Upcoming Doctoral Dissertations
School of Engineering and Science
Candidate | Konstantinos Kleftogiorgos |
Date | Friday, July 11, 2025 |
Time | 10:00 AM (EDT) |
Title | Offloading Security Checks Via Software-Driven Logging |
Location | Virtual (https://stevens.zoom.us/j/91724044286) |
"Memory-unsafe languages such as C and C++ are foundational to systems programming, but they present a persistent security challenge due to their susceptibility to memory corruption attacks. The prevailing defense strategies present a difficult trade-off. Inline software monitors, while broadly deployable on existing systems, often incur significant performance overhead and introduce architectural weaknesses." Read more
Candidate | Licheng Xiao |
Date | Friday, July 11, 2025 |
Time | 2:00 PM (Eastern) |
Title | Quantum Photonic Devices from Strained-Engineered and Plasmonic Nanocavity Coupled 2D Semiconductors |
Location | Babbio 210 |
"Deterministic quantum emitters (QEs) underpin secure quantum communication, scalable photonic computing, and ultrasensitive metrology. Atomically thin transition-metal dichalcogenides (TMDCs) are attractive hosts because their excitonic properties can be tuned by strain and nanophotonic confinement. Among them, WSe₂ offers two complementary exciton classes." Read more
Candidate | Jingda Yang |
Date | Thursday, July 24, 2025 |
Time | 2:00 PM (Eastern) |
Title | Autonomous NextG System Vulnerability Detection from Protocol Verification to Runtime Validation |
Location | Babbio Center Room 503 |
"Vulnerability detection is crucial for defending against cyber threats and protecting wireless communication systems. Despite advancements in robust detection methods, such as machine learning and scalable cloud-based vulnerability detection, existing approaches to automatic vulnerability detection still have several limitations: the lack of fully automated protocol-based vulnerability detection, heavy dependence on computational resources for detecting implementation vulnerabilities, and the inability to update learned attack patterns during runtime." Read more
To view past Doctoral Dissertations, please visit this website.