I am a third-year Ph.D. candidate in Industrial and Systems Engineering at the University of Wisconsin–Madison, advised by Prof. Kaibo Liu. Before joining UW–Madison, I earned a B.S. in Engineering and Finance (double major) and an M.S. in Management Science and Engineering from the South China University of Technology, advised by Prof. Wenbin Zhu.

[Google Scholar] [LinkedIn] [CV] (Last updated: Jan., 2025)

Contact: ying.fu@wisc.edu

My research focuses on developing advanced machine learning, including reinforcement learning, and optimization methods to enhance prediction and decision-making across various industrial applications. Key areas include:

• Foundational Machine Learning: instance selection and high-cardinality categorical variable encoding.
• Discrete Optimization: 3D dynamic heterogeneous robotic palletization.

• Machine Learning and Optimization Integration: degradation modeling, prognostics and decision making.

• Edge Computing for Distributed Systems.

I am actively seeking a Machine Learning Engineer/Scientist internship for Summer 2025. If you’re interested in my work, feel free to reach out or email me!

Educations

Ph.D., Industrial and Systems Engineering, University of Wisconsin-Madison, Sep 2022 – present

M.S., Computer Science, University of Wisconsin-Madison, Sep 2022 – present

M.S., Management Science and Engineering, South China University of Technology, Sep 2019 - Jun 2022

B.S., Polymer Materials and Engineering and Finance (Double Major), South China University of Technology, Sep 2015 - Jun 2019

Publications

Published or Accepted

1. Ying Fu, Kaibo Liu, and Wenbin Zhu. “ Instance Selection Via Voronoi Neighbors for Binary Classification Tasks.” IEEE Transactions on Knowledge and Data Engineering (2023). (The Best Paper Finalist award in the DAIS Section of Industrial and Systems Engineering Research Conference (ISERC), 2023). [paper][code]
2. Ying Fu, Ye Kwon Huh, and Kaibo Liu, “Degradation Modeling and Prognostic Analysis Under Unknown Failure Modes.” IEEE Transactions on Automation Science and Engineering (2025). [paper][code]
3. Wenbin Zhu, Ying Fu, and You Zhou. “3D dynamic heterogeneous robotic palletization problem.” European Journal of Operational Research (2024). [paper][code]

Under revision/review

1. Ye Kwon Huh, Ying Fu, and Kaibo Liu, “A Bayesian spike-and-slab sensor selection approach for high-dimensional prognostics, “ under revision.
2. Wenbin Zhu, Xiaoting Wu, Ying Fu, and Heng-Qing Ye, “Maximum homogeneity grouping for high-cardinality categorical variables in binary classification,” under review. [code]
3. Wenbin Zhu, Runwen Qiu, and Ying Fu. “Comparative Study on the Performance of Categorical Variable Encoders in Classification and Regression Tasks,” under review. [paper][code]

Awards and Honors

• ISyE Graduate Student Travel Awards, University of Wisconsin-Madison (2023)
• Chancellor’s Opportunity Award, University of Wisconsin-Madison (2022)
• China National Scholarship, Ministry of Education of P. R. China (2017)

Teaching

• Teaching Assistant, ISyE/ME 412 “Fundamentals of industrial data analytics”, Dept. of Industrial and Systems Engineering, University of Wisconsin–Madison, undergraduate level, Spring 2025

Services

• Journal reviewer: IEEE Transactions on Automation Science and Engineering
• Membership: INFORMS, IISE, and SME
• Vice President of the SME Student Chapter, 2023-2025

Hobbies and Interests

In my free time, I am passionate about photography and hiking. I often capture photos during my hikes, and you can view my collection here. Additionally, I enjoy playing badminton and watching movies.