Dong Jin Data-verified

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Federal Grant PI High Impact

Researcher

Last publication 2025 Last refreshed 2026-05-22

faculty

22 h-index 112 pubs 1,711 cited

Biography and Research Information

OverviewAI-generated summary

Dong Jin is a faculty member at the University of Arkansas at Fayetteville, with a research focus that spans advanced computational techniques, network security, and the application of artificial intelligence in complex systems. Jin has led research efforts funded by the National Science Foundation (NSF), including a significant grant of $320,000 for research focused on enabling programmable in-network security for an attack-resilient smart grid. Additional NSF funding includes planning grants for the Center for Infrastructure Security in the Era of AI (ISEAI) and student travel grants for the ACM SIGSIM Principles of Advanced Discrete Simulation (PADS) conference.

Jin's recent publications demonstrate a broad interest in areas such as quantum network simulation, federated incremental learning for intrusion detection, and the optimization of power distribution grids. Other work explores graph neural networks for causality discovery in multi-step attack scenarios, enhancements in P4-based network emulation, and industrial network protocol security. Jin leads a research group and has a notable publication record, with 112 total publications and 1,711 citations, contributing to a high-impact researcher designation and an h-index of 22. Key collaborators include Yanfeng Qu, Zheng Hu, Luke Waind, and Reuben Samson Raj, all from the University of Arkansas at Fayetteville.

Metrics

  • h-index: 22
  • Publications: 112
  • Citations: 1,711

Selected Publications

  • In-Network Recovery of Delayed and Missing PMU Measurements using Programmable Switches (2025)
  • Introduction to the Special Issue on PADS 2023 (2025)
  • Enhancing P4-Based Network Emulation Fidelity Through a Lightweight Virtual Time System and Application Evaluation (2025)
    3 citations DOI OpenAlex
  • Introduction to the Special Issue on PADS 2022 (2024)
  • A Deep Learning Approach for In-Network Synchrophasor Missing Data Recovery Using Programmable Network Switches (2024)
    1 citation DOI OpenAlex
  • Leveraging Compact Data Accumulator to Enable In-Network Anomaly Detection in Programmable Switches for Power Grids (2024)
  • Synchronized Power Simulation and Programmable Network Emulation Testbed for SCADA System Security Evaluation (2024)
  • Comparative Analysis and Evaluation of P4-Based Network Emulation Testing Environments (2024)
    1 citation DOI OpenAlex
  • In-Network Logging and Missing Data Recovery In PMU Networks via Programmable Data Plane Devices (2024)
  • Towards Secure and Resilient Synchrophasor Networks Using P4 Programmable Switches (2024)
    1 citation DOI OpenAlex
  • Industrial Network Protocol Security Enhancement Using Programmable Switches (2023)
    4 citations DOI OpenAlex
  • VT-IO: A Virtual Time System Enabling High-Fidelity Container-Based Network Emulation for I/O Intensive Applications (2023)
    3 citations DOI OpenAlex
  • Dynamic Data-Driven Approach for Cyber-Resilient and Secure Critical Energy Systems (2023)
    2 citations DOI OpenAlex
  • Enhancing Fidelity of P4-Based Network Emulation with a Lightweight Virtual Time System (2023)
    5 citations DOI OpenAlex
  • HELICSAuto: Automating the Development of Cyber-Physical Co-Simulation Framework for Smart Grids (2023)

View all publications on OpenAlex →

Federal Grants 5 $355,000 total

Collaboration Network

85 Collaborators 15 Institutions 4 Countries

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