Marquita Ellis is an early career researcher at the IBM Thomas J. Watson Research Center. She received her Ph.D. in Computer Science from UC Berkeley, advised by Katherine Yelick. Ellis studied parallelism paradigms, programming systems, and hardware features necessary to scale irregular applications, from a hardware-software codesign perspective. Under the Exascale Computing Project, her results for scalable genomics, collected using US leading supercomputing facilities (NERSC, ALCF, OLCF, among others) have been published internationally and in top-tier conferences, in parallel and distributed computing. Ellis’ interest in HPC-Cloud convergence piqued while doing a retrospective on her results collected between 2017-2021, comparing performance between certain NERSC and cloud offerings (and seeing the cloud start to catch-up). Afterward, Ellis joined IBM Research, as it is a leader in both hybrid cloud and supercomputing technologies, and her research is now focused on leveraging HPC and Cloud technologies together, for HPC&AI application scalability, portability, and developer-productivity.
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