World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
63
Citations
36367
World Ranking
2673
National Ranking
1325

Research.com Recognitions

  • 2015 - Fellow of Alfred P. Sloan Foundation

Overview

Ryan P. Adams is affiliated with Princeton University in the United States. Their research spans multiple disciplines, with a primary focus on Engineering and Computer Science. Within these areas, key subfields of study include Artificial Intelligence, Mechanical Engineering, Materials Chemistry, Biomedical Engineering, and Computational Mechanics.

The scientist's work covers a variety of topics related to machine learning and materials science. These main topics include:

  • Machine Learning in Materials Science
  • Adversarial Robustness in Machine Learning
  • Machine Learning and Algorithms
  • Gaussian Processes and Bayesian Inference
  • Microbial Community Ecology and Physiology
  • Advanced Materials and Mechanics
  • Manufacturing Process and Optimization

Ryan P. Adams has authored publications in several venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Nature
  • Journal of the American Chemical Society
  • Cell Host & Microbe
  • Nature Materials

Recent papers authored by the scientist demonstrate interdisciplinary collaboration and wide-ranging interests. Selected papers include:

  • Bayesian reaction optimization as a tool for chemical synthesis (2021) published in Nature
  • A Multi-Objective Active Learning Platform and Web App for Reaction Optimization (2022) published in Journal of the American Chemical Society
  • Diverse events have transferred genes for edible seaweed digestion from marine to human gut bacteria (2022) published in Cell Host & Microbe
  • A data-driven computational scheme for the nonlinear mechanical properties of cellular mechanical metamaterials under large deformation (2020) published in Soft Matter
  • Automated discovery of reprogrammable nonlinear dynamic metamaterials (2024) published in Nature Materials

The scientist frequently collaborates with several coauthors, with multiple joint works produced alongside:

  • Deniz Oktay
  • Alex Beatson
  • Eder Medina
  • Diana Cai
  • Mehran Mirramezani

Ryan P. Adams was awarded the status of Fellow of the Alfred P. Sloan Foundation in 2015, recognizing contributions to their fields of study.

Best Publications

  • Practical Bayesian Optimization of Machine Learning Algorithms

    Jasper Snoek;Hugo Larochelle;Ryan P Adams

  • Taking the Human Out of the Loop: A Review of Bayesian Optimization

    Bobak Shahriari;Kevin Swersky;Ziyu Wang;Ryan P. Adams

  • Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules

    Rafael Gómez-Bombarelli;Jennifer Nansean Wei;David Duvenaud;José Miguel Hernández-Lobato

  • Convolutional networks on graphs for learning molecular fingerprints

    David Duvenaud;Dougal Maclaurin;Jorge Aguilera-Iparraguirre;Rafael Gómez-Bombarelli

  • Bayesian reaction optimization as a tool for chemical synthesis.

    Benjamin J. Shields;Jason Stevens;Jun Li;Marvin Parasram

  • Mapping Sub-Second Structure in Mouse Behavior.

    Alexander B. Wiltschko;Matthew J. Johnson;Giuliano Iurilli;Ralph E. Peterson

  • Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks

    Jose Miguel Hernandez-Lobato;Ryan Adams

  • Scalable Bayesian Optimization Using Deep Neural Networks

    Jasper Snoek;Oren Rippel;Oren Rippel;Kevin Swersky;Ryan Kiros

  • Bayesian Online Changepoint Detection

    Ryan Prescott Adams;David J. C. MacKay

  • Multi-Task Bayesian Optimization

    Kevin Swersky;Jasper Snoek;Ryan P Adams

  • Gradient-based Hyperparameter Optimization through Reversible Learning

    Dougal Maclaurin;David Duvenaud;Ryan Adams

  • Gaussian Process Kernels for Pattern Discovery and Extrapolation

    Andrew Wilson;Ryan Adams

  • Composing graphical models with neural networks for structured representations and fast inference

    Matthew J. Johnson;David Duvenaud;Alexander B. Wiltschko;Ryan P. Adams

  • Bayesian optimization with unknown constraints

    Michael A. Gelbart;Jasper Snoek;Ryan P. Adams

  • Elliptical slice sampling

    Iain Murray;Ryan Prescott Adams;David J.C. MacKay

  • Spectral representations for convolutional neural networks

    Oren Rippel;Jasper Snoek;Ryan P. Adams

  • Discovering Latent Network Structure in Point Process Data

    Scott Linderman;Ryan Prescott Adams

  • Composing graphical models with neural networks for structured representations and fast inference

    Matthew J. Johnson;David Duvenaud;Alexander B. Wiltschko;Sandeep R. Datta

  • Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities

    Ryan Prescott Adams;Iain Murray;David J. C. MacKay

  • Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010)

    Ryan Prescott Adams;George E. Dahl;Iain Murray

  • Freeze-Thaw Bayesian Optimization

    Kevin Swersky;Jasper Snoek;Ryan Prescott Adams

Frequent Co-Authors

Jasper Snoek
Jasper Snoek Google (United States)
David Duvenaud
David Duvenaud University of Toronto
Iain Murray
Iain Murray University of Edinburgh
Andrew Miller
Andrew Miller University of Illinois at Urbana-Champaign
Kevin Swersky
Kevin Swersky Google (United States)
Zoubin Ghahramani
Zoubin Ghahramani University of Cambridge
Richard S. Zemel
Richard S. Zemel University of Toronto
José Miguel Hernández-Lobato
José Miguel Hernández-Lobato University of Cambridge
David J. C. MacKay
David J. C. MacKay University of Cambridge
Hugo Larochelle
Hugo Larochelle Google (United States)

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

Exploring online options for studying Computer Science in the USA has never been more accessible. If budget is a key consideration, you might want to look into the cheapest online college programs, which offer quality education at a fraction of traditional costs.

For students who are concerned about their academic history, there are also best colleges for low gpa, opening doors for more flexible admissions. This helps ensure that a wider range of aspiring professionals can pursue their tech aspirations.

Beyond Computer Science, related areas like environmental science also offer diverse opportunities. If you are wondering about your future career options, check out what jobs can you get with an environmental science degree for insights into different industries and job roles.

Those looking for a fast-track approach might consider the 2-year computer science degree online, which can accelerate your pathway into the tech workforce. Whichever route you choose, the flexibility of online learning supports a variety of backgrounds and career goals.

Best Scientists Citing Ryan P. Adams

Trending Scientists

Recently Published Articles