Hai Jiang Source Confirmed

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

Professor

Arkansas State University

faculty

18 h-index 119 pubs 990 cited

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Biography and Research Information

OverviewAI-generated summary

Hai Jiang's research focuses on the intersection of computer science, deep learning, and cybersecurity. His recent work includes developing a malware detection approach utilizing autoencoders within deep learning frameworks. Jiang has also investigated blockchain technology, contributing to special issues on its application in Internet-of-Things and cyber-physical systems, and exploring adversarial honeypots in Ethereum for smart contract security. He has experience with hardware acceleration, having worked on FPGA-based implementations of cryptographic algorithms like NTRUEncrypt and high-performance, energy-efficient heterogeneous computing systems combining FPGAs, GPUs, and CPUs. Jiang also contributes to research on scalable and fault-tolerant data processing methods. His scholarly output is reflected in an h-index of 18 and over 119 publications with approximately 990 citations.

Metrics

  • h-index: 18
  • Publications: 119
  • Citations: 990

Selected Publications

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

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