I recently completed my PhD in Computer Engineering at Indiana University, where my research focused on high-performance computing, graph processing, and hardware-software co-design. During my doctoral work, I developed hardware accelerated framework for scalable graph processing - Gmap, a novel programming model and Gmachine, runtime system for scalable graph analytics on modern architectures.
As part of the AGILE program funded by IARPA and the U.S. Army, I contributed to the design of a graph-accelerator-based supercomputer for processing massive-scale graphs, with applications in machine learning, DNA sequencing, and network analysis.
I bring a strong foundation in systems design, parallel computing, and performance optimization, with hands-on experience in both academic and applied research environments. My expertise lies in developing efficient, scalable solutions that bridge the gap between hardware and software—particularly for data-intensive applications.
I’m now looking to apply my skills and continue growing as a systems researcher or software engineer in high-performance computing, AI infrastructure, or specialized graph systems.