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D-Index & Metrics

Computer Science

D-Index
54
Citations
13252
World Ranking
4524
National Ranking
2119

Overview

Robert J. Marks is affiliated with Baylor University in the United States. Their research spans multiple fields and subfields within engineering and computer science, focusing primarily on electrical and electronic engineering, aerospace engineering, artificial intelligence, computer vision and pattern recognition, and radiology, nuclear medicine and imaging.

The primary areas of study include:

  • Radio Frequency Integrated Circuit Design
  • Energy Harvesting in Wireless Networks
  • Radar Systems and Signal Processing
  • Antenna Design and Optimization
  • Advanced SAR Imaging Techniques
  • Full-Duplex Wireless Communications
  • Advanced Power Amplifier Design

Recent publications demonstrate a diverse range of topics and collaboration with other researchers. Key papers include:

  • "Radiomics Feature Activation Maps as a New Tool for Signature Interpretability," 2020, Frontiers in Oncology
  • "Extrapolation of Load-Pull Data: A Novel Use of GAN Artificial Intelligence Image Completion," 2022, IEEE Transactions on Microwave Theory and Techniques
  • "Spurious Beam Suppression in Dual-Beam Phased Array Transmission by Impedance Tuning," 2022, IEEE Transactions on Aerospace and Electronic Systems
  • "A Plasma-Switch Impedance Tuner With Microsecond Reconfiguration," 2022, IEEE Transactions on Microwave Theory and Techniques
  • "A Low-Loss Reconfigurable Plasma Impedance Tuner for Real-Time, Frequency-Agile, High-Power RF Applications," 2022, 2022 IEEE/MTT-S International Microwave Symposium - IMS 2022

The coauthors who have frequently collaborated with Robert J. Marks include:

  • Charles Baylis
  • Austin Egbert
  • Adam Goad
  • Trevor Van Hoosier
  • Anthony F. Martone

Published work is often found in a range of venues, reflecting the broad scope of Robert J. Marks's research interests. Frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Microwave Theory and Techniques
  • IEEE Transactions on Aerospace and Electronic Systems
  • 2022 IEEE/MTT-S International Microwave Symposium - IMS 2022
  • 2022 IEEE Radar Conference (RadarConf22)

This profile presents an overview of Robert J. Marks's research contributions across engineering and computer science, highlighting engagement with topics related to radio frequency technologies, signal processing, and artificial intelligence within technical and scientific publication platforms.

Best Publications

  • Electric load forecasting using an artificial neural network

    D.C. Park;M.A. El-Sharkawi;R.J. Marks;L.E. Atlas

  • Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks

    Russell D. Reed;Robert J. Marks

  • The use of cone-shaped kernels for generalized time-frequency representations of nonstationary signals

    Y. Zhao;L.E. Atlas;R.J. Marks

  • Introduction to Shannon Sampling and Interpolation Theory

    II Robert J. Marks

  • Support vector machines for transient stability analysis of large-scale power systems

    L.S. Moulin;A.P.A. da Silva;M.A. El-Sharkawi;R.J. Marks

  • Computational Intelligence: Imitating Life

    Robert J. Marks;Jacek M. Zurada;Charles J. Robinson

  • Advanced topics in Shannon sampling and interpolation theory

    Robert J. Marks

  • Swarm intelligence for routing in communication networks

    I. Kassabalidis;M.A. El-Sharkawi;R.J. Marks;P. Arabshahi

  • Query-based learning applied to partially trained multilayer perceptrons

    J.-N. Hwang;J.J. Choi;S. Oh;R.J. Marks

  • A performance comparison of trained multilayer perceptrons and trained classification trees

    L. Atlas;J. Connor;D. Park;M. El-Sharkawi

  • Minimum power broadcast trees for wireless networks: integer programming formulations

    A. K. Das;R. J. Marks;M. El-Sharkawi;P. Arabshahi

  • An adaptively trained neural network

    D.C. Park;M.A. El-Sharkawi;R.J. Marks

  • Handbook of Fourier Analysis & Its Applications

    Robert J Marks

  • Inversion of snow parameters from passive microwave remote sensing measurements by a neural network trained with a multiple scattering model

    L. Tsang;Z. Chen;S. Oh;R.J. Marks

  • Dynamic security border identification using enhanced particle swarm optimization

    I.N. Kassabalidis;M.A. El-Sharkawi;R.J. Marks;L.S. Moulin

  • A performance comparison of trained multilayer perceptrons and trained classification trees

    L. Atlas;R. Cole;Y. Muthusamy;A. Lippman

  • Similarities of error regularization, sigmoid gain scaling, target smoothing, and training with jitter

    R. Reed;R.J. Marks;S. Oh

  • Preliminary results on using artificial neural networks for security assessment (of power systems)

    M. Aggoune;M.A. El-Sharkawi;D.C. Park;M.J. Dambourg

  • Inversion of feedforward neural networks: algorithms and applications

    C.A. Jensen;R.D. Reed;R.J. Marks;M.A. El-Sharkawi

  • Differintegral interpolation from a bandlimited signal's samples

    R. Marks;M. Hall

Frequent Co-Authors

Mohamed A. El-Sharkawi
Mohamed A. El-Sharkawi University of Washington
Les Atlas
Les Atlas University of Washington
Leung Tsang
Leung Tsang University of Michigan–Ann Arbor
Donald C. Wunsch
Donald C. Wunsch Missouri University of Science and Technology
Dimitrios Peroulis
Dimitrios Peroulis Purdue University West Lafayette
Joan E. Sanders
Joan E. Sanders University of Washington
Jenq-Neng Hwang
Jenq-Neng Hwang University of Washington
Alfred T. C. Chang
Alfred T. C. Chang Goddard Space Flight Center
Shannon D. Blunt
Shannon D. Blunt University of Kansas
Michael C. Wicks
Michael C. Wicks University of Dayton

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