Anshul Gandhi

  


      
Anshul Gandhi

Associate Professor
Department of Computer Science
Department of Applied Mathematics & Statistics (affiliate appointment)
Stony Brook University

Office: 347, Computer Science.  Phone: (631) 632-8475.
Email: anshul (at) cs (dot) stonybrook (dot) edu
Lab: 336, Computer Science.  PACE Lab.
Twitter: @PACELab_SBU.

CV: [pdf] (updated: June 2021)

[News]   [Background]   [Research Interests]   [Awards]   [Publications]   [Funding]   [Patents]   [Teaching]   [Service]   [PACE Lab]   [Gallery]

I am an Associate Professor in the Department of Computer Science at Stony Brook University, where I lead the PACE Lab.
I am broadly interested in systems and performance modeling. My research aims to improve system performance via analytical tools.
My recent projects include interference-aware performance modeling and management and dynamic provisioning of cloud-deployed applications.
Please see my research interests and publications below for more information.
Feel free to email me if you want to learn more about my research and are interested in joining my group.

[Brief (third-person) bio]

News:

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August 2022: Our joint work with the NetSys lab on analyzing BBR's performance on mobile devices is accepted to IMC 2022. Congrats to Santiago!
August 2022: Gagan's theoretical work on truncating Markov chains with probability guarantees is accepted to MASCOTS 2022. Congratulations to Gagan!
August 2022: Excited to announce that the multi-institution effort I led on sustainable data centers was awarded an NSF Large grant. Thanks NSF!
August 2022: Our collaborative project with PiCASSo Lab on video analytics systems received an OVPR Seed Grant Award. Thanks, SBU!
July 2022: Gagan's work on configuration tuning of microservices is accepted to ACSOS 2022. Congratulations to Gagan!
June 2022: Our collaborative work on sustainability metrics in data centers is accepted to HotCarbon 2022!
April 2022: Pramodh's work on near-data processing for Spark is accepted to ICDCS 2022. Congratulations to Pramodh!
March 2022: Gagan's work on using GNNs to detect bottlenecks in microservices applications is accepted to the WIP track of ICPE 2022. Congratulations to Gagan!
August 2021: Amogha's work on opportunistic execution of serverless functions in the cloud is accepted to SOCC 2021. Congratulations to Amogha!
May 2021: Thank you to OpenInfra Labs for supporting our research!
May 2021: Ubaid's work on placement and scheduling of TensorFlow operations is accepted to Middleware 2021. Congratulations to Ubaid and Xiao!
May 2021: NSF funds our multi-tier cache modeling work. Thanks NSF!
March 2021: Our preliminary work on optimizing the configuration of microservices applications is accepted to the EuroMLSys 2021 workshop. Congrats to Gagan!
January 2021: Our joint work with the NetSys lab on DASH video performance under BBR is accepted to WWW 2021. Congrats to Santiago and Rebecca!
August 2020: Promoted to Associate Professor with tenure!
August 2020: One paper accepted to IISWC 2020. Congrats, Ubaid!
June 2020: Two papers accepted to ACSOS 2020. Congratulations to Amogha, Wajahat, and Gagan!
May 2020: One paper accepted to appear in the Performance Evaluation journal. Congrats, Wajahat!
February 2020: Honored and excited to serve as PC Co-Chair for Sigmetrics 2021!
[more]

Background:

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I was a Post Doctoral Researcher in the Cloud Optimization and Analytics group at the IBM T. J. Watson Research Center from 2013 to 2014.
I completed my Ph.D. in 2013 from the Computer Science Department at Carnegie Mellon University where I was advised by Prof. Mor Harchol-Balter.
My Ph.D. thesis, Dynamic Server Provisioning for Data Center Power Management, was awarded the 2013 SPEC Distinguished Dissertation Award.
I completed my undergraduate studies in 2007 from the Department of Computer Science and Engineering at Indian Institute of Technology, Kanpur.

Research Interests:

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I am interested in applying theory to systems. In particular, my research aims to leverage mathematical tools such as {Performance Modeling, Queueing Theory, Machine Learning, Control Theory} to analyze the behavior of systems such as {Distributed Systems, Cloud, Data Centers, ML Systems} and to optimize metrics of interest such as {Performance, Energy}.

Some of my current projects include:

Selected Awards and Honors:

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Publications:      [Google Scholar]  [DBLP]  [ResearchGate]

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Funding:

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Patents:

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Teaching:

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Service:

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