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Intelligent Systems Lab

Virginia Tech's College of Engineering's AutoDrive VT team members with Chevy Bolt they are preparing for the Society for Automotive Engineers' AutoDrive Challenge next month at the Yuma Proving Ground in Arizona.

Wireless technologies and the Internet of Things are fundamentally changing the way we collect data and process information. With increased computing power and availability, improvements in data curation and management, and ever-evolving data science techniques, we are fundamentally changing the way we interact with and learn from data.

Over the past decade, we saw the emergence of the social-mobile internet, which transformed the way we interact with data and each other. The next decade will continue to be transformational, with new technologies like 5G and edge computing terraforming the global information and communication technologies ecosystem. The lines between data science, machine learning, and cybersecurity are blurring as algorithms that include machine learning are integrated into production systems. The validation of complex systems through rigorous test and evaluation processes is also needed to ensure the efficacy and safety of algorithms embedded in systems as they accomplish tasks with greater autonomy and operational impact.

The lab conducts research to address critical areas of national security in:

  1. Data science, machine learning, and artificial intelligence - applying technologies to a range of defense and intelligence missions
  2. Cybersecurity and complex systems engineering - analyzing security concerns associated with the proliferation of cyber-physical systems and impacts to national security.
  3. Complex system validation and test and evaluation -investigating methods for providing system assurance before fielding. 

The Hume Center's Intelligent Systems Lab conducts research to address critical areas of national security in three technological thrusts:

  1. Data Science, Machine Learning, and Artificial Intelligence
  2. Cybersecurity and Complex Systems Engineering
  3. Complex System Validation and Test and Evaluation (T&E)

The Data Science, Machine Learning, and Artificial Intelligence thrust applies these technologies to a range of defense and intelligence missions. These include:

  • Optimizing collection and tasking from intelligence, surveillance, and reconnaissance missions
  • Deep learning-based sensor processing for advanced object detection and classification
  • Multi-intelligence sensemaking and fusion
  • Natural language processing for technology and threat emergence
  • Adversarial learning for synthetic data generation
  • Reinforcement learning and adversary state estimation/forecasting
  • Machine learning methods for Signals Intelligence (SIGINT), communications optimization, and emitter identification

The Cybersecurity and Complex Systems Engineering thrust investigates security concerns associated with the proliferation of cyber-physical systems and impacts to national security. Areas include:

  • Security for embedded systems and networks
  • Privacy and integrity for data in smart ecosystems
  • Cybersecurity for energy and transportation systems
  • Security of ML-based sensors and AI-based system orchestration for IoT
  • Analog cybersecurity for cyber-physical systems
  • Cyber operations and cyber mission orchestration
  • RF-based cyber-attack and defense
  • Providing resilience for connected critical infrastructure

The Complex System Validation and Test and Evaluation (T&E) thrust investigates methods for providing system assurance before fielding. Areas include:

  • Measure and metric development to enhance operational relevance of AI systems
  • Developing critical test sets for providing AI assurance based on the intended operating environment
  • Optimal test set allocation using optimal learning
  • Evaluations of the effectiveness of transfer learning to new operating environments

If you are interested in completing undergraduate research opportunities with the Intelligent Systems Lab, please contact Danielle Kauffman, Project Coordinator of the Intelligent Systems Lab.

If you are interested in completing graduate research opportunities with the Intelligent Systems Lab, please contact Danielle Kauffman, Project Coordinator of the Intelligent Systems Lab.