Andrew Markham is a Professor of Computer Science and he works on sensors, signal processing/machine learning, and systems. His research revolves around making machines better understand the physical world. He works within the Cyber-Physical Systems (CPS) theme and leads a large group of researchers and students. He investigates how to track and localize people, animals, and objects, particularly in environments where technologies like GPS fail, such as underground or indoors. Key to this is the use of magneto-inductive tracking and communication. His work is typically cross-disciplinary and he collaborates with colleagues from a wide range of disciplines. Increasingly, his research has turned to data-driven methods and physics-informed approaches to learning from noisy sensor data. He obtained his PhD from the University of Cape Town, South Africa in 2008 researching the design and implementation of a wildlife tracking system, using heterogeneous wireless sensor networks. Within the department, he was a Postdoctoral Fellow from 2008 to 2012, he was appointed as an Associate Professor in 2013 and awarded the title of full Professor in 2021.