Bio

Mengmeng Zhu is an assistant professor in the Department of Textile Engineering, Chemistry and Science. She is also an Associate Faculty in the Operations Research Graduate Program at NC State University. She also has over six years of experience in industries including manufacturing, warehousing and distribution centers.

Zhu is the recipient of Best Paper Award in the 24th ISSAT International Conference on Reliability and Quality in Design, 2019, Best Student Paper Award in the 23rd ISSAT International Conference on Reliability and Quality in Design, 2018, and 2017 Chinese Government Award for Outstanding Self-Financed Students Abroad, respectively.

Area(s) of Expertise

Zhu’s research interests lie in computational data analytics and mathematical modeling for system reliability, resilience, and health monitoring and control. The applications of her research are on complex systems including smart health with wearable and implantable devices, energy, the Internet of Things, transportation, and software development. Her teaching interests include quality and reliability engineering, statistics, data analytics, and applied operations research.

Publications

• SDDC-YOLO: A Diagnostic Framework for Defect Detection in Industrial Materials , (2026)
• A nonlinear wiener process degradation model with damage resistance for reliability analysis , Annals of Operations Research (2025)
• Novel differential voltage features based machine learning approach to lithium-ion batteries SOH prediction at various C-rates , Energy (2025)
• Structure information based multi-component system resilience assessment framework with application to battery energy storage system design , Annals of Operations Research (2025)
• Convolutional neural network based multi-input multi-output model for multi-sensor multivariate virtual metrology in semiconductor manufacturing , Annals of Operations Research (2024)
• Damage-resistant CPS reliability modeling considering coupled system resistance effects , Reliability Engineering & System Safety (2024)
• Lifetime prediction and maintenance assessment of Lithium-ion batteries based on combined information of discharge voltage curves and capacity fade , Journal of Energy Storage (2024)
• Modeling Human–Machine Interaction System Reliability with Multiple Dependent Degradation Processes and Situation Awareness , International Journal of Reliability Quality and Safety Engineering (2023)
• Lithium-ion battery remaining useful life prediction using a two-phase degradation model with a dynamic change point , Journal of Energy Storage (2022)
• Shock-Loading-Based Reliability Modeling with Dependent Degradation Processes and Random Shocks , International Journal of Reliability Quality and Safety Engineering (2022)

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