Professor Hong Lin PhD

Dr. Hong Lin is a senior professor in Computer Science & Engineering Technology at the University of Houston-Downtown. He earned his PhD in Computer Science from the University of Science and Technology of China in 1997. Prior to joining UHD, he held positions including Postdoctoral Research Associate at Purdue University and Assistant Research Officer at the National Research Council of Canada. He is Chair of the Computer Science Curriculum Committee at UHD. His research spans brain-state modelling, human-centered computing, parallel/distributed computing, and big data analytics.

Education Details 

• PhD: Computer Science (University of Science and Technology of China, 1997)
• Postdoctoral Research Associate: Purdue University

Professional Background

• Professor (Current) - Department of Computer Science and Engineering Technology, University of Houston-Downtown.
• Program Director (Current) - Master of Science in Artificial Intelligence, UHD.
• Supervisor - Grid Computing Lab, UHD.
• Co-founder - Data Center, UHD.
• Assistant Research Officer (Former) - National Research Council, Canada.
   

Achievements 

• Senior Member of the Association for Computing Machinery (ACM).
• Chair of the Computer Science Curriculum Committee at UHD.
• Guest Associate Editor for Digital Public Health (Frontiers in Public Health).
   

Current Research Projects

• Brain State Modeling: Developing advanced algorithms for EEG data analytics to understand human brain states and assist in promoting human healthcare.
• Cognitive Intelligence Applications: Research focused on human-centered computing and cognitive intelligence systems.
• Image Processing for Medicine: Applying deep learning methods and computer vision techniques for medical image analysis (e.g., brain tumor classification, infectious disease detection)
   

Academic Profiles of Professor Hong Lin:

• University Faculty Profile
• Google Scholar
• ResearchGate

Professor Lin's research spans computer science, engineering, and biomedical applications. The following list presents five of his most recent publications in descending chronological order, prioritizing relevance to his core expertise.

•  Lin, H., Li, Y., & Rajinikanth, V. (2023). Optimized Convolutional Neural Networks for Automated Brain Tumor Classification using MRI Data. Journal of Medical Systems, 47(1), 14. DOI: 10.1007/s10916-023-01861-w.
• Rajinikanth, V., Rajamani, A., Lin, H., & Dey, N. (2023). A novel strategy for the early detection of brain tumor using texture and color-based features. International Journal of Imaging Systems and Technology, 33(2), 522-535. DOI: 10.1002/ima.22849.
• Lin, H., Luan, H., Yang, L., Han, C., S, Zhang, H., Zhu, H., & Chen, G. (2023). Numerical simulation and consequence analysis of accidental hydrogen fires in a conceptual offshore hydrogen production platform. International Journal of Hydrogen Energy, 48(27), 10250-10263. DOI: 10.1016/j.ijhydene.2023.01.077.
• Dey, N., Rajinikanth, V., Lin, H., et al. (2022). Ensemble Learning for Classification of Brain State from EEG Signal. IEEE Access, 10, 9866-9877. DOI: 10.1109/ACCESS.2022.3142750.
• Lin, H., Han, C., Yang, L., et al. (2022). Numerical investigation on performance optimization of offshore sandwich blast walls with different honeycomb cores subjected to blast loading. Journal of Marine Science and Engineering, 10(11), 1743. DOI: 10.3390/jmse10111743.

Last Updated on October 09, 2025