Jalil Ahmed
I am a machine learning researcher with a background in engineering, working primarily with deep learning systems for complex, real-world data. My experience spans model development, evaluation, and deployment under practical constraints, with a growing focus on understanding why and when learning systems succeed or fail. Rather than treating neural networks as black-box tools, I am interested in their generalisation behaviour, interpretability, uncertainty, and the structure of the relationships they learn. My long-term aim is to pursue a career that bridges theory, systems, and application, contributing to the development of machine learning methods that are robust, understandable, and reliable in high-impact settings.