World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
81
Citations
26604
World Ranking
1021
National Ranking
543

Research.com Recognitions

  • 2005 - IEEE Fellow For contributions to concurrent programming, system software, security, and ubiquitous computing.
  • 1934 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

Roy H. Campbell is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research spans several fields, with a significant focus on Medicine, Biochemistry, Genetics and Molecular Biology, and Computer Science. The subfields of their work include Molecular Biology, Artificial Intelligence, Infectious Diseases, Neurology, and Radiology, Nuclear Medicine and Imaging.

The primary topics covered in their publications include:

  • Parkinson's Disease Mechanisms and Treatments
  • Gene expression and cancer classification
  • COVID-19 diagnosis using AI
  • SARS-CoV-2 and COVID-19 Research
  • Bioinformatics and Genomic Networks
  • Voice and Speech Disorders
  • Autism Spectrum Disorder Research

Roy H. Campbell has published research in various venues. The most frequent include:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • SSRN Electronic Journal
  • arXiv (Cornell University)
  • npj Parkinson s Disease
  • Practice and Experience in Advanced Research Computing

Among recent papers, some notable works are:

  • Identification and prediction of Parkinson's disease subtypes and progression using machine learning in two cohorts, 2022, npj Parkinson s Disease
  • HAL: Computer System for Scalable Deep Learning, 2020, Practice and Experience in Advanced Research Computing
  • Application of Aligned-UMAP to longitudinal biomedical studies, 2023, Patterns
  • Going by the numbers: Learning and modeling COVID-19 disease dynamics, 2020, Chaos Solitons & Fractals
  • Multi-Modality Machine Learning Predicting Parkinson's Disease, 2021, bioRxiv (Cold Spring Harbor Laboratory)

Frequent collaborators in their research include:

  • Anant Dadu
  • Faraz Faghri
  • Hirotaka Iwaki
  • Andrew Singleton
  • Mike A. Nalls

Roy H. Campbell has been recognized with awards such as the IEEE Fellow status in 2005 for contributions to concurrent programming, system software, security, and ubiquitous computing. Additionally, they are a Fellow of the American Association for the Advancement of Science (AAAS).

Best Publications

  • A middleware infrastructure for active spaces

    M. Roman;C. Hess;R. Cerqueira;A. Ranganathan

  • Big data: Astronomical or genomical?

    Zachary D. Stephens;Skylar Y. Lee;Faraz Faghri;Roy H. Campbell

  • The specification of process synchronization by path expressions

    Roy H. Campbell;A. Nico Habermann

  • A middleware for context-aware agents in ubiquitous computing environments

    Anand Ranganathan;Roy H. Campbell

  • ARIA: automatic resource inference and allocation for mapreduce environments

    Abhishek Verma;Ludmila Cherkasova;Roy H. Campbell

  • Model-Based Reinforcement Learning for Atari

    Lukasz Kaiser;Mohammad Babaeizadeh;Piotr Milos;Blazej Osinski

  • The case for reflective middleware

    Fabio Kon;Fabio Costa;Gordon Blair;Roy H. Campbell

  • Monitoring, security, and dynamic configuration with the dynamicTAO reflective ORB

    Fabio Kon;Manuel Román;Ping Liu;Jina Mao

  • An infrastructure for context-awareness based on first order logic

    Anand Ranganathan;Roy H. Campbell

  • Consistent and durable data structures for non-volatile byte-addressable memory

    Shivaram Venkataraman;Niraj Tolia;Parthasarathy Ranganathan;Roy H. Campbell

  • Reasoning about uncertain contexts in pervasive computing environments

    A. Ranganathan;J. Al-Muhtadi;R.H. Campbell

  • Towards security and privacy for pervasive computing

    Roy Campbell;Jalal Al-Muhtadi;Prasad Naldurg;Geetanjali Sampemane

  • Stochastic Variational Video Prediction

    Mohammad Babaeizadeh;Chelsea Finn;Dumitru Erhan;Roy H. Campbell

  • A fault-tolerant scheduling problem

    A. L. Liestman;R. H. Campbell

  • Model Based Reinforcement Learning for Atari

    Łukasz Kaiser;Mohammad Babaeizadeh;Piotr Miłos;Błażej Osiński

  • Samza: stateful scalable stream processing at LinkedIn

    Shadi A. Noghabi;Kartik Paramasivam;Yi Pan;Navina Ramesh

  • Real-Time Video and Audio in the World Wide Web.

    Zhigang Chen;See-Mong Tan;Roy H. Campbell;Yongcheng Li

  • Method and system for transmitting and/or retrieving real-time video and audio information over performance-limited transmission systems

    Roy Campbell;See-Mong Tan;Dong Xie;Zhigang Chen

  • Error recovery in asynchronous systems

    R. H. Campbell;B. Randell

  • Monitoring, security, and dynamic configuration with the dynamic TAO reflective ORB

    Fabio Kon;Manuel Román;Ping Liu;Jina Mao

Frequent Co-Authors

Anand Ranganathan
Anand Ranganathan Unscrambl Inc.
Fabio Kon
Fabio Kon Universidade de São Paulo
Jalal Al-Muhtadi
Jalal Al-Muhtadi King Saud University
Klara Nahrstedt
Klara Nahrstedt University of Illinois at Urbana-Champaign
Indranil Gupta
Indranil Gupta Dalhousie University
Apu Kapadia
Apu Kapadia Indiana University
Shivaram Venkataraman
Shivaram Venkataraman University of Wisconsin–Madison
Mike A. Nalls
Mike A. Nalls National Institutes of Health
Andrew B. Singleton
Andrew B. Singleton National Institutes of Health

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