Yu-Zheng Lin

ENG 257

1127 E. James E. Rogers Way P.O. Box 210020

Tucson, AZ 85721-0020

Yu-Zheng Lin is a Ph.D. candidate in the Electrical and Computer Engineering at the University of Arizona. He received his M.S. degree from the National Taiwan University of Science and Technology (TaiwanTech). Previously, he worked as a research assistant at the National Synchrotron Radiation Research Center in Taiwan. His research interests include signal processing, control systems, complex systems, artificial intelligence, and cyber-physical security.

news

Sep 29, 2025	My project, Toward Resilience in Cyber-Physical Systems: A Generative Digital Twin–Enabled Dynamic Data-Driven Framework for Decision-Making under Uncertainty, has been awarded an NSF ACCESS Explorer allocation of 200,000 credits (equivalent to $5,000 based on CloudBank Exchange Rates). I serve as the Principal Investigator (PI) on this project.
Sep 18, 2025	My paper titled “LLM-HyPZ: Hardware Vulnerability Discovery using an LLM-Assisted Hybrid Platform for Zero-Shot Knowledge Extraction and Refinement” was accepted to the Accepted by IEEE International Conference on Data Mining (ICDM) 2025 Workshop - LLM4Sec.
Sep 14, 2025	My paper titled “DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework” was accepted to the IEEE Transactions on Artificial Intelligence (TAI).
Jul 16, 2025	Yu-Zheng Lin has been competitively selected for and completed the CI Pathways Machine Learning & AI Track, a training program jointly organized by the National Center for Supercomputing Applications (NCSA) and the Pittsburgh Supercomputing Center (PSC). View Certificate (PDF)
Jan 14, 2025	Yu-Zheng Lin, serving as Principal Investigator (PI), has been awarded acceptance into the OpenAI Researcher Access Program. The award provides $2000 in API credits to support research on large language model (LLM) stability, with applications to high-performance computing, digital twins, and cybersecurity.
Nov 19, 2024	Yu-Zheng Lin received the Outstanding Teaching Assistant Award from the University of Arizona College of Engineering. (Course: ECE 513: Web Development and the Internet of Things) More Detail
Jul 22, 2024	Yu-Zheng Lin has been selected for and completed the CoDaS-HEP (Computational and Data Science for High Energy Physics) program at Princeton University, with full travel funding support. The program focused on advanced high-performance computing topics, including machine learning, parallel computing, and large-scale data processing. More Detail

selected publications

Discussion and improvement of a blade-type XBPM with coupling suppression by compensating calibration coefficients

J-Y Chuang, Y-Z Lin, Y-M Hsiao, and 8 more authors

Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2020

DOI Bib HTML

@article{chuang2020discussion,
  title = {Discussion and improvement of a blade-type XBPM with coupling suppression by compensating calibration coefficients},
  author = {Chuang, J-Y and Lin, Y-Z and Hsiao, Y-M and Liu, Y-C and Shu, D and Kuan, C-K and Wu, H and Sheng, I-C and Cheng, Y-T and Shueh, C and others},
  journal = {Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment},
  volume = {953},
  pages = {163174},
  year = {2020},
  publisher = {Elsevier},
  doi = {10.1016/j.nima.2020.163174},
}

DT4I4-secure: Digital twin framework for industry 4.0 systems security

Yu-Zheng Lin, Sicong Shao, Md Habibor Rahman, and 2 more authors

In 2023 IEEE 14th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2023

DOI Bib

@inproceedings{lin2023dt4i4,
  title = {DT4I4-secure: Digital twin framework for industry 4.0 systems security},
  author = {Lin, Yu-Zheng and Shao, Sicong and Rahman, Md Habibor and Shafae, Mohammed and Satam, Pratik},
  booktitle = {2023 IEEE 14th Annual Ubiquitous Computing, Electronics \& Mobile Communication Conference (UEMCON)},
  pages = {0200--0209},
  year = {2023},
  organization = {IEEE},
  doi = {10.1109/UEMCON59035.2023.10316090}
}

DDD-GenDT: Dynamic data-driven generative digital twin framework

Yu-Zheng Lin, Qinxuan Shi, Zhanglong Yang, and 5 more authors

arXiv preprint arXiv:2501.00051, 2024

Accepted by IEEE Transactions on Artificial Intelligence

DOI Bib

@article{lin2024ddd,
  title = {DDD-GenDT: Dynamic data-driven generative digital twin framework},
  author = {Lin, Yu-Zheng and Shi, Qinxuan and Yang, Zhanglong and Latibari, Banafsheh Saber and Satam, Shalaka and Shao, Sicong and Salehi, Soheil and Satam, Pratik},
  journal = {arXiv preprint arXiv:2501.00051},
  doi = {10.48550/arXiv.2501.00051},
  year = {2024},
  note = {Accepted by IEEE Transactions on Artificial Intelligence},
}

Autonomous Vehicle Security: Hybrid Threat Modeling Approach

Amal Yousseef, Yu-Zheng Lin, Shalaka Satam, and 5 more authors

IEEE Open Journal of Vehicular Technology, 2025

DOI Bib

@article{yousseef2025autonomous,
  title = {Autonomous Vehicle Security: Hybrid Threat Modeling Approach},
  author = {Yousseef, Amal and Lin, Yu-Zheng and Satam, Shalaka and Latibari, Banafsheh Saber and Pacheco, Jesus and Salehi, Soheil and Hariri, Salim and Satam, Pratik},
  journal = {IEEE Open Journal of Vehicular Technology},
  year = {2025},
  publisher = {IEEE},
  doi = {10.1109/OJVT.2025.3580538},
}

HWREx: AI-enabled Hardware Weakness and Risk Exploration and Storytelling Framework with LLM-assisted Mitigation Suggestion

Sujan Ghimire^*, Yu-Zheng Lin^*, Muntasir Mamun, and 10 more authors

ACM Transactions on Design Automation of Electronic Systems, 2025

*Authors contributed equally to this research.

DOI Bib

@article{10.1145/3737459,
  author = {Ghimire, Sujan and Lin, Yu-Zheng and Mamun, Muntasir and Chowdhury, Muhtasim Alam and Alemi, Farhad and Cai, Shuyu and Guo, Jinduo and Zhu, Mingyu and Li, Honghui and Saber Latibari, Banafsheh and Rafatirad, Setareh and Satam, Pratik and Salehi, Soheil},
  title = {HWREx: AI-enabled Hardware Weakness and Risk Exploration and Storytelling Framework with LLM-assisted Mitigation Suggestion},
  year = {2025},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  issn = {1084-4309},
  url = {https://doi.org/10.1145/3737459},
  doi = {10.1145/3737459},
  journal = {ACM Transactions on Design Automation of Electronic Systems},
  note = {*Authors contributed equally to this research.},
}