Xizhuo(Cici) Zhang

💫Welcome to my website!

I'm Xizhuo(Cici) Zhang, a Ph.D. candidate and Graduate Teaching Associate at the Department of Industrial & Systems Engineering, The University of Tennessee Knoxville, TN, U.S.A.

Research Goal: I aim to develop and validate new technologies at the frontier of Data Analytics and Quantum Computing.

I am especially motivated by problems where rigorous modeling, scalable algorithms, and real-world impact come together, from physics-informed learning and uncertainty-aware AI to spatiotemporal systems in biomedical and engineering domains.

Email | LinkedIn | Google Scholar

Education

Ph.D. in Industrial & Systems Engineering (2024 - Present)

University of Tennessee Knoxville, U.S.A.
Advisor: Dr. Bing Yao

M.S. in Computational Technology & Engineering (2021 - 2024)

University of Chinese Academy of Sciences, China

B.Eng. in Mechanical Engineering (2017 - 2021)

Shandong University, China
Honors Degree, Top 1%

Research Interests

Data-Knowledge Fusion and Trustworthy AI/ML, focusing on multi-source and multi-task learning, physics-augmented and geometry-aware models, and domain knowledge integration for reliable prediction and decision support in complex systems.
Uncertainty-Aware Analytics for Decision-Making Support, focusing on calibrated uncertainty quantification, active learning, risk-aware forecasting, and decision quality under sparse, noisy, and costly data conditions in real-world business and operational settings.
High-Performance Quantum Computing for Scalable Analytics, focusing on hybrid quantum-classical algorithms (such as variational quantum linear solvers with pre-encoding) and quantum machine learning for large-scale inverse problems and high-dimensional physical systems.
Applied AI/ML for Advanced Data-to-Decision Applications, focusing on healthcare (including cardiac electrophysiology, disease detection, and medical operations), robotics (such as generative design and control of soft robots), and sustainable energy (covering thermal-aware chip and battery design, as well as clean energy systems like wave, tidal, and solar power).

Publications

[J4] Zhang, X., Wang, Z., Liu, F., Yao, B.* (2026). P-K-GCN: Physics-augmented Koopman-enhanced Graph Convolutional Network for Deep Spatiotemporal Super-resolution. IISE Transactions. (under major revision) [Paper]

[J3] Zhang, X. & Yao, B.* (2026). Physics-augmented Multi-task Gaussian Process for Modeling Spatiotemporal Dynamics. IEEE Transactions on Automation Science and Engineering, 23, 13316-13329. [Paper]

[J2] Zhang, X. & Yao, B.* (2026). Geometry-aware Active Learning of Spatiotemporal Dynamic Systems. IISE Transactions, 1–22. [Paper]

[J1] Zhang, X., Zhang, L., Yuan, Y., & Zhai, Q.* (2020). Life Cycle Assessment on Wave and Tidal Energy Systems: A Review of Current Methodological Practice. International Journal of Environmental Research and Public Health, 17(5), 1604. [Paper]

More works (quantum computing) are available online soon. Please stay tuned !

Selected Awards

Best Paper Finalist (1/4) (Oct 2025) [news]. QSR Best Refereed Paper Competition, INFORMS Annual Meeting, Atlanta, GA, USA.
Graduate Student Senate (GSS) Travel Award (May 2026). The University of Tennessee, Knoxville, TN, USA.
NSF Student Travel Award (May 2025). IISE Annual Conference, Atlanta, GA, USA.
Graduate Fellowship of UTK (Aug 2024). The University of Tennessee, Knoxville, TN, USA.
Graduate Excellence Scholarship (Nov 2022). University of Chinese Academy of Sciences, China.
Outstanding Graduate (Jan 2021). Shandong University, China.
Academic Excellence Scholarship (Top 1%) (Dec 2020). Shandong University, China
National Third Prize (Nov 2019). 4th "Guangwei Cup'" China Composites Society University Students Science and Technology Innovation Competition, China