Nguyen Khanh

Khanh Nguyen is an Assistant Professor in the Department of Computer Science & Engineering at Texas A&M University, part of the College of Engineering. His research focuses on improving scalability and efficiency in Big Data systems through compiler and runtime innovations, particularly in memory management and distributed computing.

• Education:
  • Ph.D. in Computer Science, University of California, Los Angeles (2019)
  • M.S. in Computer Science, University of California, Irvine (2015)
  • B.S. in Computer Science, University of California, Irvine (2012)

His research interests include programming languages, compiler design, memory management, and Big Data systems. He has developed techniques such as Gerenuk for thin computation over big data, Skyway for distributed heap connectivity, and Yak, a high-performance garbage collector. His work emphasizes resource efficiency and workload scalability, particularly for machine learning and data-parallel applications.

Recent publications (2021–2024) highlight advancements in adaptive memory management for warehouse-scale computers, semantics-aware swapping in disaggregated systems, and query-driven distributed tracing.

• Awards:
  • Google Ph.D. Fellowship (2017)
  • Facebook Ph.D. Fellowship Finalist (2017)

His research bridges compiler/runtime systems with large-scale data processing, addressing challenges in distributed systems and far-memory utilization. He collaborates with industry and academic partners to advance practical, scalable solutions for modern data-intensive workloads.