World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
82
Citations
37007
World Ranking
938
National Ranking
511

Research.com Recognitions

  • 2016 - Fellow, National Academy of Inventors
  • 1999 - ACM - IEEE CS Eckert-Mauchly Award For fundamental contributions to high performance microarchitecture, including saturating counters for branch prediction, reorder buffers for precise exceptions, decoupled access/execute architectures, and vector supercomputer organization, memory, and interconnects.

Overview

James E. Smith is affiliated with the University of Wisconsin-Madison in the United States. Their research primarily spans the field of Computer Science, with a strong focus on Artificial Intelligence. The subfields of study include Cognitive Neuroscience, Electrical and Electronic Engineering, Health Informatics, and Social Psychology.

The main topics of their work cover areas such as Advanced Memory and Neural Computing, Neural dynamics and brain function, Artificial Intelligence in Healthcare and Education, Privacy-Preserving Technologies in Data, Neural Networks and Applications, Neural Networks and Reservoir Computing, and Explainable Artificial Intelligence (XAI).

The scientist has contributed extensively to various publication venues. Frequently, their work appears in:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • The Science of The Total Environment
  • International Journal of Social Robotics
  • International Journal for Population Data Science

James E. Smith has worked with several frequent co-authors, including:

  • Felix Ritchie
  • Emily Jefferson
  • Richard J. Preen
  • Esma Mansouri-Benssassi
  • Maeve Malone

Their recent papers include:

  • "Assessing and managing SARS-CoV-2 occupational health risk to workers handling residuals and biosolids," 2021, The Science of The Total Environment
  • "Protein Structured Reservoir Computing for Spike-Based Pattern Recognition," 2021, IEEE Transactions on Parallel and Distributed Systems
  • "Disclosure control of machine learning models from trusted research environments (TRE): New challenges and opportunities," 2023, Heliyon
  • "Predicting downed woody material carbon stocks in forests of the conterminous United States," 2021, The Science of The Total Environment
  • "Sentence encoding for Dialogue Act classification," 2021, Natural Language Engineering

James E. Smith has been recognized with awards including being named a Fellow of the National Academy of Inventors in 2016. Earlier, in 1999, they received the ACM - IEEE CS Eckert-Mauchly Award for contributions to high performance microarchitecture, including saturating counters for branch prediction, reorder buffers for precise exceptions, decoupled access/execute architectures, and vector supercomputer organization, memory, and interconnects.

Best Publications

  • Introduction to evolutionary computing

    Agoston E. Eiben;J. E. Smith

  • Virtual Machines: Versatile Platforms for Systems and Processes

    James E. Smith;Ravi Nair

  • Complexity-effective superscalar processors

    Subbarao Palacharla;Norman P. Jouppi;J. E. Smith

  • A study of branch prediction strategies

    James E. Smith

  • The architecture of virtual machines

    J.E. Smith;Ravi Nair

  • A tutorial for competent memetic algorithms: model, taxonomy, and design issues

    N. Krasnogor;J. Smith

  • Introduction to Evolutionary Computing

    A.E. Eiben;J.E. Smith

  • Trace cache: a low latency approach to high bandwidth instruction fetching

    Eric Rotenberg;Steve Bennett;James E. Smith

  • The predictability of data values

    Yiannakis Sazeides;James E. Smith

  • From evolutionary computation to the evolution of things

    Ágoston E. Eiben;James E. Smith

  • The microarchitecture of superscalar processors

    J.E. Smith;G.S. Sohi

  • Trace processors

    Eric Rotenberg;Quinn Jacobson;Yiannakis Sazeides;Jim Smith

  • Parameter Control in Evolutionary Algorithms

    A. E. Eiben;Zbigniew Michalewicz;Marc Schoenauer;James E. Smith

  • Data Cache Prefetching Using a Global History Buffer

    K.J. Nesbit;J.E. Smith

  • Managing multi-configuration hardware via dynamic working set analysis

    Ashutosh S. Dhodapkar;James E. Smith

  • Fair Queuing Memory Systems

    Kyle J. Nesbit;Nidhi Aggarwal;James Laudon;James E. Smith

  • Assigning confidence to conditional branch predictions

    Erik Jacobsen;Eric Rotenberg;J. E. Smith

  • Implementing precise interrupts in pipelined processors

    J.E. Smith;A.R. Pleszkun

  • Speculative versioning cache

    S. Gopal;T.N. Vijaykumar;J.E. Smith;G.S. Sohi

  • Decoupled access/execute computer architectures

    James E. Smith

  • A First-Order Superscalar Processor Model

    Tejas S. Karkhanis;James E. Smith

  • Implementation of precise interrupts in pipelined processors

    James E. Smith;Andrew R. Pleszkun

  • Comparing program phase detection techniques

    Ashutosh S. Dhodapkar;James E. Smith

  • Data cache prefetching using a global history buffer

    K.J. Nesbit;J.E. Smith

  • Retrospective: a study of branch prediction strategies

    James E. Smith

Frequent Co-Authors

Lieven Eeckhout
Lieven Eeckhout Ghent University
Mikko H. Lipasti
Mikko H. Lipasti University of Wisconsin–Madison
Mateo Valero
Mateo Valero Barcelona Supercomputing Center
Per Stenström
Per Stenström Chalmers University of Technology
Norman P. Jouppi
Norman P. Jouppi Google (United States)
Antonio Gonzalez
Antonio Gonzalez Universitat Politècnica de Catalunya
Gurindar S. Sohi
Gurindar S. Sohi University of Wisconsin–Madison
Howard Jay Siegel
Howard Jay Siegel Colorado State University
Pradip Bose
Pradip Bose IBM (United States)
Parthasarathy Ranganathan
Parthasarathy Ranganathan Google (United States)

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