RESEARCH INTEREST

PATENT seeks to be a leader in fundamental Artificial Intelligence (AI) research and its applications in healthcare, cybersecurity, and cyber-physical systems. Our faculty and researcher research various AI topics, including: Deep Learning, Reinforcement Learning, Neuro-symbolic computing/Hybrid AI, Knowledge Graph Development, Natural Language Processing, Collaborative Assistants, Multiagent Systems, Brain-inspired computing, Interpretation/Explainability in AI systems.

PATENT has extensive ongoing collaborations with a significant majority of colleges in the universities and a large number of external organizations. Areas of collaboration and applications include: healthcare/nursing (patient management, hospital management), cyber operations, predictive maintenance for on-road/off-road autonomous vehicles, social good (disinformation/extremism detection), agricultural operations and autonomy, etc. 

1. Development of ML/AI models to Estimate the Health Status of Individual Systems
   • Explainable Machinery Faults Prediction Using Ensemble Tree Classifiers: Bagging or Boosting
   • A Survey of HMM-based Algorithms in Machinery Fault Prediction
   • Deep Learning Approaches to Remaining Useful Life Prediction: A Survey
   • Similarity-Based Methods for Faulty Pattern Detection in Predictive Maintenance
   • Scalability, Explainability, and Performance of Data-Driven Algorithms in Predictive Maintenance: A Comprehensive Review
2. Soft Computing‐Based Intrusion Detection
   • Explainable Intrusion Detection (X-IDS): Current Methods, Challenges, and Opportunities
3. Vehicle Performance, Reliability & Operations (VePro)- Analysis to Reduce Costs & Extend Life
4. Objective-based Manufacturability Assessment for HPC Tradespace Analytics
5. Hospital Patient Flow Optimization
6. Game Theory-Based Predictive Analytics: Using Current Dynamics instead of Past Data

• Vehicle Performance, Reliability & Operations (VePro)- Analysis to Reduce Costs & Extend Life
• Cybersecurity Education Hub-An MSU-MCA Collaborative Project
• GenCyber: Mississippi State University Student Camp
• Develop ML/AI models to estimate the health status of individual system
• Automated Low-Cost Distributed Acoustics Sensing for Perimeter Intrusion Detections using Fiber Bragg Gratings
• Systems Engineering Analytics

• Enhanced Network Cybersecurity Research: Self-Organizing Maps for Intrusion Detection -
• A Hybrid Model-Based Approach to Self-Defense of Health Information Systems
• Large Scale Simulation of Fluid Flow through Porous Media with Quantum Computing

• Engineering Research & Development Center (ERDC) (DOD)
• Appalachian Regional Commission (ARC)
• National Security Agency (NSA)
• National Science Foundation
• United States Department of Defense (DOD)
• United States Department of Energy (DOE)
• United States Department of Transportation (DOT)