World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
51
Citations
8840
World Ranking
5406
National Ranking
2469

Research.com Recognitions

  • 2011 - ACM Distinguished Member

Overview

Benjamin G. Zorn is affiliated with Microsoft in the United States. Their research spans multiple areas within computer science, with a particular focus on topics intersecting artificial intelligence, data management, and security.

The scientist's recent publications are predominantly featured in arXiv (Cornell University). These papers include:

  • "Safety, Security, and Privacy Threats Posed by Accelerating Trends in the Internet of Things," 2020, arXiv (Cornell University)
  • "Participatory prompting: a user-centric research method for eliciting AI assistance opportunities in knowledge workflows," 2023, arXiv (Cornell University)
  • "Evolving Methods for Evaluating and Disseminating Computing Research," 2020, arXiv (Cornell University)
  • "Solving Data-centric Tasks using Large Language Models," 2024, arXiv (Cornell University)

Their work touches on several main and subfields of study. Key fields include:

  • Computer Science

Within this broad field, their research contributes to subfields such as:

  • Artificial Intelligence
  • Information Systems and Management
  • Computer Networks and Communications
  • Signal Processing
  • Sociology and Political Science

The primary topics covered in their work are:

  • Explainable Artificial Intelligence (XAI)
  • Scientific Computing and Data Management
  • IoT and Edge/Fog Computing
  • Advanced Malware Detection Techniques
  • Privacy, Security, and Data Protection

Benjamin G. Zorn has collaborated frequently with several coauthors, including:

  • Advait Sarkar
  • Andrew D. Gordon
  • Jack M. Williams
  • Ian Drosos
  • Rob DeLine

One notable recognition awarded to Benjamin G. Zorn is the ACM Distinguished Member accolade, received in 2011.

Best Publications

  • Flikker: saving DRAM refresh-power through critical data partitioning

    Song Liu;Karthik Pattabiraman;Thomas Moscibroda;Benjamin G. Zorn

  • DieHard: probabilistic memory safety for unsafe languages

    Emery D. Berger;Benjamin G. Zorn

  • ZOZZLE: fast and precise in-browser JavaScript malware detection

    Charlie Curtsinger;Benjamin Livshits;Benjamin Zorn;Christian Seifert

  • NOZZLE: a defense against heap-spraying code injection attacks

    Paruj Ratanaworabhan;Benjamin Livshits;Benjamin Zorn

  • Quantifying Behavioral Differences Between C and C++ Programs

    Brad Calder;Dirk Grunwald;Benjamin Zorn

  • Rozzle: De-cloaking Internet Malware

    C. Kolbitsch;B. Livshits;B. Zorn;C. Seifert

  • Reconsidering custom memory allocation

    Emery D. Berger;Benjamin G. Zorn;Kathryn S. McKinley

  • Using lifetime predictors to improve memory allocation performance

    David A. Barrett;Benjamin G. Zorn

  • Design Decisions in SPUR

    Mark Hill;Susan Eggers;Jim Larus;George Taylor

  • OOPSLA 2002: Reconsidering custom memory allocation

    Emery D. Berger;Benjamin G. Zorn;Kathryn S. McKinley

  • JSMeter: comparing the behavior of JavaScript benchmarks with real web applications

    Paruj Ratanaworabhan;Benjamin Livshits;Benjamin G. Zorn

  • Policy Management for the Cloud

    William Hunter Hudson;Patrick J. Helland;Benjamin G. Zorn

  • Composing high-performance memory allocators

    Emery D. Berger;Benjamin G. Zorn;Kathryn S. McKinley

  • The measured cost of conservative garbage collection

    Benjamin Zorn

  • Inductive programming meets the real world

    Sumit Gulwani;José Hernández-Orallo;Emanuel Kitzelmann;Stephen H. Muggleton

  • BIT: a tool for instrumenting java bytecodes

    Han Bok Lee;Benjamin G. Zorn

  • Evidence-based static branch prediction using machine learning

    Brad Calder;Dirk Grunwald;Michael Jones;Donald Lindsay

  • Segregating heap objects by reference behavior and lifetime

    Matthew L. Seidl;Benjamin G. Zorn

  • Improving the cache locality of memory allocation

    Dirk Grunwald;Benjamin Zorn;Robert Henderson

  • FlashRelate: extracting relational data from semi-structured spreadsheets using examples

    Daniel W. Barowy;Sumit Gulwani;Ted Hart;Benjamin Zorn

Frequent Co-Authors

Dirk Grunwald
Dirk Grunwald University of Colorado Boulder
Emery D. Berger
Emery D. Berger University of Massachusetts Amherst
Benjamin Livshits
Benjamin Livshits Imperial College London
Karthik Pattabiraman
Karthik Pattabiraman University of British Columbia
Sumit Gulwani
Sumit Gulwani Microsoft (United States)
Alexander L. Wolf
Alexander L. Wolf University of California, Santa Cruz
James R. Larus
James R. Larus École Polytechnique Fédérale de Lausanne
Shwetak N. Patel
Shwetak N. Patel University of Washington
Elizabeth D. Mynatt
Elizabeth D. Mynatt Northeastern University
Jennifer Rexford
Jennifer Rexford Princeton University

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