Rate My Professor Ali Butt

Ali R. Butt is a Professor of Computer Science at Virginia Tech, where he serves as Associate Department Head for Faculty Development and Director of the stack@cs Center for Computer Systems. He also holds a courtesy appointment in Electrical and Computer Engineering and leads the Distributed Systems & Storage Laboratory (DSSL). Butt earned his Ph.D. in Electrical and Computer Engineering from Purdue University in 2006. His research interests encompass cloud and high-performance computing systems, systems support for machine and deep learning applications, file, I/O, and storage systems, distributed systems, and large-scale experimental computer systems.

Butt has held visiting positions including an academic visitor at IBM Almaden Research Center in summer 2012 and a visiting research fellow at Queen's University of Belfast in summer 2013. His accolades include ACM Distinguished Member, NSF CAREER Award (2008), IBM Faculty Awards (2008, 2015), NetApp Faculty Fellowships (2011, 2015), Virginia Tech College of Engineering Dean's Award for Outstanding New Assistant Professor (2009), and IBM Shared University Research Award (2009). He is an alumnus of the National Academy of Engineering's U.S. Frontiers of Engineering Symposium (2009), organizer of the 2010 U.S. FOE, US-Japan FOE (2012), and participant in the National Academy of Sciences' Arvind and Chandralekha Aserkar Symposium on Sensor Science (2015). Key publications feature "FLStore: Efficient Federated Learning Storage for Non-training Workloads" (MLSys 2025), "10Cache: Heterogeneous Resource-Aware Tensor Caching and Migration for LLM Training" (SoCC 2025), "Tarazu: An Adaptive End-to-End I/O Load-Balancing Framework for Large-Scale Parallel File Systems" (ACM Transactions on Storage 2024), "SHADE: Enable Fundamental Cacheability for Distributed Deep Learning Training" (USENIX FAST 2023), and "Heterogeneity-Aware Adaptive Federated Learning Scheduling" (IEEE BigData 2022), among dozens of others in premier venues that advance storage and systems for AI, cloud, and HPC.