معرفی
Majid Salimibeni is a PostDoc Researcher and Research Fellow at Vienna University of Technology (TU Wien), affiliated with the Parallel Computing research unit. He previously held a Postdoc position at the Department of Computer Science at the University of Salerno, Italy (2024), and has been a visiting researcher at TU Wien (2023). Currently based in Vienna, Austria, his work focuses on High Performance Computing (HPC) and its interdisciplinary applications.
- Education:
- Ph.D. in Computer Science, University of Salerno, Italy (2020–2024)
- M.Sc. in Computer Engineering (Software), Shiraz University, Iran (2017–2020)
- B.Sc. in Computer Engineering (Software), University of Birjand, Iran (2012–2016)
Salimibeni's research explores High Performance and Parallel Computing, with a focus on optimizing GPU communication via NCCL, improving energy efficiency in heterogeneous computing environments, and enhancing MPI collective algorithms for large-scale systems. His work bridges HPC infrastructure with emerging applications in Distributed Deep Learning and AI.
Recent publications highlight his expertise in GPU frequency scaling, NCCL profiling, and process arrival pattern analysis to improve distributed system performance. These works appear at top conferences like IPDPS, Cluster Computing, and ASHPC.
- Scientific Awards:
- Best Paper Award, Bench 2022
Salimibeni contributes to academic committees as a program committee member for IEEE ICPP 2025, ISC 2025, and BigHPC 2024, and serves on artifact evaluation committees for ASPLOS and CF conferences.
