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David A. Winkler

David A. Winkler

D-Index & Metrics

Engineering and Technology

D-Index
57
Citations
12651
World Ranking
2629
National Ranking
135

Overview

David A. Winkler is affiliated with La Trobe University in Australia and conducts research primarily in the fields of Materials Science and Engineering. Their work encompasses various subfields such as Materials Chemistry, Molecular Biology, Biomedical Engineering, Computational Theory and Mathematics, and Artificial Intelligence.

The main research topics covered by Winkler include:

  • Machine Learning in Materials Science
  • Computational Drug Discovery Methods
  • 3D Printing in Biomedical Research
  • SARS-CoV-2 and COVID-19 Research
  • Nanoparticles: synthesis and applications
  • Ion-surface interactions and analysis
  • Advanced Photocatalysis Techniques

Winkler has coauthored multiple papers with several collaborators, with frequent co-authors including:

  • Grazziela P. Figueredo
  • Morgan R. Alexander
  • Wil Gardner
  • Benjamin W. Muir
  • Paul J. Pigram

The most common venues where Winkler has published include:

  • Analytical Chemistry
  • Advanced Materials Interfaces
  • Chemical Society Reviews
  • OPAL (Open@LaTrobe) (La Trobe University)
  • bioRxiv (Cold Spring Harbor Laboratory)

Selected recent papers authored or co-authored by Winkler are:

  • QSAR without borders, 2020, Chemical Society Reviews
  • Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery, 2022, Chemical Reviews
  • Systematic Comparison of the Structural and Dynamic Properties of Commonly Used Water Models for Molecular Dynamics Simulations, 2021, Journal of Chemical Information and Modeling
  • A critical overview of computational approaches employed for COVID-19 drug discovery, 2021, Chemical Society Reviews
  • Immune Modulation by Design: Using Topography to Control Human Monocyte Attachment and Macrophage Differentiation, 2020, Advanced Science

In addition to journal publications, Winkler has contributed to book literature. Notably, they published a book titled Ethics of Medical Innovation, Experimentation, and Enhancement in Military and Humanitarian Contexts in 2020 through Springer International Publishing.

Best Publications

  • QSAR without borders

    Eugene N. Muratov;Eugene N. Muratov;Jürgen Bajorath;Robert P. Sheridan;Igor V. Tetko

  • Beware of R2: Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models

    David L J Alexander;Alexander Tropsha;David Alan Winkler

  • Bayesian regularization of neural networks.

    Frank Burden;David Winkler

  • Quantitative Structure–Property Relationship Modeling of Diverse Materials Properties

    Tu Le;V. Chandana Epa;Frank R. Burden;David A. Winkler

  • Robust QSAR models using Bayesian regularized neural networks.

    Frank R. Burden;David A. Winkler

  • Opening the black box of neural networks: methods for interpreting neural network models in clinical applications

    Zhongheng Zhang;Marcus W Beck;David A Winkler;Bin Huang

  • A renaissance of neural networks in drug discovery

    Igor I Baskin;David Winkler;Igor V Tetko

  • Materials Genome in Action: Identifying the Performance Limits of Physical Hydrogen Storage

    Aaron William Thornton;Cory M. Simon;Jihan Kim;Ohmin Kwon

  • Systematic Comparison of the Structural and Dynamic Properties of Commonly Used Water Models for Molecular Dynamics Simulations.

    Sachini P. Kadaoluwa Pathirannahalage;Sachini P. Kadaoluwa Pathirannahalage;Nastaran Meftahi;Aaron Elbourne;Alessia C. G. Weiss

  • Modeling biological activities of nanoparticles.

    Chandana Epa;Frank Robert Burden;Carlos Tassa;Ralph Weissleder

  • Discovery and Optimization of Materials Using Evolutionary Approaches.

    Tu Le;David Alan Winkler

  • Computational Modeling and Simulation of CO2 Capture by Aqueous Amines

    Xin Yang;Xin Yang;Robert J. Rees;William Conway;Graeme Puxty

  • Applying quantitative structure–activity relationship approaches to nanotoxicology: Current status and future potential

    David A. Winkler;Enrico Mombelli;Antonio Pietroiusti;Lang Tran

  • The role of quantitative structure - activity relationships (QSAR) in biomolecular discovery

    David A. Winkler

  • A critical overview of computational approaches employed for COVID-19 drug discovery.

    Eugene N Muratov;Rommie Amaro;Carolina H Andrade;Nathan Brown

  • Understanding the Roles of the "Two QSARs".

    Toshio Fujita;David Alan Winkler

  • Towards chromate-free corrosion inhibitors: structure–property models for organic alternatives

    David Alan Winkler;Michael Breedon;Anthony E Hughes;Frank Robert Burden

  • Use of automatic relevance determination in QSAR studies using Bayesian neural networks.

    Frank R. Burden;Martyn G. Ford;David C. Whitley;David A. Winkler

  • Materials for stem cell factories of the future

    Adam Celiz;James G W Smith;Robert Samuel M Langer;Daniel G Anderson

  • Glossary of terms used in computational drug design, part II (IUPAC Recommendations 2015)

    Yvonne C. Martin;Ruben Abagyan;György G. Ferenczy;Val J. Gillet

  • Comparison of linear and nonlinear classification algorithms for the prediction of drug and chemical metabolism by human UDP-glucuronosyltransferase isoforms.

    Michael J. Sorich;John O. Miners;Ross A. McKinnon;David A. Winkler

  • Classification of emergence and its relation to self-organization

    Julianne. D. Halley;David A. Winkler

Frequent Co-Authors

Feng Wang
Feng Wang Swinburne University of Technology
Morgan R. Alexander
Morgan R. Alexander University of Nottingham
David N. Haylock
David N. Haylock Commonwealth Scientific and Industrial Research Organisation
Susan K. Nilsson
Susan K. Nilsson Commonwealth Scientific and Industrial Research Organisation
Olexandr Isayev
Olexandr Isayev Carnegie Mellon University
Joseph G. Shapter
Joseph G. Shapter University of Queensland
George W. J. Fleet
George W. J. Fleet University of Oxford
Martyn C. Davies
Martyn C. Davies University of Nottingham

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