Jacob Buckelew

Jacob Buckelew is a Graduate Research Assistant at Scope Lab focused on neuro-symbolic planning and optimization for large combinatorial cyber-physical systems. His research tackles the challenge of solving large-scale optimization problems that combine discrete choices with continuous parameters—a fundamental problem in transportation, routing, and resource allocation.

Jacob’s work bridges machine learning and classical optimization techniques, developing hybrid approaches that leverage the strengths of both neural networks and symbolic solvers. This combination is essential for addressing real-world combinatorial problems in the lab’s projects that involve millions of possible decisions and constraints.