Upcoming Doctoral Dissertations

"Additive manufacturing (AM) has great capabilities to fabricate intricate parts through layer-by-layer material deposition. Ensuring high-quality production is a challenge due to the complexity of AM processes and the lack of effective real-time monitoring and data analysis. This research aims to address these challenges by developing comprehensive, AI-driven models for real-time monitoring, data fusion, and quality control in AM processes. This study centers on two distinct AM technologies: Fused Filament Fabrication (FFF) and Direct Energy Deposition (DED)" Read more

"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

"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

"People often use unreliable sources such as social media to find health information and tend to overestimate their knowledge. As a result, they make many daily decisions based on inaccurate knowledge, which can create risks to their health outcomes. Throughout my research, I conducted a series of experiments testing the effectiveness of causal diagrams and causal information for decision-making support in healthcare." Read more

"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