Ricardo Bianchini

Last updated
Ricardo Bianchini
Born
Rio de Janeiro, Brazil
Alma mater University of Rochester (PhD)
Awards
  • ACM Fellow (2016)
  • IEEE Fellow (2015)
Scientific career
Fields Computer science
Institutions

Ricardo Bianchini is a computer scientist specializing in server and data center energy management. He currently serves as a Technical Fellow and Corporate Vice President at Microsoft Azure, where he leads the Compute Capacity and Efficiency group. His work focuses on enhancing the efficiency and sustainability of Microsoft's online services and datacenters. [1]

Contents

Bianchini was named Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2015 [2] for contributions to server and data center energy management. He was named an Association for Computing Machinery (ACM) Fellow in 2016 [3] for contributions to power, energy and thermal management of servers and datacenters. He has published nine award papers and received the CAREER award from the National Science Foundation. [4]

Education

Bianchini received a PhD from the University of Rochester in the Hajim School of Engineering & Applied Sciences in 1995. [5]

From 1995 to 1999, he was a Research Associate and Assistant Professor of Computer Science at the Federal University of Rio de Janeiro.

Professional contributions

Bianchini was a Professor of Computer Science at Rutgers University from 2000 [5] to 2015. In 2014 he started at Microsoft as a Chief Efficiency Strategist, became a Distinguished Engineer in the Microsoft Research group and then in the Azure group. He is now a Technical Fellow and Corporate VP at Microsoft. Bianchini has served as a steering committee member, and keynote speaker [6] [4] [7] for academic conferences including the Conference on Machine Learning and Systems, [8] ICSE, [9] ASPLOS, [10] AAAI, [11] Eurosys, [12] and ICDS. [13]

Awards and honors

Selected publications

References

  1. ↑ "Ricardo Bianchini, Microsoft Azure". Microsoft Research. Retrieved 2024-12-26.
  2. ↑ "2015 elevated fellow" (PDF). IEEE Fellows Directory. Archived from the original (PDF) on March 30, 2015.
  3. 1 2 "ACM 2016 Fellows Recognized for Advances that Are Transforming Science and Society".
  4. 1 2 "SYSTOR 2020". www.systor.org. Archived from the original on 2020-10-30. Retrieved 2024-12-26.
  5. 1 2 3 "URCS Alum Ricardo Bianchini named an IEEE Fellow". www.cs.rochester.edu. Retrieved 2024-12-26.
  6. ↑ "Program". cloudintelligenceworkshop.org. Retrieved 2024-12-26.
  7. ↑ "Keynote Speakers - HPDC'12". hpdc.org. Retrieved 2024-12-26.
  8. ↑ "Cloud Intelligence / AIOps The Workshop". cloudintelligenceworkshop.org. Retrieved 2024-12-26.
  9. ↑ "Organizers". cloudintelligenceworkshop.org. Retrieved 2024-12-26.
  10. ↑ "Organizers". cloudintelligenceworkshop.org. Retrieved 2024-12-26.
  11. ↑ "Organizers". cloudintelligenceworkshop.org. Retrieved 2024-12-26.
  12. ↑ "European Chapter of ACM SIGOPS - Conferences". www.eurosys.org. Retrieved 2024-12-26.
  13. ↑ Bianchini, Ricardo; Shigeno, Hiroshi (2016-08-08). "Message from the ICDCS 2016 Program Committee Co-Chairs". 2016 IEEE 36th International Conference on Distributed Computing Systems (ICDCS). Vol. 2016-August. pp. xv. doi:10.1109/ICDCS.2016.5. ISBN   978-1-5090-1483-5.
  14. ↑ Rosi, Emma J (26 December 2023). "Award Abstract # 1855277". nsf.gov. Retrieved 26 December 2024.
  15. ↑ Agarwal, Anant; Bianchini, Ricardo; Chaiken, David; Johnson, Kirk L.; Kranz, David; Kubiatowicz, John; Lim, Beng-Hong; Mackenzie, Kenneth; Yeung, Donald (May 1995). "The MIT Alewife machine: architecture and performance". ACM SIGARCH Computer Architecture News. 23 (2): 2–13. doi:10.1145/225830.223985. ISSN   0163-5964.
  16. ↑ Pinheiro, Eduardo; Bianchini, Ricardo; Carrera, Enrique V.; Heath, Taliver (2001). "Load balancing and unbalancing for power and performance in cluster-based systems". doi:10.7282/t3-agfw-yt73.{{cite journal}}: Cite journal requires |journal= (help)
  17. ↑ Cortez, Eli; Bonde, Anand; Muzio, Alexandre; Russinovich, Mark; Fontoura, Marcus; Bianchini, Ricardo (2017-10-14). "Resource Central: Understanding and Predicting Workloads for Improved Resource Management in Large Cloud Platforms". Proceedings of the 26th Symposium on Operating Systems Principles. Shanghai China: ACM. pp. 153–167. doi:10.1145/3132747.3132772. ISBN   978-1-4503-5085-3.
  18. ↑ Patel, Pratyush; Choukse, Esha; Zhang, Chaojie; Goiri, Íñigo; Warrier, Brijesh; Mahalingam, Nithish; Bianchini, Ricardo (2024-04-27). "Characterizing Power Management Opportunities for LLMs in the Cloud". Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3. ASPLOS '24. Vol. 3. New York, NY, USA: Association for Computing Machinery. pp. 207–222. doi:10.1145/3620666.3651329. ISBN   979-8-4007-0386-7.


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