Kate M. Bowers
Papers
1
Total Citations
12
H-Index
1
About
Kate M. Bowers is a leading researcher in the field of self-adaptive systems, with a particular focus on the intersection of software engineering and artificial intelligence. Her work addresses the critical challenge of balancing functional and non-functional requirements in dynamic environments, where systems must autonomously adjust to changing conditions. Bowers is best known for her seminal paper "Providentia: Using search-based heuristics to optimize satisficement and competing concerns between functional and non-functional objectives in self-adaptive systems" (2019), which has garnered 12 citations and introduced a novel heuristic-driven approach to managing trade-offs in real-time adaptation. This work has been instrumental in advancing the state of the art in autonomic computing, offering practical solutions for optimizing system performance, reliability, and resource efficiency simultaneously. Her contributions have influenced subsequent research in search-based software engineering and have been applied in domains ranging from cloud computing to cyber-physical systems. Bowers’ research continues to shape how modern software systems achieve resilience and efficiency, making her a notable figure in the self-adaptive systems community.
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Top Papers
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