REU projects create and test innovative technologies that empower people to solve important problems with impacts for society at large. Each REU student will learn about and make a contribution in cybersecurity or artificial intelligen for the program. Several research labs within our College participate. REU students are assigned to a project within a research lab, and become a member of the lab for the summer. Research labs and faculty members connected with our REU program are highlighted below, along with prior and example projects.
Usable Security and Privacy
Security and Privacy Experiences Lab
Our research covers the human side of security and privacy, examining user needs and behaviors along with the usability of security and privacy technologies.
- User Perceptions of Security/Privacy in Automated Home Devices - Consumer devices for smart homes collect and use a wide array of potentially sensitive information. We are investigating how to help users understand and control that information, empowering them to maintain the security and privacy of their homes.
Security and Cyber-Physical Systems
Security faculty perform research across a wide range of connections between cybersecurity and cyber-physical systems. For example, projects focus on privacy and security in smart homes and Internet of Things - at the intersection of the digital and physical worlds.
- Dr. Chenglong Fu - [ Personal Site ]
- Dr. Meera Sridhar - [ Personal Site, Lab Site ]
- Dr. Chao Wang - [ Personal Site ]
- Dr. Jinpeng Wei - [ Personal Site ]
- Retroactive Security for Mobile + IoT Apps - Many mobile applications are developed to interact with IoT sensors / devices. This project investigates how to protect hybrid mobile apps against a range of security and privacy vulnerabilities.
- Security Threats against IoT Devices - This project investigates use of penetration testing tools to discover security vulnerabilities in consumer IoT devices.
- IoT Data Provenance. This project investigates how to track the origin and flow of information as it travels through IoT systems, such as low-resource devices that interact with the physical world around them.
Faculty explore artificial intelligence in use in a variety of systems, including robotics, image and video analysis, information systems. Research explores the creation and application of AI algorithms, including machine learning and deep learning.
- Dr. Christian Kuemmerle - [Personal Site]
- Dr. Jake Lee - [ Personal Site ]
- Dr. Wenhao Luo - [ Personal Site ]
- Dr. Srinivas Akella - [ Personal Site ]
- Dr. David Wilson - [ Personal Site ]
Explainable, Trustworthy Recommender systems. Explores the application of explainable AI approaches to providing trustworthy user recommendations to help people search, navigate, and explore different choices in information systems.
Safe Behavior Design in Mixed-Autonomy Traffic. Contribute to a universal framework with computational tools that can empower autonomous vehicles with varying levels of autonomy to understand the diving behavior of surrounding vehicles, and perform control with verifiable assurance to achieve human and machine safety.
Pathfinding Algorithms for Multipart Payments in the Lightning Network. Review pathfinding algorithms suitable for instantaneous settlement of Bitcoin-demonimated payments within the Lightning network payment protocol. Explore the application of continuous optimization algorithms to find optimal multipart payment splits with respect to several partially competing objectives.
The research and outreach projects include the development and study of innovations in pedagogy and technology in CS education, cybersecurity, and artificial intelligence. Research includes utilizing AI techniques to analyze and learn from student data.