World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
20645
World Ranking
4190
National Ranking
1976

Overview

Robert L. Grossman is affiliated with the University of Chicago in the United States. Their research spans several intersecting domains, primarily focusing on biochemistry, genetics, molecular biology, medicine, and computer science.

Grossman's work includes a variety of publications across multiple fields of study. Key areas include molecular biology and cancer research, along with artificial intelligence and information systems. Their research topics notably cover cancer genomics and diagnostics, scientific computing and data management, research data management practices, AI in cancer detection, data quality and management, radiomics and machine learning in medical imaging, and ethics in clinical research.

Frequent co-authors collaborating with Grossman include Zhenyu Zhang, Allison P. Heath, Brian D. O'Connor, Kyle M. Hernandez, and Lauren C. Leiman.

Research outputs have been frequently published in venues such as bioRxiv (Cold Spring Harbor Laboratory), arXiv (Cornell University), Cancer Research, Scientific Data, and Nature Biotechnology.

Recent papers include the following:

  • GA4GH: International policies and standards for data sharing across genomic research and healthcare, 2021, Cell Genomics
  • The impact of site-specific digital histology signatures on deep learning model accuracy and bias, 2021, Nature Communications
  • The NCI Genomic Data Commons, 2021, Nature Genetics
  • Uniform genomic data analysis in the NCI Genomic Data Commons, 2021, Nature Communications
  • Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space, 2022, Cell Genomics

Best Publications

  • Pan-cancer analysis of whole genomes

    Peter J. Campbell;Gad Getz;Jan O. Korbel;Joshua M. Stuart

  • Toward a Shared Vision for Cancer Genomic Data.

    Robert L. Grossman;Allison P. Heath;Vincent Ferretti;Harold E. Varmus

  • A User's Guide to the Encyclopedia of DNA Elements (ENCODE)

    Richard M. Myers;John Stamatoyannopoulos;Michael Snyder;Ian Dunham

  • Identification of Functional Elements and Regulatory Circuits by Drosophila modENCODE

    Sushmita Roy;Jason Ernst;Peter V. Kharchenko;Pouya Kheradpour

  • The Case for Cloud Computing

    R.L. Grossman

  • Mining data records in Web pages

    Bing Liu;Robert Grossman;Yanhong Zhai

  • Hybrid Systems

    Robert L. Grossman;Anil Nerode;Anders P. Ravn;Hans Rischel

  • UDT: UDP-based data transfer for high-speed wide area networks

    Yunhong Gu;Robert L. Grossman

  • Hybrid Systems I

    Robert L. Grossman

  • PSockets: The Case for Application-level Network Striping for Data Intensive Applications using High Speed Wide Area Networks

    H. Sivakumar;S. Bailey;R. L. Grossman

  • Graph-theoretic scagnostics

    L. Wilkinson;A. Anand;R. Grossman

  • Data mining using high performance data clouds: experimental studies using sector and sphere

    Robert Grossman;Yunhong Gu

  • Compute and storage clouds using wide area high performance networks

    Robert L. Grossman;Yunhong Gu;Michael Sabala;Wanzhi Zhang

  • The NCI Genomic Data Commons as an engine for precision medicine

    Mark A. Jensen;Vincent Ferretti;Robert L. Grossman;Louis M. Staudt

  • GA4GH: International policies and standards for data sharing across genomic research and healthcare

    Heidi L. Rehm;Heidi L. Rehm;Angela J.H. Page;Lindsay Smith;Jeremy B. Adams

  • Data Mining for Scientific and Engineering Applications

    Vipin Kumar;Robert L. Grossman

  • The impact of site-specific digital histology signatures on deep learning model accuracy and bias.

    Frederick M. Howard;James Dolezal;Sara Kochanny;Jefree Schulte

  • A Nondegenerate Code of Deleterious Variants in Mendelian Loci Contributes to Complex Disease Risk

    David R. Blair;Christopher S. Lyttle;Jonathan M. Mortensen;Charles F. Bearden

  • Sector and Sphere: the design and implementation of a high-performance data cloud

    Yunhong Gu;Robert L. Grossman

  • Hopf-algebraic structure of families of trees

    Robert Grossman;Richard G Larson

  • PeakRanger: A cloud-enabled peak caller for ChIP-seq data

    Xin Feng;Xin Feng;Xin Feng;Robert Grossman;Lincoln Stein;Lincoln Stein;Lincoln Stein

Frequent Co-Authors

Kevin P. White
Kevin P. White National University of Singapore
Margaret A. LeMone
Margaret A. LeMone National Center for Atmospheric Research
Fei Chen
Fei Chen National Center for Atmospheric Research
Lincoln Stein
Lincoln Stein Ontario Institute for Cancer Research
Jason Leigh
Jason Leigh University of Hawaii at Manoa
Christopher D. Brown
Christopher D. Brown University of Pennsylvania
David Yates
David Yates National Center for Atmospheric Research
Richard Coulter
Richard Coulter Argonne National Laboratory
Thomas A. DeFanti
Thomas A. DeFanti University of California, San Diego

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