World's Best Scientists 2026 revealed!
Mark S. Squillante

Mark S. Squillante

D-Index & Metrics

Computer Science

D-Index
40
Citations
6162
World Ranking
9359
National Ranking
3970

Research.com Recognitions

  • 2017 - Fellow of the Institute for Operations Research and the Management Sciences (INFORMS)
  • 2008 - ACM Fellow For contributions to the theory and practice of stochastic modeling.
  • 2002 - IEEE Fellow For contributions to analysis, modeling and optimization of computer systems.

Overview

Mark S. Squillante is affiliated with IBM in the United States and conducts research primarily within the field of Computer Science. Their work spans multiple subfields, including Artificial Intelligence, Computational Theory and Mathematics, Electrical and Electronic Engineering, Management Science and Operations Research, and Computer Networks and Communications.

The scientist's research addresses several main topics, notably:

  • Advanced Queuing Theory Analysis
  • Risk and Portfolio Optimization
  • Matrix Theory and Algorithms
  • Stochastic Gradient Optimization Techniques
  • Interconnection Networks and Systems
  • Advanced Wireless Network Optimization
  • Markov Chains and Monte Carlo Methods

Mark S. Squillante has published extensively, with a significant number of papers appearing in venues such as:

  • arXiv (Cornell University)
  • ACM SIGMETRICS Performance Evaluation Review
  • Queueing Systems
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • IEEE Transactions on Automatic Control

Some of the recent papers include:

  • Quantum Topological Data Analysis with Linear Depth and Exponential Speedup, 2021, arXiv (Cornell University)
  • Topological data analysis on noisy quantum computers, 2022, arXiv (Cornell University)
  • Decentralized Bilevel Optimization for Personalized Client Learning, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • On Heavy-Traffic Optimal Scaling of c-Weighted MaxWeight Scheduling in Input-Queued Switches, 2021, IEEE Transactions on Automatic Control
  • Generalization Performance of Transfer Learning: Overparameterized and Underparameterized Regimes, 2023, arXiv (Cornell University)

The scientist has collaborated frequently with several co-authors, including:

  • Chai Wah Wu
  • Vasileios Kalantzis
  • Lior Horesh
  • Shashanka Ubaru
  • Yingdong Lu

Mark S. Squillante has been recognized by professional organizations through fellowships, including:

  • Fellow of the Institute for Operations Research and the Management Sciences (INFORMS), 2017
  • ACM Fellow, 2008, for contributions to the theory and practice of stochastic modeling
  • IEEE Fellow, 2002, for contributions to analysis, modeling and optimization of computer systems

Best Publications

  • Failure data analysis of a large-scale heterogeneous server environment

    R.K. Sahoo;M.S. Squillante;A. Sivasubramaniam;Yanyong Zhang

  • Using processor-cache affinity information in shared-memory multiprocessor scheduling

    M.S. Squillante;E.D. Lazowska

  • On maximizing service-level-agreement profits

    Zhen Liu;Mark S. Squillante;Joel L. Wolf

  • Analysis and characterization of large-scale Web server access patterns and performance

    Arun K. Iyengar;Mark S. Squillante;Li Zhang

  • Optimal crawling strategies for web search engines

    J. L. Wolf;M. S. Squillante;P. S. Yu;J. Sethuraman

  • Method, computer program product, and system for deriving web transaction performance metrics

    Willy W. Chiu;Nagui Halim;Joseph L. Hellerstein;LeRoy Albert Krueger

  • Performance implications of failures in large-scale cluster scheduling

    Yanyong Zhang;Mark S. Squillante;Anand Sivasubramaniam;Ramendra K. Sahoo

  • Computer resource proportional utilization and response time scheduling

    Liana Liyow Fong;Mark Steven Squillante;Roger Eldred Hough

  • Flexible dynamic partitioning of resources in a cluster computing environment

    Liana Liyow Fong;Ajei Sarat Gopal;Nayeem Islam;Andreas Leonidas Prodromidis

  • Gang scheduling for resource allocation in a cluster computing environment

    Liana Liyow Fong;Ajei Sarat Gopal;Nayeem Islam;Andreas Leonidas Prodromidis

  • Performance analysis of job scheduling policies in parallel supercomputing environments

    V. K. Naik;M. S. Squillante;S. K. Setia

  • A Hierarchical Approach for the Resource Management of Very Large Cloud Platforms

    B. Addis;D. Ardagna;B. Panicucci;M. S. Squillante

  • Evaluation of Multithreaded Uniprocessors for Commercial Application Environments

    Richard J. Eickemeyer;Ross E. Johnson;Steven R. Kunkel;Mark S. Squillante

  • Web traffic modeling and Web server performance analysis

    M.S. Squillante;D.D. Yao;Li Zhang

  • Analysis of task migration in shared-memory multiprocessor scheduling

    Mark S. Squillante;Randolph D. Nelson

  • Apparatus and methods for maximizing service-level-agreement profits

    Zhen Liu;Mark Squillante;Joel Wolf

  • Predictability of Web-server traffic congestion

    Y. Baryshnikov;E. Coffman;G. Pierre;D. Rubenstein

  • Asymptotic Optimality of Constant-Order Policies for Lost Sales Inventory Models with Large Lead Times

    David A. Goldberg;Dmitriy A. Katz-Rogozhnikov;Yingdong Lu;Mayank Sharma

  • Optimizing method for digital content delivery in a multicast network

    Charu C. Aggarwal;Jayachandran Sethuraman;Mark S. Squillante;Joel L. Wolf

  • The impact of I/O on program behavior and parallel scheduling

    Emilia Rosti;Giuseppe Serazzi;Evgenia Smirni;Mark S. Squillante

  • Matrix-Analytic Methods in Stochastic Models

    Guy Latouche;Vaidyanathan Ramaswami;Jay Sethuraman;Karl Sigman

Frequent Co-Authors

Li Zhang
Li Zhang IBM (United States)
Zhen Liu
Zhen Liu Nokia (Finland)
Chai Wah Wu
Chai Wah Wu IBM (United States)
Joel L. Wolf
Joel L. Wolf IBM (United States)
Aleksandra Mojsilovic
Aleksandra Mojsilovic IBM (United States)
David D. Yao
David D. Yao Columbia University
Vijay K. Naik
Vijay K. Naik IBM (United States)
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Joseph L. Hellerstein
Joseph L. Hellerstein University of Washington
Jianying Hu
Jianying Hu IBM (United States)

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