Andrew Markham

Andrew Markham is a prominent academic in the field of computer science, currently serving as a Professor of Computer Science at the University of Oxford. He specializes in sensors, signal processing, machine learning, and systems, with a particular focus on how machines can better understand the physical world. His research is primarily situated within the Cyber Physical Systems (CPS) theme, where he leads a team of researchers and students.

Academic Background

• PhD in Electrical Engineering from the University of Cape Town, South Africa (2008), where he researched wildlife tracking systems using wireless sensor networks.
• BSc in Electrical Engineering (First Class Honours) from the same institution (2004).

Career Path

• Joined the University of Oxford as a Postdoctoral Fellow from 2008 to 2012.
• Appointed as an Associate Professor in 2013 and later promoted to Professor in 2021.

Research Focus

Markham's research addresses challenges in tracking and localizing people, animals, and objects, especially in environments where traditional technologies like GPS are ineffective, such as underground or indoors. His work utilizes magneto-inductive tracking and communication technologies. Additionally, he has increasingly incorporated data-driven methods and physics-informed approaches to enhance learning from noisy sensor data.

Selected Contributions

His projects include:

• The WildSensing project, which monitored badger behavior using wireless sensor nodes.
• Development of techniques for 3D tracking of animals in challenging environments.

Markham has published numerous papers in reputable journals and conferences, contributing significantly to advancements in areas such as indoor localization technologies and machine learning applications in sensor networks.

Contact Information

For further inquiries, he can be reached via email at andrew.markham@cs.ox.ac.uk or by phone at +44 1865 (6) 10729. His office is located at the Wolfson Building, Parks Road, Oxford OX1 3QD.

In summary, Andrew Markham is a distinguished figure in computer science with extensive expertise in sensor technology and localization systems, making significant contributions to both academic research and practical applications.