David Ojika, PhD
David is a postdoctoral associate in the Electrical and Computer Engineering department
of the University of Florida. He specializes in using reconfigurable
architectures for machine learning and heterogeneous computing. He has had
several industry experiences working with the Data Center group at Intel,
focusing on 2 accelerator-based systems: Intel Xeon+FPGA, and a
compute-near-memory (CNM) infrastructure. He also spent a summer at Microsoft
Research (in the Project Catapult team), working on the integration of FPGAs in
the cloud. Prior to these, he was a systems engineer at a satellite
communications company. Currently, his research focuses on applied AI and
end-to-end machine learning workflows for scientific computing and streaming
big data analytics.
Research interests
Intelligent IoT
Science gateway
Distributed dataflow computing
Accelerated ML training/inference workflows
Hardware/software co-simulation of accelerators
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