Alvin R. Lebeck

Professor of Computer Science

My interests span atoms to applications, with a foundation centered in computer architecture and systems. I enjoy a combination of interdisciplinary and conventional research.

Appointments and Affiliations

  • Professor of Computer Science
  • Core Faculty in Innovation & Entrepreneurship

Contact Information

  • Office Location: D308 Lev Sci Res Ctr, Durham, NC 27708
  • Office Phone: (919) 660-6551
  • Email Address: alvy@cs.duke.edu
  • Websites:

Education

  • B.S. University of Wisconsin - Madison, 1989
  • M.S. University of Wisconsin - Madison, 1991
  • Ph.D. University of Wisconsin - Madison, 1995

Awards, Honors, and Distinctions

  • Alan D. Berenbaum Distinguished Service Award. ACM SIGARCH. 2020
  • Recognition of Service Award. Association of Computing Machinery. 2019
  • Fellow. IEEE. 2017
  • Honorable Mention, IEEE MICRO Top Picks from Computer Architecture Conferences . IEEE MICRO. 2017
  • Best Paper. 6th International Workshop on Network on Chip Architectures. 2013
  • IEEE MICRO Top Picks from Computer Architecture Conferences . IEEE. 2010
  • IEEE MICRO Top Picks from Computer Architecture Conferences . IEEE MICRO. 2009
  • Best Paper. 31st Annual ACM/IEEE International Symposium on Microarchitecture. 1998
  • NSF CAREER. National Science Foundation. 1997
  • Outstanding Graduate Student Researcher. Department of Computer Sciences, University of Wisconsin at Madison. 1995

Courses Taught

  • COMPSCI 210D: Introduction to Computer Systems
  • ECE 652: Advanced Computer Architecture II

In the News

Representative Publications

  • Snyder, J., and A. R. Lebeck. “Fast Convergence to Fairness for Reduced Long Flow Tail Latency in Datacenter Networks.” In Proceedings  2022 Ieee 36th International Parallel and Distributed Processing Symposium, Ipdps 2022, 1007–17, 2022. https://doi.org/10.1109/IPDPS53621.2022.00102.
  • Snyder, J., A. R. Lebeck, and D. Zhuo. “RDMA Congestion Control: It's Only for the Compliant.” Ieee Micro, January 1, 2022. https://doi.org/10.1109/MM.2022.3208746.
  • Zhang, X., R. Bashizade, Y. Wang, S. Mukherjee, and A. R. Lebeck. “Statistical robustness of Markov chain Monte Carlo accelerators.” In International Conference on Architectural Support for Programming Languages and Operating Systems  Asplos, 959–74, 2021. https://doi.org/10.1145/3445814.3446697.
  • Bashizade, Ramin, Xiangyu Zhang, Sayan Mukherjee, and Alvin R. Lebeck. “Accelerating Markov Random Field Inference with Uncertainty Quantification.” Corr abs/2108.00570 (2021).
  • Zeng, H., C. S. Ellis, A. R. Lebeck, and A. Vahdat. “Currentcy: A unifying abstraction for expressing energy management policies.” In Proceedings of the General Track: 2003 Usenix Annual Technical Conference, 43–56, 2020.