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D-Index & Metrics

Computer Science

D-Index
54
Citations
11431
World Ranking
4576
National Ranking
2138

Overview

John Paul Shen is affiliated with Carnegie Mellon University in the United States. Their research spans multiple fields and subfields within engineering and computer science, with a strong focus on electrical and electronic engineering, computer vision and pattern recognition, artificial intelligence, cognitive neuroscience, and mechanical engineering.

The scientist has contributed extensively to advanced topics including:

  • Advanced Memory and Neural Computing
  • Neural dynamics and brain function
  • Neural Networks and Reservoir Computing
  • Ferroelectric and Negative Capacitance Devices
  • Video Surveillance and Tracking Methods
  • Human Pose and Action Recognition
  • CCD and CMOS Imaging Sensors

Their publication record includes recent papers published in varied venues such as arXiv (Cornell University), Frontiers in Big Data, ACM Transactions on Internet of Things, and ACM Transactions on Spatial Algorithms and Systems. Notable papers include:

  • IDIoT: Multimodal Framework for Ubiquitous Identification and Assignment of Human-carried Wearable Devices, 2023, ACM Transactions on Internet of Things
  • Direct CMOS Implementation of Neuromorphic Temporal Neural Networks for Sensory Processing, 2020, arXiv (Cornell University)
  • A Microarchitecture Implementation Framework for Online Learning with Temporal Neural Networks, 2021, arXiv (Cornell University)
  • Generating Realistic Ride-Hailing Datasets Using GANs, 2020, ACM Transactions on Spatial Algorithms and Systems
  • SemNet: Learning semantic attributes for human activity recognition with deep belief networks, 2022, Frontiers in Big Data

Frequent venues for publication include:

  • arXiv (Cornell University)
  • Frontiers in Big Data
  • ACM Transactions on Internet of Things
  • ACM Transactions on Spatial Algorithms and Systems
  • Green Chemical Engineering

John Paul Shen frequently collaborates with several researchers, including Harideep Nair, Prabhu Vellaisamy, James E. Smith, Shanmuga Venkatachalam, and Ming Zeng. Collaborations with Harideep Nair are particularly prominent.

Their extensive body of published work reflects a consistent engagement with interdisciplinary aspects of engineering and computational sciences, addressing neural computing, sensory processing, and data-driven modeling approaches.

Best Publications

  • Value locality and load value prediction

    Mikko H. Lipasti;Christopher B. Wilkerson;John Paul Shen

  • Die Stacking (3D) Microarchitecture

    Bryan Black;Murali Annavaram;Ned Brekelbaum;John DeVale

  • Exceeding the dataflow limit via value prediction

    Mikko H. Lipasti;John Paul Shen

  • Inductive Fault Analysis of MOS Integrated Circuits

    John P. Shen;W. Maly;F. Joel Ferguson

  • Modern Processor Design: Fundamentals of Superscalar Processors

    John Paul Shen;Mikko H. Lipasti

  • Speculative precomputation: long-range prefetching of delinquent loads

    Jamison D. Collins;Hong Wang;Dean M. Tullsen;Christopher Hughes

  • Mitigating Amdahl's Law through EPI Throttling

    Murali Annavaram;Ed Grochowski;John Shen

  • Dynamic speculative precomputation

    Jamison D. Collins;Dean M. Tullsen;Hong Wang;John P. Shen

  • A CMOS fault extractor for inductive fault analysis

    F.J. Ferguson;J.P. Shen

  • Coming challenges in microarchitecture and architecture

    R. Ronen;A. Mendelson;K. Lai;Shih-Lien Lu

  • Continuous signature monitoring: low-cost concurrent detection of processor control errors

    K. Wilken;J.P. Shen

  • Best of both latency and throughput

    E. Grochowski;R. Ronen;J. Shen;Hong Wang

  • Post-pass binary adaptation for software-based speculative precomputation

    Steve S.W. Liao;Perry H. Wang;Hong Wang;Gerolf Hoflehner

  • Physical experimentation with prefetching helper threads on Intel's hyper-threaded processors

    D. Kim;S.S.-W. Liao;P.H. Wang;J. del Cuvillo

  • Systematic characterization of physical defects for fault analysis of MOS IC cells

    W. Maly;F. J. Ferguson;J. P. Shen

  • Theoretical modeling of superscalar processor performance

    Derek B. Noonburg;John P. Shen

  • Programmable event driven yield mechanism which may activate other threads

    Hong Wang;Per Hammarlund;Xiang Zou;John P. Shen

  • Superspeculative microarchitecture for beyond AD 2000

    M.H. Lipasti;J.P. Shen

  • A variable instruction stream extension to the VLIW architecture

    Andrew Wolfe;John P. Shen

  • The block-based trace cache

    Bryan Black;Bohuslav Rychlik;John Paul Shen

  • A performance counter architecture for computing accurate CPI components

    Stijn Eyerman;Lieven Eeckhout;Tejas Karkhanis;James E Smith

Frequent Co-Authors

Hong Wang
Hong Wang Intel (United States)
Murali Annavaram
Murali Annavaram University of Southern California
Mikko H. Lipasti
Mikko H. Lipasti University of Wisconsin–Madison
Chris Wilkerson
Chris Wilkerson Nvidia (United Kingdom)
Antonio Gonzalez
Antonio Gonzalez Universitat Politècnica de Catalunya
Radek Grzeszczuk
Radek Grzeszczuk Microsoft (United States)
Wojciech Maly
Wojciech Maly Carnegie Mellon University
Dean M. Tullsen
Dean M. Tullsen University of California, San Diego
Margaret Martonosi
Margaret Martonosi Princeton University

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