Professor Andy Philippides is a faculty member in the School of Engineering and Informatics at the University of Sussex, where he holds the title of Professor of Biorobotics (Informatics). He has been continuously affiliated with the university since 1995, progressing from an MSc and PhD student to a permanent academic, achieving full professorship in 2017. His work is deeply interdisciplinary, bridging robotics, neuroscience, and artificial intelligence. His research interests focus on the mechanisms of intelligent behavior through the interaction of body, brain, and environment. Key areas include visual navigation in insects and robots, neuromodulation in neural networks (e.g., GasNets), evolutionary robotics, and computer vision. He leads and contributes to high-impact projects such as Brains-on-Board, INSIGHT, and be.AI, funded by EPSRC, BBSRC, MRC, and the European Union. His recent publications (2022–2025) reflect a strong trend in bio-inspired algorithms, particularly in insect navigation, spiking neural networks, and adaptive robotics. These works span journals like PLoS Computational Biology , Frontiers in Physiology , and Biomimetics , emphasizing visual route learning, memory networks, and neuromorphic computing. He has supervised over 50 MSc theses and numerous PhD students, many of whom now hold academic or industry positions. His collaborations include prominent researchers such as Paul Graham, Phil Husbands, and Tom Collett. He is actively involved in grant-funded research, with current projects extending into 2028. Action-based bio-inspired autonomous navigation (Universities UK) Emergent embodied cognition in shallow neural networks (BBSRC) be.AI - biomimetic embodied Artificial Intelligence (Leverhulme Trust) ActiveAI - active learning and selective attention (EPSRC) He teaches courses such as Intelligence in Animals and Machines and Research Methods in Neuroscience, and has previously taught in computational neuroscience and robotics. His lab, part of the Centre for Computational Neuroscience and Robotics (CCNR), fosters interdisciplinary research in biorobotics and neural modelling.










