Yuefan Deng

[1] His research centers on developing parallel computing and machine learning algorithms for supercomputers, with a particular focus on modeling human platelet dynamics and optimizing Markov Chain Monte Carlo techniques for various applications.

[8] With his former doctoral students, he presented methods for enhancing parallel processing and storage systems: one by using mixed torus and hypercube tensor expansion to improve bandwidth and scalability, and another by creating interlaced bypass torus (iBT) networks to add bypass links for better interconnection in parallel computers and storage systems.

[9][10] Furthermore, he introduced an ultra-scalable supercomputer with MPU architecture designed for high TFLOPS/PFLOPS performance, featuring advanced interconnect topologies, routing strategies, and modular hardware for efficient parallel processing and communication.

In a review for Zentralblatt MATH, Svitlana Rogovchenko remarked, "The book can be warmly recommended as a good source of problems both for the lecturer and for the students’ independent study.

"[16] Deng co-authored the Chinese Scientists Encyclopedia entry on Chen Ning Yang, whom he wrote several papers with.