Christopher Kirkbride

Dr. Christopher Kirkbride is a Senior Lecturer in Management Science at Lancaster University's Management School. His research focuses on decision-making under uncertainty, employing methodologies such as stochastic dynamic programming, simulation, and approximate dynamic programming to address challenges in project scheduling, nuclear decommissioning, workforce planning, and asset management. He actively supervises PhD students and participates in interdisciplinary research groups like STOR-i and the Lancaster Intelligent Systems Centre.

Key research projects include optimizing nuclear decommissioning processes and developing resource allocation strategies for dynamic environments. He has presented at major conferences such as EURO and IFORS, contributing to both academic and applied operational research communities. His work bridges theoretical advancements with practical applications, emphasizing robust solutions for stochastic systems.

Dr. Kirkbride advises PhD students on topics including reinforcement learning applications and optimization for dynamic systems. His grants include projects funded through STOR-i, focusing on reinforcement learning safety and machine learning-optimization integration. He collaborates with teams specializing in simulation, stochastic modeling, and intelligent systems, further enhancing interdisciplinary research impact.