I’m Yanzhi Wang (王衍之), a third year PHD student at the College of Engineering, Peking University, fortunate to be advised by Prof. Jie Song(Google Scholar) and Prof. Jianxiao Wang(Google Scholar). My research interests include data centric AI, data-driven optimization, energy systems and uncertainty estimation. You can find my Google Scholar profile here.

Recently, my research centers on advancing the interpretability of data science within energy systems. I am particularly interested in leveraging AI and data-driven methodologies to implement end-to-end optimization. My current work emphasizes enhancing the reliability and efficiency of energy systems under uncertainty through data-centric decision-making.

I am actively seeking academic exchanges for next year. You can find my CV here: [PDF]

🔥 News

• 2025.2:  🛩️🛩️ Heading to Princeton as a VSCR this autumn!
• 2024.10:  🛩️🛩️ Going to Seattle for INFORMS 2024!

📝 Publications (Article)

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

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

  [PDF]

• 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)

  [PDF]

[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)

[PDF]

• 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.

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

  Yanzhi Wang, Jie Song* (2024)

  [PDF]

• [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)

  [PDF]

• [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)

  [PDF]

📝 Publications (Conference)

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

  Yanzhi Wang, Jianxiao Wang*, Jie Song

  [PDF]

• [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

  [PDF]

📝 Manuscripts under submission

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

  Yanzhi Wang, Jianxiao Wang*, Jie Song* (Accepted by Engineering)

• Feature Selection for Battery Lifetime Prediction using Explainable Machine Learning

  Yanzhi Wang, Jianxiao Wang*, et al. (Accepted by IEEE Transactions on Industry Applications)

• Condensed Data Acquisition for Non-Intrusive Load Monitoring via Household Selection

  YiHang Jin, Yanzhi Wang, Jianxiao Wang*, et al. (Submitted to CSEE Jornal of Power and Energy Systems)

🎖 Honors and Awards

• 2024.10 The Youth Talent Support Program of the China Association for Science and Technology (Doctoral Program)
• 2024.09 National Scholarship
• 2024.06 Wei-Ming PhD Scholars (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 level)

📖 Educations

• 2022.09 - now, Ph.D. in Industrial and Systems Engineering (GPA=3.75), College of Engineering, Peking University, Beijing, China.
• 2019.09 - 2022.07, B.E. in Economics, National School of Development, Peking University, Beijing, China.
• 2018.09 - 2022.07, B.E. in Theoretical and Applied Mechanics (GPA=3.62), College of Engineering, Peking University, Beijing, China.
• 2015.06 - 2018.07, RDFZ, Beijing, China.

🧩 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.

💬 Invited Talks

• 2022.04, Physician word-of-mouth ratings in complex models, 2022 International Conference for Chinese Scholars in Industrial Engineering

💻 Internships

• 2022.07 - 2022.08, Beijing International Big Data Exchange, China.