Gulsum Gudukbay Akbulut

I am a Computer Science and Engineering Ph.D. candidate working on Architectural Bottleneck Analysis, using Machine Learning to characterize applications and optimize hardware design, adding accelerator support to platforms, phase prediction, and reconfigurable hardware.

More specifically, my research is focused on optimizing the performance and resource allocation of HPC by performing application characterization using ML, using this characterization and phase prediction to perform dynamic hardware reconfiguration, intelligent GPU-supported job scheduling, and recomputation for multithreaded applications. 

I also work in accelerating bioinformatics applications, containerizing bioinformatics tools, and private cloud infrastructure resource utilization prediction using ML.