World's Best Scientists 2026 revealed!
Daphne Koller

Daphne Koller

Award Badge
Best Female Scientists
2025
Award Badge
Computer Science
USA
2026

D-Index & Metrics

Best Female Scientists

D-Index
147
Citations
111937
World Ranking
166
National Ranking
101

Computer Science

D-Index
138
Citations
91401
World Ranking
75
National Ranking
45

Research.com Recognitions

  • 2026 - Research.com Computer Science in United States Leader Award
  • 2025 - Research.com Best Female Scientists Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2023 - Research.com Computer Science in United States Leader Award
  • 2022 - Research.com Computer Science in United States Leader Award
  • 2019 - ACM AAAI Allen Newell Award For seminal contributions to machine learning and probabilistic models, the application of these techniques to biology and human health, and for contributions to democratizing education.
  • 2014 - Fellow of the American Academy of Arts and Sciences
  • 2011 - Member of the National Academy of Engineering For contributions to representation, inference, and learning in probabilistic models with applications to robotics, vision, and biology.
  • 2007 - ACM Prize in Computing For her work on combining relational logic and probability that allows probabilistic reasoning to be applied to a wide range of applications, including robotics, economics, and biology.
  • 2004 - Fellow of the MacArthur Foundation
  • 2004 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to the integration of logic and probability and development of methods for reasoning, learning, and decision making under uncertainty.
  • 1996 - Fellow of Alfred P. Sloan Foundation

Overview

Daphne Koller is affiliated with insitro Inc. in the United States and has contributed extensively to the fields of biochemistry, genetics, molecular biology, and medicine. Their research focuses particularly on genetics, molecular biology, and hepatology, with additional work in epidemiology and control and systems engineering.

The scientist's work addresses several main topics, including:

  • Genetic Associations and Epidemiology
  • Genetic Syndromes and Imprinting
  • Liver Disease Diagnosis and Treatment
  • Chronic Lymphocytic Leukemia Research
  • Gene expression and cancer classification
  • Liver physiology and pathology
  • Human Motion and Animation

Daphne Koller has co-authored multiple papers with frequent collaborators such as Francesco Paolo Casale, Theofanis Karaletsos, Zachary R. McCaw, Matthew L. Albert, and Colm O'Dushlaine.

Their recent papers cover topics from genetic discovery methods to disease pathology with the following notable works:

  • "An allelic-series rare-variant association test for candidate-gene discovery," 2023, The American Journal of Human Genetics
  • "EmbedGEM: a framework to evaluate the utility of embeddings for genetic discovery," 2024, Bioinformatics Advances
  • "TDP-43 loss induces cryptic polyadenylation in ALS/FTD," 2025, Nature Neuroscience
  • "An allelic series rare variant association test for candidate gene discovery," 2022, bioRxiv (Cold Spring Harbor Laboratory)
  • "Convolutional neural networks of H&E-stained biopsy images accurately quantify histologic features of non-alcoholic steatohepatitis," 2020, Journal of Hepatology

Publishing frequently in venues like the Journal of Hepatology, bioRxiv (Cold Spring Harbor Laboratory), Cancer Research, The American Journal of Human Genetics, and Bioinformatics Advances, their work spans experimental and computational approaches.

The scientist has been recognized through several awards over the years, including:

  • ACM AAAI Allen Newell Award, 2019, for contributions to machine learning, probabilistic models, and applications in biology and human health
  • Fellow of the American Academy of Arts and Sciences, 2014
  • Member of the National Academy of Engineering, 2011, for representation, inference, and learning in probabilistic models
  • ACM Prize in Computing, 2007, for work on combining relational logic and probability
  • Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), 2004
  • Fellow of the MacArthur Foundation, 2004
  • Fellow of Alfred P. Sloan Foundation, 1996

Best Publications

  • The Genotype-Tissue Expression (GTEx) project

    John Lonsdale;Jeffrey Thomas;Mike Salvatore;Rebecca Phillips

  • The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans

    Kristin G. Ardlie;David S. Deluca;Ayellet V. Segrè

  • Support vector machine active learning with applications to text classification

    Simon Tong;Daphne Koller

  • FastSLAM: a factored solution to the simultaneous localization and mapping problem

