Summary
Shubhendra Singhal is a PhD candidate at Georgia Tech with nine years of experience focused on high-performance computing, distributed runtime systems, and parallel algorithms across GPUs, DPUs, and CPUs. His work spans low-level libraries and networking stacks (OpenSHMEM, MPI) informed by real application needs in graph analytics, nuclear fusion, and ML, and has been published at top venues like SC, HPDC, and VLDB. He develops actor-based asynchronous runtimes (FA-BSP HClib-Actor, Conveyors) and contributes to software–hardware co-design for scalable barriers and in-network offloads, with a growing research emphasis on energy-efficient supercomputing. Practically minded, he has built validated AI data-center sandboxes at Accenture and prototyped in-network programming models at ORNL, bridging lab prototypes to operational demos. Known for pushing asynchrony without sacrificing correctness or productivity, he combines rigorous theory with hands-on engineering and cross-institutional collaborations that include national labs and industry partners.
8 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Georgia Institute of Technology
B.Tech(Honours), Computer Science and Engineering, B.Tech(Honours), Computer Science and Engineering at National Institute of Technology, Tiruchirappalli
Master's degree, Computer Science, Master's degree, Computer Science at University of Pennsylvania
English, Hindi