Tom has a particular interest in transport and logistics, AI hardware as well as health/bioinformatics. He has a wealth of hands-on experience in the AI space, having worked with companies across the technical spectrum in areas such as multi modal threat detection, neurological assessments, and video analysis.

Tom works with inventors during the invention capture process to ensure that the resulting patent application is robust and suitable across jurisdictions. He also regularly assists foreign attorneys to obtain European protection for AI inventions. 

Emma focuses on AI as applied to e commerce, educational tools, digital health, internet of things, as well as optics/photonics. She recognises the fast moving nature of software and the need to obtain protection quickly. She takes a proactive approach in prosecution including arranging examiner interviews and regularly advises upon acceleration mechanisms, both locally in the UK and Europe as well as across global portfolios. Emma has a particular focus on drafting applications designed to achieve the best protection possible in both Europe and the US; a skill that often requires just the right amount of compromise. In 2014 she spent time on secondment working in Silicon Valley, giving her a unique perspective of the challenges that US applicants face when patenting in Europe.

Rebecca has a particular interest in transport/logistics and AI hardware as well as electronic design. Before joining Mewburn Ellis, Rebecca worked as an electronics and firmware engineer for a technology consultancy where she undertook a variety of research and development projects for the defence and aerospace industries. Rebecca has a breadth of practical experience in FPGA design, analogue and digital electronics, radar modelling, and radio communications. Additionally, Rebecca has significant experience from her Masters project and her time as a technology consultant in applying AI/ML for signal processing, computer vision and data security applications. She has practical experience using Caffe, Pytorch, Keras, and Tensorflow to build and test neural networks such as CNNs, GANs and LSTMs.