    Michael Montemerlo;Sebastian Thrun;Daphne Koller;Ben Wegbreit

  • A Gene-Coexpression Network for Global Discovery of Conserved Genetic Modules

    Joshua M. Stuart;Eran Segal;Daphne Koller;Stuart K. Kim

  • Toward optimal feature selection

    Daphne Koller;Mehran Sahami

  • Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data

    Eran Segal;Michael Shapira;Aviv Regev;Aviv Regev;Dana Pe'er

  • SCAPE: shape completion and animation of people

    Dragomir Anguelov;Praveen Srinivasan;Daphne Koller;Sebastian Thrun

  • Max-Margin Markov Networks

    Ben Taskar;Carlos Guestrin;Daphne Koller

  • Hierarchically Classifying Documents Using Very Few Words

    Daphne Koller;Mehran Sahami

  • Correction: Corrigendum: Synchronized age-related gene expression changes across multiple tissues in human and the link to complex diseases

    Jialiang Yang;Tao Huang;Francesca Petralia;Quan Long

  • Self-Paced Learning for Latent Variable Models

    M. P. Kumar;Benjamin Packer;Daphne Koller

  • Learning Probabilistic Relational Models

    Nir Friedman;Lise Getoor;Daphne Koller;Avi Pfeffer

  • The Chemical Genomic Portrait of Yeast: Uncovering a Phenotype for All Genes

    Maureen E. Hillenmeyer;Eula Fung;Jan Wildenhain;Sarah E. Pierce

  • Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks

    Nir Friedman;Daphne Koller

  • Simultaneous Localization and Mapping with Sparse Extended Information Filters

    Sebastian Thrun;Yufeng Liu;Daphne Koller;Andrew Y. Ng

  • Decomposing a scene into geometric and semantically consistent regions

    Stephen Gould;Richard Fulton;Daphne Koller

  • A module map showing conditional activity of expression modules in cancer.

    Eran Segal;Eran Segal;Nir Friedman;Daphne Koller;Aviv Regev

  • Discriminative probabilistic models for relational data

    Ben Taskar;Pieter Abbeel;Daphne Koller

  • Tractable inference for complex stochastic processes

    Xavier Boyen;Daphne Koller

  • Context-specific independence in Bayesian networks

    Craig Boutilier;Nir Friedman;Moises Goldszmidt;Daphne Koller

  • Support Vector Machine Active Learning with Application sto Text Classification

    Simon Tong;Daphne Koller

  • Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning

    Daphne Koller;Nir Friedman

  • The Genotype-Tissue Expression (GTEx) project

    John Lonsdale;Jeffrey Thomas;Mike Salvatore;Rebecca Phillips

  • A Bayesian Approach to Structure Discovery in Bayesian Networks

    Nir Friedman;Daphne Koller

Frequent Co-Authors

Nir Friedman
Nir Friedman Weizmann Institute of Science
Eran Segal
Eran Segal Weizmann Institute of Science
Aviv Regev
Aviv Regev Genentech
Joseph Y. Halpern
Joseph Y. Halpern Cornell University
Sebastian Thrun
Sebastian Thrun Stanford University
Andrew Y. Ng
Andrew Y. Ng Stanford University
Christophe Benoist
Christophe Benoist Harvard University
Avi Pfeffer
Avi Pfeffer Charles River Laboratories (Netherlands)
Stephen Gould
Stephen Gould Australian National University
Diane Mathis
Diane Mathis Harvard University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Expanding your studies beyond traditional computer science can unlock diverse career opportunities. There is increasing interest in specialized fields such as cybersecurity, project management, law enforcement, and finance—each offering unique growth prospects.

For students interested in protecting digital systems, consider exploring cyber security schools online. These programs can equip you with high-demand skills in threat prevention and cyber defense.

Alternatively, some students may seek a broader skill set in project oversight and infrastructure. Pursuing an affordable online construction management degree can lead to roles in planning, supervising, and executing major projects worldwide.

Law enforcement and legal technologies also intersect with computer science. Those interested in public safety and legal systems may wish to research criminal justice degree price to find budget-friendly pathways into criminal justice careers.

Finally, those with a knack for numbers and business analytics could benefit from the cheapest accredited online accounting degree. These programs prepare you for essential finance and accounting roles across industries.

Best Scientists Citing Daphne Koller

Trending Scientists

Recently Published Articles