Hai Jiang Data-verified

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

Professor

Last publication 2024 Last refreshed 2026-05-16

faculty

18 h-index 119 pubs 1,006 cited

Biography and Research Information

OverviewAI-generated summary

Hai Jiang's research focuses on advanced computing techniques, particularly in the areas of deep learning, blockchain technology, and high-performance computing systems. He has investigated malware detection using autoencoders and explored the application of blockchain for Internet-of-Things and cyber-physical systems. His work also includes the design and implementation of scalable smart contracts for platforms like Ethereum, with applications in digital certificates. Jiang has contributed to the development of heterogeneous computing systems, optimizing performance and energy efficiency using FPGA, GPU, and CPU architectures. Additionally, his research extends to fault-tolerant and scalable methods for processing vertically partitioned data. Jiang has published extensively, with a notable body of work in computer science and engineering. His scholarship metrics include an h-index of 18 and over 100 publications, indicating a sustained contribution to his fields.

Metrics

  • h-index: 18
  • Publications: 119
  • Citations: 1,006

Selected Publications

  • A fault‐tolerant and scalable boosting method over vertically partitioned data (2024)
    1 citation DOI OpenAlex
  • Guest Editorial Introduction to the Special Section on Computing and Networking for Cyber-Physical-Social Systems (2022)
  • A Malware Detection Approach Using Autoencoder in Deep Learning (2022)
    93 citations DOI OpenAlex
  • High-Performance and Energy-Efficient FPGA-GPU-CPU Heterogeneous System Implementation (2021)
    3 citations DOI OpenAlex
  • A FPGA-Based Heterogeneous Implementation of NTRUEncrypt (2021)
    4 citations DOI OpenAlex
  • Guest Editorial for Special Issue on Blockchain for Internet-of-Things and Cyber-Physical Systems (2021)
    7 citations DOI OpenAlex

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Collaboration Network

28 Collaborators 19 Institutions 11 Countries

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