World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
13363
World Ranking
6343
National Ranking
2831

Research.com Recognitions

  • 2019 - Fellow of the American Academy of Arts and Sciences
  • 2014 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2009 - ACM - IEEE CS Ken Kennedy Award For her influential leadership in the design, development and deployment of national-scale cyberinfrastructure, her inspiring work as a teacher and mentor, and her exemplary service to the high performance community.
  • 2000 - ACM Fellow For pioneering work in application scheduling for parallel distributed computing.
  • Fellow of The National Academy of Public Administration
  • Fellow of The National Academy of Public Administration
  • Fellow of The National Academy of Public Administration

Overview

Francine Berman is affiliated with Rensselaer Polytechnic Institute in the United States. Their research spans decision sciences and computer science, with a focus on subfields such as information systems and management, management science and operations research, computer networks and communications, and electrical and electronic engineering.

Their work addresses a range of topics including research data management practices, scientific computing and data management, data quality and management, opportunistic and delay-tolerant networks, vehicular ad hoc networks (VANETs), and big data technologies and applications.

Frequent co-authors of Francine Berman include:

  • Mercè Crosas
  • Emilia Cabrera
  • Ali Jebari
  • Wassim Marrakchi
  • Jill Lepore

Several publication venues appear repeatedly in their profile, with multiple papers published in:

  • Harvard Data Science Review
  • Patterns

Recent notable papers authored by Francine Berman include:

  • "The Research Data Alliance: Benefits and Challenges of Building a Community Organization," 2020, Harvard Data Science Review
  • "The impact universe-a framework for prioritizing the public interest in the Internet of Things," 2022, Patterns
  • "The People Machine: The Earliest Machine Learning?," 2021, Harvard Data Science Review

Francine Berman's recognitions comprise several fellowships and awards, including:

  • Fellow of the American Academy of Arts and Sciences, 2019
  • Fellow of the American Association for the Advancement of Science (AAAS), 2014
  • ACM - IEEE CS Ken Kennedy Award, 2009, for leadership in national-scale cyberinfrastructure design, teaching and mentoring, and service to the high performance community
  • ACM Fellow, 2000, for pioneering work in application scheduling for parallel distributed computing
  • Fellow of The National Academy of Public Administration

Best Publications

  • Overview of the Book: Grid Computing – Making the Global Infrastructure a Reality

    Fran Berman;Geoffrey Fox;Tony Hey;Tony Hey

  • Heuristics for scheduling parameter sweep applications in grid environments

    H. Casanova;A. Legrand;D. Zagorodnov;F. Berman

  • Application-Level Scheduling on Distributed Heterogeneous Networks

    Francine D. Berman;Rich Wolski;Silvia Figueira;Jennifer Schopf

  • Adaptive computing on the Grid using AppLeS

    F. Berman;R. Wolski;H. Casanova;W. Cirne

  • The AppLeS Parameter Sweep Template: User-Level Middleware for the Grid

    H. Casanova;F. Berman;G. Obertelli;R. Wolski

  • The GrADS Project: Software Support for High-Level Grid Application Development

    Francine Berman;Andrew Chien;Keith Cooper;Jack Dongarra

  • The AppLeS Parameter Sweep Template: User-Level Middleware for the Grid

    Unknown

  • On mapping parallel algorithms into parallel architectures

    Francine Berman;Lawrence Snyder

  • High-performance schedulers

    Francine Berman

  • The Grid: Past, Present, Future

    Fran Berman;Geoffrey Fox;Tony Hey;Tony Hey

  • TeraGrid: Analysis of organization, system architecture, and middleware enabling new types of applications

    Charlie Catlett;William E. Allcock;Phil Andrews;Ruth A. Aydt

  • A comprehensive model of the supercomputer workload

    W. Cirne;F. Berman

  • Scheduling from the perspective of the application

    F. Berman;R. Wolski

  • New grid scheduling and rescheduling methods in the GrADS project

    F. Berman;H. Casanova;A. Chien;K. Cooper

  • Toward a framework for preparing and executing adaptive grid programs

    K. Kennedy;M. Mazina;J. Mellor-Crummey;K. Cooper

  • Got data?: a guide to data preservation in the information age

    Francine Berman

  • Master/slave computing on the Grid

    G. Shao;F. Berman;R. Wolski

  • A study of deadline scheduling for client-server systems on the Computational Grid

    A. Takefusa;H. Casanova;S. Matsuoka;F. Berman

  • New grid scheduling and rescheduling methods in the GrADS project

    K. Cooper;A. Dasgupta;K. Kennedy;C. Koelbel

  • A model for moldable supercomputer jobs

    W. Cirne;F. Berman

  • From TeraGrid to Knowledge Grid.

    Francine Berman

Frequent Co-Authors

Henri Casanova
Henri Casanova University of Hawaii at Manoa
Rich Wolski
Rich Wolski University of California, Santa Barbara
Jack Dongarra
Jack Dongarra University of Tennessee at Knoxville
Daniel A. Reed
Daniel A. Reed University of Utah
Ken Kennedy
Ken Kennedy Rice University
Geoffrey C. Fox
Geoffrey C. Fox University of Virginia
Carl Kesselman
Carl Kesselman University of Southern California
Ian Foster
Ian Foster University of Chicago
Keith D. Cooper
Keith D. Cooper Rice University
Andrew A. Chien
Andrew A. Chien University of Chicago

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