Hsiao-Ping Ni
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Mail code: 5706Campus: Tempe
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Student Information
Graduate StudentArtificial Intelligence Engineering (Mechanical Engineering)
Ira A Fulton Engineering
Dr. Ni is a Postdoctoral Research Scholar in Electrical, Computer, and Energy Engineering. His research leverages artificial intelligence and digital twin approaches to enhance the reliability and efficiency of semiconductor systems. During his PhD at ASU, he developed and evaluated AI models using real-time data from semiconductor facility energy systems, with a focus on predictive performance, anomaly detection, and supply chain resilience. Currently, he is extending this work across the semiconductor lifecycle—exploring explainable, reliability-aware AI methods in chip–package co-design and operations. His goal is to develop practical tools and insights that advance dependable and efficient semiconductor technologies.
Ph.D. Systems Engineering, Arizona State University 2025
M.S. Robotics & Autonomous Systems (Systems Engineering), Arizona State University 2022
B.S. Mechanical Engineering, Michigan State University 2017
*: Corresponding Author
- Ni, H. P.*, Liu, C. Y., Paul, F., Chong, W. O., & Chou, J. S. (2025). Enhancing supply chain resilience and efficiency of HVAC systems in semiconductor manufacturing facilities using graph-based large multimodal models. Applied Energy, 398, 126420.
- Li, Y.*, Liu, C. Y., Ni, H. P., Paul, F., Chong, W. O., & Chou, J. S. (2025). Generative artificial intelligence-based framework for bridging lifecycle gaps in semiconductor HVAC systems. Journal of Building Engineering, 112349.
- Ni, H. P.*, Liu, C. Y., Li, Y., Chong, W. O., & Chou, J. S. (2025). Enhancing HVAC energy efficiency modeling in semiconductor manufacturing facilities using tree-structured parzen estimator-optimized deep learning. Building and Environment, 271, 112589.
- Ni, H. P.*, & Chong, W. O. (2024). Semiconductor fab energy optimization and data-intensive energy efficiency modeling. Engineering Technology Open Access Journal. 5(5): 555674.
- Ni, H. P.*, Chong, W. O., & Chou, J. S. (2024). Optimizing HVAC systems for semiconductor fabrication: A data-intensive framework for energy efficiency and sustainability. Journal of Building Engineering, 89, 109397.
Mechanical System Engineer (2022-2025), Internship, United Integrated Services, USA
Robotic Systems Design Engineer (2021), Internship, 2Unify, USA
Research And Development Engineer (2020), Internship, Easy Field Corporation, Taiwan
Development Engineer (2019), Full-time, SINBON Electronics, Taiwan