Cyber-Physical Systems

In an increasingly interconnected world, the fusion of digital intelligence and physical systems has become the driving force behind innovation and technological advancement. Our Electrical & Computer Engineering department is at the forefront of this transformative field, shaping the future of Cyber-Physical Systems (CPS).

  • AI and Machine Learning Engineering
  • Autonomous Systems Testing and Evaluation
  • Communications and Networking
  • Computer Vision and Computational Modeling
  • Cyber-Physical Modeling & Simulation
  • Cybersecurity Engineering
  • Distributed Simulation Architecture
  • High Performance Computing
  • Intelligent Transportation Systems
  • Scientific Data Visualization
  • Security and Hardware
  • System Controls
  • Virtual Reality and Augmented Reality

Participating Faculty

Associate Professor Electrical & Computer Engineering
Associate Professor Electrical & Computer Engineering
Professor & Chair Electrical & Computer Engineering
Associate Professor Electrical & Computer Engineering
Professor Electrical & Computer Engineering
Associate Professor Electrical & Computer Engineering
Professor Academic Affairs
Professor Electrical & Computer Engineering
Interim Associate Dean for Research and Innovation & Professor Electrical & Computer Engineering
Professor & Executive Director Csics Virginia Modeling, Analysis & Simulation Center
Professor Electrical & Computer Engineering
Associate Professor Electrical & Computer Engineering
Assistant Professor Electrical & Computer Engineering
Professor Electrical & Computer Engineering
Associate Professor Academic Affairs

Associated Labs

The Applied M&S Research Laboratory is a graduate research laboratory that contains PC workstations and spaces for 10 graduate students, and also supports faculty/VMASC collaborative research activities. Several research topics are conducted in this laboratory including high performance computing, cyber security, simulation architectures, transportation systems, military M&S, digital manufacturing, and enterprise decision support. Visualization of these is also a significant part of these areas.

The CCNI Lab carries out transformative research to advance the state of the arts in the fields of cybersecurity, communications, and networking, in particular the security for cognitive radio networks, wireless communications, and wireless networking. The Lab promotes the integration of research into education through vibrant curriculum design, program strengthening, and innovative outreach activities to the Hampton Roads region. Visit CCNI website ▶

The Collaborative Autonomous Systems Laboratory supports instructional and multidisciplinary research activities related to autonomous systems. This laboratory area is shared with the Mechanical and Aerospace Engineer Department. The laboratory includes workstations and various types of robotic systems. The lab contains an area dedicated to cyber security research as related to collaborative autonomous systems.

The Undergraduate Projects and Research Laboratory, is mainly used for facilitating modeling and simulation projects-based instruction in both lower and upper division undergraduate levels. This also involves courses in the major with a significant laboratory component. The Laboratory can accommodate 24 students with laptop computers and provide 5 workstations for undergraduate labs and research. Each workstation contains a high performance computer and collaboration spaces. The lab also contains a Polycom Teleconference system to support distance learning. The lab is equipped with 3 digital projectors to support teaching.

The Vision Lab aims to develop novel theory, state-of-art algorithms, and architectures for learning and real-time applications in human and machine-centered interaction and recognition; biomedical imaging and signal analysis; and environmental and geoscience applications based on the disciplines of computer vision, signal/image processing and AI/machine learning. Visit Vision Lab website ▶

The Vision Lab aims to develop novel theory, state-of-art algorithms, and architectures for learning and real-time applications in human and machine-centered interaction and recognition; biomedical imaging and signal analysis; and environmental and geoscience applications based on the disciplines of computer vision, signal/image processing and AI/machine learning. Visit Vision Lab website ▶