disrupting system operations. The project will bring transformative change in fundamental understanding of such phenomena and propose new control strategies to damp the oscillations by leveraging the cyber layer of the power grid including sensors and communication network.
Performance Period: 09/01/2023 - 08/31/2026
Institution: Pennsylvania State Univ University Park
Sponsor: National Science Foundation
Award Number: 2317272
CAREER: Temporal Causal Reinforcement Learning and Control for Autonomous and Swarm Cyber-Physical Systems
Zhe Xu
Lead PI:
Zhe Xu
Abstract
Understanding the root cause of behavior is imperative for informed decision-making and preventing ineffective or biased policies. Currently, most AI-based learning and control modules embedded in cyber-physical systems (CPS) rely on statistical correlation rather than causality for decision-making. This not only results in incorrect decisions but also hinders the interpretability of learning, limiting transferability and scalability. This CAREER proposal aims to bridge the gap between causal inference and the growing capabilities of reinforcement learning (RL) in CPS.
Zhe Xu
I am an assistant professor in Aerospace and Mechanical Engineering in the School for Engineering of Matter, Transport and Energy at Arizona State University. My research focuses on developing neuro-symbolic learning and control tools for human–machine systems that take into account the limited availability of simulated and real data, the complex and adversary task environment, and the expressivity and interpretability of high-level knowledge (e.g., temporal logic) representations.
Performance Period: 03/01/2024 - 02/28/2029
Institution: Arizona State University
Sponsor: National Science Foundation
Award Number: 2339774
Congestion Impacts Reduction via CAV-in-the-loop Lagrangian Energy Smoothing (CIRCLES)
Alexandre Bayen
Lead PI:
Alexandre Bayen
Co-PI:
Abstract

The Congestion Impacts Reduction via CAV-in-the-loop Lagrangian Energy Smoothing (CIRCLES) project aims to reduce instabilities in traffic flow, called "phantom jams," that cause congestion and wasted energy. If you have ever encountered a temporary traffic jam for no apparent reason, this might have been a phantom jam that occurred naturally because of human driving behavior.

Performance Period: 01/01/2020 - 12/31/2023
Sponsor: US Department of Energy
Award Number: CID DE-EE0008872
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