Torsten Hoefler is a Professor of Computer Science at ETH Zurich[8] and the Chief Architect for Machine Learning at the Swiss National Supercomputing Centre.

[9] Previously, he led the Advanced Application and User Support team at the Blue Waters Directorate of the National Center for Supercomputing Applications,[10] and held an adjunct professor position at the Computer Science Department at the University of Illinois at Urbana Champaign.

He received his PhD in Computer Science in 2008 from Indiana University and was subsequently honored with the university's Young Alumni Award[21] as well as Distinguished Alumni Award[22] He continued his work on the Message Passing Interface standard as a key member of the MPI Forum[23] responsible for the chapters on Collective Communication and Process Topologies as well as co-authoring the chapter on One-Sided Communications.

He spent his sabbatical in 2019 at Microsoft helping to establish various AI supercomputing efforts including the Maia 100 system.

[31] He was elected IEEE Fellow for “contributions to large-scale parallel processing systems and supercomputers”,[12] ACM Fellow for “foundational contributions to High-Performance Computing and the application of HPC techniques to machine learning”,[13] and he received the IEEE Sidney Fernbach Award in 2022 for “application-aware design of HPC algorithms, systems and architectures, and transformative impact on scientific computing and industry”.

[38] Nonblocking collective operations such as allreduce, allgather, or broadcast form the basis of modern AI training systems.

[48] He has been a convener of the Berlin Summit in Earth Virtualization Engines[49] to develop strategies to enable global access to high-resolution climate simulations.

[54] His group received the SIGHPC Certificate of Appreciation for reproducible methods at the ACM/IEEE Supercomputing Conference (SC22) ACM student cluster competition.