World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
7865
World Ranking
9213
National Ranking
3921

Overview

Dan Grossman is affiliated with the University of Washington in the United States. Their research primarily focuses on the field of Computer Science, with contributions spanning subfields such as Information Systems and Management, Artificial Intelligence, Clinical Psychology, Organic Chemistry, and Management Information Systems.

Their work covers a diverse set of main topics, including:

  • Psychedelics and Drug Studies
  • Chemical synthesis and alkaloids
  • Diverse academic research themes
  • Security and Verification in Computing
  • Big Data and Business Intelligence
  • Scientific Computing and Data Management
  • Ethics and Social Impacts of AI

Dan Grossman has coauthored frequently with several researchers, including:

  • Chandrakana Nandi
  • Max Willsey
  • Adam Anderson
  • Zachary Tatlock
  • Jacob S. Aday

The venues in which Dan Grossman has published multiple works include:

  • arXiv (Cornell University)
  • Psychedelic Medicine
  • Artifact Digital Object Group
  • Proceedings of the ACM on Programming Languages
  • Zenodo (CERN European Organization for Nuclear Research)

Some of the recent papers authored or coauthored by Dan Grossman include:

  • Psychedelic Commercialization: A Wide-Spanning Overview of the Emerging Psychedelic Industry, 2023, Psychedelic Medicine
  • SPML: A DSL for Defending Language Models Against Prompt Attacks, 2024, arXiv (Cornell University)
  • The Case for Anticipating Undesirable Consequences of Computing Innovations Early, Often, and Across Computer Science, 2023, arXiv (Cornell University)
  • Szalinski: A Tool for Synthesizing Structured CAD Models with Equality Saturation and Inverse Transformations, 2020, Artifact Digital Object Group
  • Rewrite rule inference using equality saturation, 2021, Proceedings of the ACM on Programming Languages

Best Publications

  • Cyclone: A Safe Dialect of C

    Trevor Jim;J. Greg Morrisett;Dan Grossman;Michael W. Hicks

  • EnerJ: approximate data types for safe and general low-power computation

    Adrian Sampson;Werner Dietl;Emily Fortuna;Danushen Gnanapragasam

  • Region-based memory management in cyclone

    Dan Grossman;Greg Morrisett;Trevor Jim;Michael Hicks

  • Learning Bayesian network classifiers by maximizing conditional likelihood

    Daniel Grossman;Pedro Domingos

  • CoreDet: a compiler and runtime system for deterministic multithreaded execution

    Tom Bergan;Owen Anderson;Joseph Devietti;Luis Ceze

  • TALx86: A Realistic Typed Assembly Language∗

    Greg Morrisett;Karl Crary;Neal Glew;Dan Grossman

  • Enforcing isolation and ordering in STM

    Tatiana Shpeisman;Vijay Menon;Ali-Reza Adl-Tabatabai;Steven Balensiefer

  • ParaTimer: a progress indicator for MapReduce DAGs

    Kristi Morton;Magdalena Balazinska;Dan Grossman

  • Type-safe multithreading in cyclone

    Dan Grossman

  • Automatic Inference of Structural Changes for Matching across Program Versions

    Miryung Kim;David Notkin;Dan Grossman

  • Estimating the progress of MapReduce pipelines

    Kristi Morton;Abram Friesen;Magdalena Balazinska;Dan Grossman

  • High-level small-step operational semantics for transactions

    Katherine F. Moore;Dan Grossman

  • AtomCaml: first-class atomicity via rollback

    Michael F. Ringenburg;Dan Grossman

  • Type-directed completion of partial expressions

    Daniel Perelman;Sumit Gulwani;Thomas Ball;Dan Grossman

  • Expressing and verifying probabilistic assertions

    Adrian Sampson;Pavel Panchekha;Todd Mytkowicz;Kathryn S. McKinley

  • IFRit: interference-free regions for dynamic data-race detection

    Laura Effinger-Dean;Brandon Lucia;Luis Ceze;Dan Grossman

  • RCDC: a relaxed consistency deterministic computer

    Joseph Devietti;Jacob Nelson;Tom Bergan;Luis Ceze

  • Searching for type-error messages

    Benjamin S. Lerner;Matthew Flower;Dan Grossman;Craig Chambers

  • Synthesizing structured CAD models with equality saturation and inverse transformations

    Chandrakana Nandi;Max Willsey;Adam Anderson;James R. Wilcox

  • Test-driven synthesis

    Daniel Perelman;Sumit Gulwani;Dan Grossman;Peter Provost

  • Experience with safe manual memory-management in cyclone

    Michael Hicks;Greg Morrisett;Dan Grossman;Trevor Jim

Frequent Co-Authors

Luis Ceze
Luis Ceze University of Washington
Greg Morrisett
Greg Morrisett Cornell University
Michael Hicks
Michael Hicks University of Maryland, College Park
Michael D. Ernst
Michael D. Ernst University of Washington
Magdalena Balazinska
Magdalena Balazinska University of Washington
James Cheney
James Cheney University of Edinburgh
Steve Zdancewic
Steve Zdancewic University of Pennsylvania
Craig Chambers
Craig Chambers Google (United States)
Jock D. Mackinlay
Jock D. Mackinlay Tableau Software (United States)
Sumit Gulwani
Sumit Gulwani Microsoft (United States)

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