World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
61
Citations
37514
World Ranking
2982
National Ranking
1461

Overview

Simon Baker is affiliated with Nvidia in the United States and focuses primarily on research within the field of Mathematics, with a strong emphasis on Mathematical Physics, Geometry and Topology, and Computational Theory and Mathematics. Their work also spans Artificial Intelligence and Statistical and Nonlinear Physics subfields.

Their research delves deeply into topics such as Mathematical Dynamics and Fractals, Advanced Topology and Set Theory, semigroups and automata theory, Caveolin-1 and cellular processes, advanced mathematical theories, Analytic Number Theory Research, and Topic Modeling.

Simon Baker has published in various academic venues, including:

  • arXiv (Cornell University)
  • Nature
  • Advances in Mathematics
  • Mathematische Annalen
  • Proceedings of the Institution of Civil Engineers - Energy

Frequent co-authors include David Vandercruyssen, D.C. Howard, George Aggidis, Demi Allen, and Christoph Aistleitner.

Among recent publications are:

  • North-south publishing data show stark inequities in global research, 2023, Nature
  • Iterated function systems with super-exponentially close cylinders, 2021, Advances in Mathematics
  • Non-Autoregressive Text Generation with Pre-trained Language Models, 2021, Apollo (University of Cambridge)
  • Tidal range electricity generation: A comparison between estuarine barrages and coastal lagoons, 2022, Heliyon
  • Tidal range generation: combining the Lancaster zero-dimension generation and cost models, 2023, Proceedings of the Institution of Civil Engineers - Energy

Best Publications

  • The CMU Pose, Illumination, and Expression (PIE) database

    T. Sim;S. Baker;M. Bsat

  • Lucas-Kanade 20 Years On: A Unifying Framework

    Simon Baker;Iain Matthews

  • A Database and Evaluation Methodology for Optical Flow

    Simon Baker;Daniel Scharstein;J. P. Lewis;Stefan Roth

  • Multi-PIE

    Ralph Gross;Iain Matthews;Jeffrey Cohn;Takeo Kanade

  • The CMU pose, illumination, and expression database

    T. Sim;S. Baker;M. Bsat

  • Active Appearance Models Revisited

    Iain Matthews;Simon Baker

  • Limits on super-resolution and how to break them

    S. Baker;T. Kanade

  • A Database and Evaluation Methodology for Optical Flow

    S. Baker;D. Scharstein;J.P. Lewis;S. Roth

  • The template update problem

    L. Matthews;T. Ishikawa;S. Baker

  • A Theory of Single-Viewpoint Catadioptric Image Formation

    Simon Baker;Shree K. Nayar

  • Hallucinating faces

    S. Baker;T. Kanade

  • Real-time combined 2D+3D active appearance models

    Jing Xiao;S. Baker;I. Matthews;T. Kanade

  • Equivalence and efficiency of image alignment algorithms

    S. Baker;I. Matthews

  • Three-dimensional scene flow

    S. Vedula;S. Baker;P. Rander;R. Collins

  • A theory of catadioptric image formation

    S. Baker;S.K. Nayar

  • Shape-from-silhouette of articulated objects and its use for human body kinematics estimation and motion capture

    K.M.G. Cheung;S. Baker;T. Kanade

  • Generic vs. person specific active appearance models

    Ralph Gross;Iain Matthews;Simon Baker

  • Appearance-based face recognition and light-fields

    R. Gross;I. Matthews;S. Baker

  • A layered approach to stereo reconstruction

    S. Baker;R. Szeliski;P. Anandan

  • Simultaneous super-resolution and feature extraction for recognition of low-resolution faces

    P.H. Hennings-Yeomans;S. Baker;B.V.K.V. Kumar

  • Limits on super-resolution and how to break them

    S. Baker;T. Kanade

Frequent Co-Authors

Takeo Kanade
Takeo Kanade Carnegie Mellon University
Iain Matthews
Iain Matthews University of East Anglia
Ralph Gross
Ralph Gross Carnegie Mellon University
Richard Szeliski
Richard Szeliski University of Washington
Shree K. Nayar
Shree K. Nayar Columbia University
Ashish Kapoor
Ashish Kapoor Microsoft (United States)
Jeffrey F. Cohn
Jeffrey F. Cohn University of Pittsburgh
Dahua Lin
Dahua Lin Chinese University of Hong Kong
Deva Ramanan
Deva Ramanan Carnegie Mellon University
Gang Hua
Gang Hua Dolby (United States)

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