FINS Director, Professor

Before becoming a faculty member, Dr. Woodard was a Director of Central Intelligence postdoctoral fellow. His postdoctoral research focused on developing advanced iris recognition systems using high-resolution sensors. His research interests include biometrics/identity science and applied artificial intelligence (machine learning, deep learning, reinforcement learning, computer vision, and natural language processing). His current research projects include authorship attribution (stylometry) / computational behavioral analytics via text analytics and natural language processing, image analysis/machine learning-based hardware assurance (hardware trojan detection, counterfeit electronics detection), and adversarial machine learning (DeepFake detection).

 

FINS Associate Director, Professor & Steven A. Yatauro Faculty Fellow

Dr. Forte’s current research focuses on:

• Traditional and AI-Enabled Computer-Aided Design (CAD) Tools, Metrics, and Rules for Hardware Security
• Microelectronics Supply Chain Security and Assurance: Semiconductor Intellectual Property (IP) Protection. Counterfeit Electronics Detection and Avoidance, Hardware Trojan Detection and Prevention, Reverse Engineering and Anti-reverse Engineering
• Hardware Security Benchmarking: Test Article Generation and Data Augmentation
• Countermeasures Against Physical Attacks
• Hardware Security Primitive Design and Fabrication: Physically Unclonable Functions (PUFs), True Random Number Generators (TRNGs), Chaogates
• Biometrics: Authentication, Indexing, and Privacy.

 

Lab Director & Assistant Professor

Dr. Fu’s lab focuses on developing intelligent and (semi-)autonomous systems through the integration of control theory, machine learning, and formal methods. At our lab, we aim to build trustworthy systems in complex decision-making and dynamic environments, in coordination with or under the supervision of human operators. The research contains several main areas: (1) Preference-aware decision making with human-on-the loop; (2) learning-enabled adaptive control and planning with complex temporal objectives; (3) game-theoretic design of provably correct autonomous systems. The applications include human-autonomy shared control, security and safety for cyber-physical systems, and cyber security. (CPSs).