معرفی
Edward Lam is a Research Fellow in the Department of Data Science and Artificial Intelligence at Monash University. His research focuses on the intersection of combinatorial optimization and neuro-symbolic AI, developing algorithms for routing, scheduling, control, and analytics, primarily applied to automated decision-making in transportation and logistics. He holds a PhD in Computer Science (2019) and a BSc(Hons) in Mathematics and Statistics (2010), both from the University of Melbourne. Lam is affiliated with CSIRO Data61 and actively supervises PhD students in optimization and machine learning.
**Education**:
- PhD in Computer Science, University of Melbourne (2019)
- BSc(Hons) in Mathematics and Statistics, University of Melbourne (2010)
**Research Interests**: Combinatorial optimization, neuro-symbolic AI, multi-agent systems, and applications in autonomous logistics. His work addresses challenges in routing, scheduling, and decision-making under constraints.
**Article Trends**: Recent publications emphasize branch-and-cut-and-price algorithms for multi-agent pathfinding, electric vehicle routing, and hybrid optimization methods. His work bridges theoretical algorithm design with real-world applications in transportation and warehousing.
**Awards**: Received the Doctoral Research Award (2019) for outstanding contributions to optimization algorithms.
**Advising & Grants**: Currently accepting PhD students focused on combinatorial optimization and machine learning, with available scholarships. Collaborates on projects funded by industry and governmental entities like CSIRO.
**Affiliations**: Maintains an external position at CSIRO Data61 and has contributed to patents in optimization algorithms (2018).
