Hongle Yu
Aspiring Supply Chain Scientist · MSc Candidate in Analytics for Transport & Mobility
Interested in Complex Logistics Systems Engineering, Supply Chain Data Engineering, and Transportation Optimization.
Seeking roles as a Data Engineer, AI Engineer, Data Scientist, or Optimization / Simulation Engineer.
Specifically interested in 4TU EngD programs in Data Science and Autonomous Systems.
About
MSc candidate in Analytics for Transport and Mobility with a strong foundation in Intelligent Logistics.
Experienced in developing predictive models and optimization algorithms (TSP, Operations Research) to solve
complex supply chain challenges. Proven track record in international logistics firms like S.F. Express and KOSTAL.
Education
MSc Operations Management & Logistics: Analytics for Transport & Mobility
Affiliated with the Information Systems group (IE&IS department) · Seeking an EngD opportunity within the 4TU network.
BSc Logistics Management: Intelligent Logistics
GPA: 3.387 / 4.0 · Rank: 7 / 71 · Third-Class Scholarship 2024, 2025
Bachelor's Thesis: Developed a Machine Learning pipeline to predict truck delivery delays using CatBoost and Optuna, achieving a test AUC of 0.918.
Projects
Built a truck delivery delay prediction system using ensemble machine learning models including XGBoost, LightGBM,
and CatBoost on logistics operation data. Designed a temporal cross-validation framework to prevent data leakage
and improve evaluation reliability. Applied SHAP interpretation, feature ablation analysis, and Optuna-based
hyperparameter optimisation within a modular Python pipeline. Test AUC: 0.918.
- Solved a Traveling Salesman Problem (TSP) using Gurobi and OR-Tools in Python.
- Formulated a facility location model covering five major regions in China using PuLP.
Experience
Intern, Management Trainee and Warehouse Operations
- Managed frontline delivery and inventory control through operational rotations in a high-volume hub.
- Collaborated with cross-functional teams to optimize daily sorting and dispatching efficiency.
Intern, Production Planning & Warehouse Operations
- Adjusted daily production plans based on real-time line status and material supply fluctuations.
- Applied ABC classification to prioritize high-value components, improving resource allocation.
- Operated within WMS to streamline warehouse workflows and support stable material supply.
Activities
Third Prize (University Level)
- Solved a production scheduling problem for an MRI manufacturer using Excel Solver.
- Modeled and optimized transportation routes using Linear Programming.
Skills
Machine Learning scikit-learn, XGBoost, LightGBM, CatBoost, Optuna, SHAP
Programming Python, pandas, NumPy, Jupyter Notebook, SQL
Operations Research Gurobi, OR-Tools, PuLP, Linear Programming, Excel Solver
Supply Chain Systems WMS, Production Planning, Inventory Analysis, ABC Classification
Languages Native Chinese, English (IELTS 7.0 / C1 Level — Listening 6.5, Reading 8.0, Writing 6.5, Speaking 7.0)
Independent & Self-driven
Effective Communication
Stakeholder Coordination
Critical Thinking
Structured Planning
Adaptability & Resilience
Result-oriented
Looking to build a long-term career in Supply Chain & Data Engineering.
Open to opportunities in Data Engineering, AI Engineering, Data Science, and Optimization / Simulation Engineering.
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