In Kee Kim is currently an Assistant Professor in the School of Computing at the University of Georgia. He obtained his Ph.D. in Computer Science from the University of Virginia in 2018.
His research interests are centered around cloud computing, large-scale distributed systems, and IoT/edge computing, with a focus on scheduling and resource management. Specifically, his ongoing research focuses on three main areas.
Firstly, he is exploring ways to optimize resource management and scheduling in cloud computing systems for scientific computations. Secondly, he is addressing performance variability and enhancing the reliability of various serverless workflows on heterogeneous execution environments, such as spot VMs and resource-constrained edge nodes. Lastly, he is working on improving throughput and minimizing latency in AI applications on resource-constrained edge devices and AI accelerators.
In Kee Kim’s research is supported by various funding agencies, including NIFA/USDA, DoD, and industry partners.