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: March 2024)

[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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March 2024: Deb's work on evaluating ML models for per-job power prediction is accepted at the HotCloudPerf 2024 workshop. Congratulations, Deb!
March 2024: Our collaborative work with FSL on accelerating storage system simulations is accepted to appear in the Performance Evaluation journal.
March 2024: Our work on detecting multiple bottlenecks in microservices applications is accepted (oral presentation) to WWW 2024. Congratulations to Gagan and Anurag!
January 2024: Our proposed work on reducing the energy consumption of DNNs received an OVPR Seed Grant Award. Thanks, SBU!
February 2024: Our collaborative work on verifiable sustainability in data centers will appear in the IEEE Security & Privacy Magazine.
January 2024: Serving on the TPC for USENIX ATC 2024.
January 2024: Serving on the TPC for MASCOTS 2024.
November 2023: Rebecca's BBR vs. BBR2 work is accepted to COMSNETS 2024. Congratulations, Rebecca!
October 2023: Our sustainability metrics HotCarbon'22 paper will also appear in ACM SIGEnergy Energy Informatics Review (Volume 3, Issue 3).
September 2023: Serving as lead guest editor for the PEVA SI on Performance Analysis and Evaluation of Systems for Artificial Intelligence.
September 2023: Our preliminary work with FSL on persistent memory research is accepted at the DIMES 2023 workshop.
September 2023: NSF funds our sustainable computing efforts on extending the lifetime of computer systems. Thanks NSF!
August 2023: Our preliminary work on sustainable DNN deployment on the edge is accepted as a WIP to IGSC 2023. Congrats to Anurag and Pramodh!
August 2023: Our collaborative work with FSL on multi-tier caches is accepted to MASCOTS 2023.
August 2023: Gagan's work on truncating Markov chains is accepted to appear in the Performance Evaluation journal. Congratulations, Gagan!
July 2023: Our collaborative work with MSR India on configuration tuning is accepted to NSDI 2024! Congratulations to Gagan!
July 2023: Serving on the TPC for Sigmetrics 2024.
June 2023: Excited to serve as Secretary-Treasurer for SIGMETRICS!.
April 2023: Serving as General Co-Chair for IEEE GreenCom 2023.
February 2023: Elevated to IEEE Senior Member grade.
January 2023: Excited to serve as PC Co-Chair for MASCOTS 2023, to be held at Stony Brook University!
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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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