I’m Yanzhi Wang (王衍之), a final-year PhD student at the School of Advanced Manufacturing and Robotics, Peking University, advised by Prof. Jie Song and Prof. Jianxiao Wang. I received my bachelor’s degrees in science and economics from Peking University.

My research focuses on data-centric optimization: improving learning and decision-making under uncertainty through better data use. I develop data valuation methods that assess data contributions for a given model and task, guiding sample selection, weighting, and feature prioritization, with applications to power and other complex systems.

I am currently seeking postdoctoral opportunities starting in fall 2027.

You can find my CV here: PDF

Working Papers

• AI-Powered Data Valuation for Robust Financial Modelling

  Yanzhi Wang, Jianxiao Wang, Yaqin Hu, Jie Song, Xiaofei Zhao. (Undergoing Major Revision at Management Science)

• Data-Value Consensus in Federated Learning

  Yanzhi Wang, Su Wang, Jianxiao Wang, H. Vincent Poor, Jie Song. (Under Submission)

Journal Articles

• [Engineering] Data-Centric Optimization: An End-to-End Strategy for Power Systems

  Yanzhi Wang, Jianxiao Wang*, Jie Song* (advance online publication)

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• Proposed DCOpt, a framework valuing features by their economic impact in end-to-end optimization.
• Developed a rolling-horizon algorithm that reduces decision costs by 8.9% in OOD scenarios.
• Demonstrated that curating high-value features outperforms increasing data quantity using ISO-NE data.

• [IEEE Transactions on Industry Applications] Feature Selection for Battery Lifetime Prediction using Explainable Machine Learning

  Yanzhi Wang, Jianxiao Wang*, Xi Chen, Yishen Wang, Jie Song (2026)

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• [Nexus] Bridging Prediction and Decision: Advances and Challenges in Data-Driven Optimization

  Yanzhi Wang, Jianxiao Wang*, Haoran Zhang, Jie Song* (2025)

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• Analyzed frameworks for integrating prediction and decision-making.
• Compared advancements in multidimensional data-driven optimizations
• Addressed challenges in data input, modeling, and decision processes
• Highlighted applications in power systems, management, and control

• [IEEE Transactions on Industrial Informatics] Data Purification for Improved Power Dispatch Against Renewable Uncertainty

  Yanzhi Wang, Jianxiao Wang, Jie Song* (2025)

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• [IEEE Transactions on Industry Applications] Dissecting Renewable Uncertainty via Deconstructive Analysis-Based Data Valuation

  Yanzhi Wang, Jie Song* (2025)

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• [Patterns] Unveiling Value Patterns via Deep Reinforcement Learning in Heterogeneous Data Analytics (Cover of the May 2024 Issue)

  Yanzhi Wang, Jianxiao Wang*, Feng Gao, Jie Song* (2024)

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• We introduce a learning-based paradigm for data valuation across scenarios.
• Our study identifies varying effects of high/low-quality data on model efficacy.
• This method explores inherent and transferable value patterns across datasets.
• Analysis reveals data value’s geographic sensitivity in nationwide power forecasts.

• [Management Review (In Chinese)] Research on the Circulation and Revenue Sharing Mechanisms of Data Elements: An Example of Integrating Meteorological Data in Wind Power Scenarios, Yanzhi Wang, Jingsi Huang, Jianxiao Wang, Feng Gao, Jie Song* (2024)

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• [Chinese Journal of Management Science (In Chinese)] Research on Data Value Based on Demand Forecast of Online Medical Platform, Zhao Yue, Yanzhi Wang, Jingsi Huang, Jie Song*, Xuan He (2024)

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Conference Articles

• [IAS 2024] Feature Valuation Toward Improved State Estimation for Automotive Lithium-ion Battery

  Yanzhi Wang, Jianxiao Wang*, Jie Song

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• [CASE 2022] What Drives Patients to Choose a Physician Online? A Study based on Tree Models and SHAP Values

  Yanzhi Wang, Yue Zhao, Jie Song*, Hongju Liu

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Honors and Awards

• 2026.09 National Scholarship
• 2025.09 National Scholarship
• 2025.05 Presidential Scholarship (Peking University)
• 2024.10 Youth Talent Support Program for Doctoral Students, China Association for Science and Technology
• 2024.09 National Scholarship
• 2024.06 Wei-Ming PhD Scholars Program (One of 13 recipients selected university-wide)
• 2024.05 Academic Rising Star (One of 5 recipients selected college-wide)
• 2022.01 Outstanding Undergraduate Research Award (College of Engineering, Peking University)

Skills

• Programming: Python, MATLAB, R.
• Academic Training: Advanced Theory of Probability, Advanced Operations Research, Optimization Methods in Machine Learning, Reinforcement Learning, Distributed Optimization, Design and Analysis of Algorithms, Carbon Neutrality and Energy Internet, etc.