Oiwi Parker Jones

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Principal Investigator

Oiwi leads the Parker Jones Neural Processing Lab (PNPL) at the University of Oxford. His aim is to build bridges between deep learning and the brain, for example by accelerating the development of Brain Computer Interfaces (BCIs), but also by developing deep learning methods for interpreting brain data and leveraging principles of systems neuroscience to inform machine learning. Oiwi completed a DPhil focused on Natural Language Processing (NLP) for low-resource languages. He further trained as a postdoc in Imaging Neuroscience at UCL and Oxford, and in Applied Artificial Intelligence at the ORI. He was previously a lecturer in Medicine at St Peter's College, Oxford, and is currently Hugh Price Fellow in Computer Science at Jesus College, Oxford.

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Pratik Somaiya

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Software Engineer

Pratik joined the Oxford Robotics Institute (ORI) in May 2023 as a Robotics Software Engineer. Before that, he pursued an MSc by Research in Robotics at the Lincoln Centre for Autonomous Systems Research (L-CAS), University of Lincoln, UK. Prior to his Master's, he was a Research Assistant at L-CAS working in agri-robotics. Pratik also spent several years in the industry before joining L-CAS. During that time, he worked on developing robots for warehouse material handling and consumer robots such as vacuum cleaning robots.

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Francesco Mantegna

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Postdoctoral Research Fellow

Francesco joined PNPL as a Postdoc in 2024 after receiving his PhD in Cognitive Psychology and Neuroscience from NYU under the supervision of David Poeppel. His interests include Brain Computer Interfaces (BCIs), Neurotechnology, and Speech Neuroprosthetics.

Mats van Es

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Research Associate

Mats helps to support a broad range of electrophysiological research in PNPL. He is a Postdoc at Oxford Centre for Human Brain Activity (OHBA) where he works with Mark Woolrich to develop analysis methods for electrophysiology (e.g. EEG, SQUID-MEG, OPM-MEG) and studying temporal dynamics in functional brain networks. Mats received his PhD from the Donders Institute (Radboud University, Netherlands) with Jan-Mathijs Schoffelen, with work on how neural oscillations affect neural processing and behaviour.

Ryan Timms

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Research Associate

Ryan helps to support MEG research that involves source reconstruction. He received his DPhil from the Oxford Centre for Human Brain Activity (OHBA) under the supervision of Mark Woolrich working on unsupervised time-series machine learning techniques for MEG source reconstruction. From there, he went on to manage the Optically Pumped Magnetometer (OPM) Laboratory at UCL with Gareth Barnes and work as a Data Scientist for the BBC.

Dulhan Jayalath

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DPhil/PhD Student

Dulhan is a DPhil student in the Autonomous Intelligent Machines and Systems (AIMS) CDT. At PNPL, his work focuses on leveraging deep learning to find efficient representations of brain signals for downstream tasks (e.g. phoneme recognition from heard speech brain data). Prior to joining PNPL, he worked on multi-agent RL and reasoning with graph neural networks at the University of Cambridge. Before this, he completed his BSc in Computer Science at the University of Southampton, where he researched computer vision systems for visual navigation. He has worked on large language models at Speechmatics and developing assembly-level machine learning kernels for new hardware at Arm.

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Gilad D. Landau

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DPhil/PhD Student

Gilad is a D.Phil student currently working on decoding semantic content from the brain with AI. He is motivated by the prospect of merging brains with AI to deepen our understanding of both. His academic background is in Philosophy of Cognitive Science, where he applied a multi-disciplinary approach to explore how brains process representations. Prior to joining PNPL he worked as an applied AI researcher, developing industry-first AI systems in several domains and modalities.

Miran Özdogan

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DPhil/PhD Student

Miran's work in PNPL has recently focused on the role of sequence models, such as state space models (e.g. S4 and Mamba) for BCIs. He is also working to establish new benchmarks and standards for neural decoding, in order to quantify and accelerate progress in the field.

Luisa Kurth

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DPhil/PhD Student

My motivation is to help improving people’s lives through AI. Currently, I am mostly interested in the challenges of advancing machine learning for medical image analysis. The CDT in AIMS offers the perfect platform for this journey and I’m excited to connect with anyone sharing my interest. I hold a Bachelor's degree in Psychology from the University of Mannheim and a Master's degree from the University of Oxford's Internet Institute. During my time at Oxford, I participated in cutting-edge research on the societal and ethical aspects of AI. This experience fueled my fascination for machine learning, leading me to pursue a second Master's degree at the University of Tübingen, where I focused on the foundations of deep learning, large language models and explainable AI. Along the way, I've conducted brain research at the Max-Planck-Institute and worked as a policy researcher at the OECD. Outside of research, I enjoy reading, socializing with friends, and visiting art galleries.

Charlotte Gerhaher

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Master’s Student

Charlotte is an MSc student in Advanced Computer Science at the University of Oxford, with a background in bioinformatics and veterinary medicine. She joined PNPL for her master's thesis to work on brain data synthesis using deep generative models, addressing the scarcity of data augmentation options for brain data. Before embarking on her current studies, she completed a BSc in Bioinformatics at the Technical University of Munich and Ludwig Maximilian University, where she focused on reducing bias in state-of-the-art machine learning models for the classification of thoracic diseases in chest X-rays.

Jeremy Ridge

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Master’s Student

Jeremy is a current MSc student in Advanced Computer Science at the University of Oxford, associated with Wolfson College. He is completing his master's dissertation with the PNPL group focusing on deep learning applications for non-invasive neuroimaging data. Before coming to Oxford, he completed his bachelors at the University of Pennsylvania, double majoring in Cognitive Science and Computer Science.

Pablo Soëtard

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Master’s Student

Pablo is an MSc student in Mathematics and Foundations of Computer Science at the University of Oxford. At PNPL, his work focuses on studying the mathematical structures that encode speech on the brain, through the use of Selective State Space Models. Prior to joining PNPL, he worked on RL for quantum communication protocols at the National Research Council of Spain, and in the Neurocomputing group at UAM on neural pattern generators for robotics control. During his undergraduate years he studied a BEng in Computer Science and Engineering and another BEng in Telecommunications Engineering at UAM. He has worked on information retrieval systems, computer vision and MLOps for the past 4 summers at Google as a Research Software Engineer.

Emma Harris

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Master’s Student

Emma is an MSc student in Clinical and Therapeutic Neuroscience. Her work in PNPL has helped to refine experimental protocol around large-scale within-subject data acquisiton.

Oğuzhan Keskin

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Research Assistant

Oğuzhan’s interests include diffusion models and other methods from computer vision. He has an M.Phil. in Computer Science from Cambridge University and software engineer experience in industry.

Alumni

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• Botos Csaba
• Daniella Ye
• Birtan Demirel
• Hayley Millard
• Brian Liu
• Yonatan Gideoni