World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
45667
World Ranking
8545
National Ranking
3650

Research.com Recognitions

  • 2015 - Member of the National Academy of Sciences
  • 2010 - SIAM Fellow For contributions to stochastic processes, image analysis, and statistical learning.

Overview

Donald Geman is affiliated with Johns Hopkins University in the United States. Their research spans multiple fields including Biochemistry, Genetics and Molecular Biology as well as Computer Science.

Their main subfields of study include:

  • Molecular Biology
  • Artificial Intelligence
  • Cancer Research
  • Computer Vision and Pattern Recognition
  • Radiology, Nuclear Medicine and Imaging

Key research topics explored by Geman are:

  • Gene expression and cancer classification
  • Metabolomics and Mass Spectrometry Studies
  • Molecular Biology Techniques and Applications
  • Single-cell and spatial transcriptomics
  • Advanced MRI Techniques and Applications
  • Lanthanide and Transition Metal Complexes
  • Microbial Metabolic Engineering and Bioproduction

Frequent coauthors collaborating with Geman include:

  • Laurent Younès (11 joint publications)
  • Luigi Marchionni (8 joint publications)
  • Wikum Dinalankara (7 joint publications)
  • Qian Ke (4 joint publications)
  • Akira Sawa (3 joint publications)

Publication venues where Geman has frequently published are:

  • bioRxiv (Cold Spring Harbor Laboratory) with 6 publications
  • Molecular Psychiatry
  • Metabolites
  • Preprints.org
  • IEEE Transactions on Information Forensics and Security

Notable recent papers authored include:

  • Longitudinal changes in brain metabolites in healthy controls and patients with first episode psychosis: a 7-Tesla MRS study (2023, Molecular Psychiatry)
  • Identifying Personalized Metabolic Signatures in Breast Cancer (2020, Metabolites)
  • Longitudinal changes in brain metabolites in healthy subjects and patients with first episode psychosis (FEP): a 7-Tesla MRS study (2020, bioRxiv)
  • Identifying personalized metabolic signatures in breast cancer (2020, Preprints.org)
  • Attribute Prototype Learning for Interactive Face Retrieval (2021, IEEE Transactions on Information Forensics and Security)

Geman has been recognized by several awards, including election as a Member of the National Academy of Sciences in 2015 and being named a SIAM Fellow in 2010 for contributions to stochastic processes, image analysis, and statistical learning.

Best Publications

  • Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images*

    Stuart Geman;Donald Geman

  • Tackling the widespread and critical impact of batch effects in high-throughput data

    Jeffrey T. Leek;Robert B. Scharpf;Héctor Corrada Bravo;Héctor Corrada Bravo;David Simcha

  • Shape quantization and recognition with randomized trees

    Yali Amit;Donald Geman

  • Constrained restoration and the recovery of discontinuities

    D. Geman;G. Reynolds

  • Nonlinear image recovery with half-quadratic regularization

    D. Geman;Chengda Yang

  • An active testing model for tracking roads in satellite images

    D. Geman;B. Jedynak

  • Boundary detection by constrained optimization

    D. Geman;S. Geman;C. Graffigne;P. Dong

  • Simple decision rules for classifying human cancers from gene expression profiles

    Aik Choon Tan;Daniel Q. Naiman;Lei Xu;Raimond L. Winslow

  • Classifying Gene Expression Profiles from Pairwise mRNA Comparisons

    Donald Geman;Christian d'Avignon;Daniel Q. Naiman;Raimond L. Winslow

  • Random fields and inverse problems in imaging

    D. Geman

  • Coarse-to-Fine Face Detection

    Francois Fleuret;Donald Geman

  • Visual Turing test for computer vision systems

    Donald Geman;Stuart Geman;Neil Hallonquist;Laurent Younes

  • Bayes Smoothing Algorithms for Segmentation of Binary Images Modeled by Markov Random Fields

    Haluk Derin;Howard Elliott;Roberto Cristi;Donald Geman

  • Joint induction of shape features and tree classifiers

    Y. Amit;D. Geman;K. Wilder

  • A computational model for visual selection

    Yali Amit;Donald Geman

  • Computational Medicine: Translating Models to Clinical Care

    Raimond L. Winslow;Natalia Trayanova;Donald Geman;Michael I. Miller

  • A coarse-to-fine strategy for multiclass shape detection

    Y. Amit;D. Geman;X. Fan

  • Robust prostate cancer marker genes emerge from direct integration of inter-study microarray data

    Lei Xu;Aik Choon Tan;Daniel Q. Naiman;Donald Geman

  • A Local Time Analysis of Intersections of Brownian Paths in the Plane

    Donald Geman;Joseph Horowitz;Jay Rosen

  • Comparing machines and humans on a visual categorization test

    François Fleuret;Ting Li;Charles Dubout;Emma K. Wampler

  • Relative expression analysis for molecular cancer diagnosis and prognosis

    James A. Eddy;Jaeyun Sung;Donald Geman;Nathan D. Price

Frequent Co-Authors

Nathan D. Price
Nathan D. Price University of Illinois at Urbana-Champaign
Nozha Boujemaa
Nozha Boujemaa French Institute for Research in Computer Science and Automation - INRIA
Leroy Hood
Leroy Hood University of Washington
Aik Choon Tan
Aik Choon Tan University of Utah
René Vidal
René Vidal University of Pennsylvania
James Z. Wang
James Z. Wang Pennsylvania State University
Jeffrey T. Leek
Jeffrey T. Leek Fred Hutchinson Cancer Research Center
Theo A. Knijnenburg
Theo A. Knijnenburg Altius Institute for Biomedical Sciences
Leslie Cope
Leslie Cope Johns Hopkins University School of Medicine
Bert Vogelstein
Bert Vogelstein Johns Hopkins University

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