Modern software increasingly relies on distributed systems to provide accessible, scalable, and reliable services. Choreographic programming brings a global perspective to distributed system development: programmers write a single program that describes the behavior of a whole system, and a compiler projects that global description into local programs run by each node. By making distributed control […]
Edge computing and distributed AI systems increasingly operate under heterogeneous resources, dynamic workloads, and frequent failures, requiring both adaptivity and fault tolerance for efficient execution. In heterogeneous edge clusters, nodes differ significantly in CPU throughput, memory capacity, and network bandwidth, while modern distributed GPU clusters supporting agentic LLM inference must recover large amounts of runtime […]
AI-assisted clinical decisions in medicine, and particularly in dermatology, demand fine-grained understanding across diverse skin tones, body sites, and disease types, yet expert-annotated datasets are scarce, demographically imbalanced, and almost devoid of rare presentations. This dissertation develops four deep learning systems for this low-label, low-coverage regime. We introduce HealNet, which learns wound healing stages from […]