World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
26373
World Ranking
8132
National Ranking
487

Overview

Jun Zhao is a researcher affiliated with the University of Oxford in the United Kingdom. Their work spans multiple disciplines, with a primary focus on computer science and social sciences. Zhao's research contributions are notably aligned with emerging challenges at the intersection of technology and society.

Their prolific publication record includes significant work within several core fields of study:

  • Computer Science
  • Social Sciences

Within these domains, Zhao has specialized in subfields such as:

  • Artificial Intelligence
  • Sociology and Political Science
  • Information Systems
  • Human-Computer Interaction
  • Education

Zhao's research covers a range of contemporary topics, including:

  • Privacy, Security, and Data Protection
  • Child Development and Digital Technology
  • Topic Modeling
  • Impact of Technology on Adolescents
  • Innovative Human-Technology Interaction
  • Advanced Graph Neural Networks
  • Natural Language Processing Techniques

Among Zhao's recent papers are the following publications:

  • "SQL Injection Attack Detection and Prevention Techniques Using Deep Learning," 2021, Journal of Physics Conference Series
  • "Informing Age-Appropriate AI: Examining Principles and Practices of AI for Children," 2022, CHI Conference on Human Factors in Computing Systems
  • "Peer Phubbing and Chinese College Students' Smartphone Addiction During COVID-19 Pandemic: The Mediating Role of Boredom Proneness and the Moderating Role of Refusal Self-Efficacy," 2021, Psychology Research and Behavior Management
  • "Before and after GDPR: tracking in mobile apps," 2021, Internet Policy Review
  • "'Don't make assumptions about me!': Understanding Children's Perception of Datafication Online," 2022, Proceedings of the ACM on Human-Computer Interaction

Zhao frequently collaborates with a group of co-authors who have contributed to related research areas. Notable frequent co-authors include:

  • Nigel Shadbolt
  • Max Van Kleek
  • Kang Liu
  • Ge Wang
  • Konrad Kollnig

Their work has appeared in various respected publication venues, with the highest concentration of their papers in:

  • arXiv (Cornell University)
  • Proceedings of the ACM on Human-Computer Interaction
  • Frontiers in Psychiatry
  • Journal of Responsible Technology
  • SSRN Electronic Journal

Best Publications

  • The FAIR Guiding Principles for scientific data management and stewardship

    Mark D Wilkinson;Michel Dumontier;IJsbrand Jan Aalbersberg;Gabrielle Appleton

  • Addendum: The FAIR Guiding Principles for scientific data management and stewardship

    Mark D. Wilkinson;Michel Dumontier;Ijsbrand Jan Aalbersberg;Gabrielle Appleton

  • 'It's Reducing a Human Being to a Percentage': Perceptions of Justice in Algorithmic Decisions

    Reuben Binns;Max Van Kleek;Michael Veale;Ulrik Lyngs

  • PROV-O: The PROV Ontology

    Timothy Lebo;Satya Sahoo;Deborah McGuinness;Khalid Belhajjame

  • Describing Linked Datasets.

    Keith Alexander;Richard Cyganiak;Michael Hausenblas;Jun Zhao

  • Describing Linked Datasets On the Design and Usage of voiD, the "Vocabulary Of Interlinked Datasets"

    Keith Alexander;Richard Cyganiak;Michael Hausenblas;Jun Zhao

  • Special Issue: The First Provenance Challenge

    Luc Moreau;Bertram Ludäscher;Ilkay Altintas;Roger S. Barga

  • The First Provenance Challenge

    Luc Moreau;Bertram Ludaescher;Ilkay Altintas;Roger S. Barga

  • Using semantic web technologies for representing E-science provenance

    Jun Zhao;Chris Wroe;Carole Goble;Robert Stevens

  • Using a suite of ontologies for preserving workflow-centric research objects

    Khalid Belhajjame;Jun Zhao;Daniel Garijo;Matthew Gamble

  • Describing linked datasets with the VoID vocabulary

    Keith Alexander;Richard Cyganiak;Michael Hausenblas;Jun Zhao

  • Publishing and consuming provenance metadata on the web of linked data

    Olaf Hartig;Jun Zhao

  • Mining Taverna's semantic web of provenance

    Jun Zhao;Carole Goble;Robert Stevens;Daniele Turi

  • Workflow-centric research objects: First class citizens in scholarly discourse.

    Khalid Belhajjame;Oscar Corcho;Daniel Garijo;Jun Zhao

  • Provenance of e-Science Experiments - Experience from Bioinformatics

    M Greenwood;C Goble;R Stevens;J Zhao

  • Workflow-Centric Research Objects: A First Class Citizen in the Scholarly Discourse

    K Belhajjame;O Corcho;D Garijo;J Zhao

  • Third Party Tracking in the Mobile Ecosystem

    Reuben Binns;Ulrik Lyngs;Max Van Kleek;Jun Zhao

  • Using web data provenance for quality assessment

    Olaf Hartig;Jun Zhao

  • Taverna/ my Grid: Aligning a Workflow System with the Life Sciences Community.

    Tom Oinn;Peter Li;Douglas B. Kell;Carole A. Goble

  • Why workflows break — Understanding and combating decay in Taverna workflows

    Jun Zhao;Jose Manuel Gomez-Perez;Khalid Belhajjame;Graham Klyne

  • PROV-O: The PROV ontology:W3C recommendation 30 April 2013

    Khalid Belhajjame;James Cheney;David Corsar;Daniel Garijo

  • 'It's Reducing a Human Being to a Percentage'; Perceptions of Procedural Justice in Algorithmic Decisions

    R Binns;M Van Kleek;M Veale;U Lyngs

Frequent Co-Authors

Carole Goble
Carole Goble University of Manchester
Nigel Shadbolt
Nigel Shadbolt University of Oxford
Max Van Kleek
Max Van Kleek University of Oxford
David De Roure
David De Roure University of Oxford
Sean Bechhofer
Sean Bechhofer University of Manchester
Oscar Corcho
Oscar Corcho Technical University of Madrid
Paolo Missier
Paolo Missier Newcastle University
Paul Groth
Paul Groth University of Amsterdam
Michel Dumontier
Michel Dumontier Maastricht University
Peter A. C. 't Hoen
Peter A. C. 't Hoen Radboud University

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