computer networking and systems

KAUST student Saverio Pasqualoni receives ISC Hans Meuer Best Paper Award for leading research on an open-source framework

3 min read ·
Improving how supercomputers communicate can significantly reduce the time required to train artificial intelligence models. Research led by KAUST M.S./Ph.D. student Saverio Pasqualoni shows that optimizing communication across large-scale systems can cut training time by up to 44%. The research introduces PICO (Performance Insights for Collective Operations), an open-source framework that analyzes and improves communication across large-scale computing systems. The system’s fine-grained profiling, rich metadata collection and automated orchestration break down complex internal algorithmic

Saverio Pasqualoni

M.S. Student, Computer Science
Saverio is a Master’s student pursuing graduate studies (M.S. and Ph.D.) in Computer Science at KAUST, working in the SANDS research group on high-performance computing and collective communications, with research interests that bridge systems-level computer science and large-scale simulation through a strong mathematical foundation.
Neil Joshua Limbaga

Neil Joshua Limbaga

Neil is a Ph.D candidate in Electrical and Computer Engineering at KAUST. He currently focuses on Computer Architecture, Embedded and Edge Computing in the applications of Cyber-Physical Systems and Artificial Intelligence. He has recently collaborated with McLaren Racing, in the United Kingdom, to help shape Human Performance with efficient AI-based algorithms.

Ziyi Yang

Ph.D. Student, Computer Science
Ziyi Yang is a PhD student in the Accelerated Connected Computing Lab at KAUST. She works on the networked integration of FPGA-based accelerators. She received her Bachelor of Science degree in Telecommunications Engineering with Management from the Beijing University of Posts and Telecommunications, China and Queen Mary University of London in 2021. She completed her MS in Computer Science at KAUST in 2022.

Enas Ahmad

Enas Ahmad obtained her Master's degree in Computer Science under the supervision of Professor Basem Shihada at King Abdullah University of Science and Technology (KAUST). Research Interests Enas' research interests included the area of computer networking and systems, specifically software-defined networking, data centers, the internet of things, and participatory sensing. Thesis title: " Energy Efficient Smartphones: Minimizing the Energy Consumption of Smartphone's GPU using DVFS Governors". Education Profile M.sc. in Computer Science, King Abdullah University of Science and Technology