🎓 I am currently pursuing a PhD in the Department of Logistics and Maritime Studies at the Faculty of Business, The Hong Kong Polytechnic University (PolyU). I hold a master’s degree in Mechanical Engineering (2026) and a bachelor’s degree in Industrial Engineering (2023), both from Guangdong University of Technology (GDUT).

🏆 Across my studies, I have published 5 papers in leading international journals, received 11 scholarships, secured 11 invention patents, and won 19 competition awards. I was also honored as an Outstanding Graduate of GDUT.

🌐 Beyond academia, I actively share study notes and technical insights on CSDN, where my blog has attracted 24k+ followers, 5.8M+ reads, 18k+ favorites, and 87k+ shares. This platform allows me to engage with a broader community, offering technical solutions and fostering knowledge exchange.

👥 I am passionate about collaborating on challenging projects that intersect discrete optimization, algorithms, and practical applications. If you are tackling complex problems or working on cutting-edge solutions, let us connect and create something interesting together!

• Master’s Degree in Mechanical Engineering, Guangdong University of Technology, Guangzhou, Guangdong, China, September 2023 ~ June 2026

  • GPA: 92.4/100

  • Ranked 3rd and 1st out of 514 (Top 1%) in the comprehensive grade-level assessments of 2024 and 2025

  • Chief Supervisor: Prof. Lijun Wei; Co-Supervisor: Prof. Roberto Baldacci

• Bachelor’s Degree in Industrial Engineering, Guangdong University of Technology, Guangzhou, Guangdong, China, September 2019 ~ June 2023

  • GPA: 88.8/100, ranked 4th out of 85 (Top 5%)

  • Ranked 6th out of 743 (Top 1%) for comprehensive score; recommended for post-graduate study

  • Chief Supervisor: Prof. Lijun Wei; Co-Supervisor: Dr. Hao Zhang

• Programming: Java; Python; C/C++; Matlab;

• Basic Exact Methods: (Integer) Linear Programming, Dynamic Programming, Branch-and-Bound...

• Advanced Exact Methods: Branch(-Cut)-and-Price, (Logic-Based) Benders Decomposition...

• Meta Heuristics: Tabu Search, Variable Neighborhood Search, Iterated Local Search...

• Swarm Intelligence Heuristics: Particle Swarm, Artificial Fish Swarm, Artificial Bee Swarm...

• Classic Machine Learning: KNN, SVM, Tree-Based Methods (Random Forest, XGBoost)...

• Deep (Reinforcement) Learning: MLP, CNN (Resnet), RNN (LSTM), GNN (GCN), DQN, PPO, AC, DDPG...

• Data Analysis: Grey Relation Analysis, Fuzzy Comprehensive Evaluation...