About
I completed my PhD in AI & Computational Neuroscience in 2024, followed by a role as a Computational Biologist at an immuno-oncology startup in Stockholm. I'm now building something cool - stay tuned! 🚀
Work Experience
Stealth
Founder
June 2025 - -
Remote
Now building an AI start-up mapping how AI systems perceive and represent brands - bringing interpretability research into the real world. I combine strong technical execution (backend, ML pipelines, product design) with a bias toward action and delivery.
Moleculent
Computational Biologist
September 2024 - March 2025
Stockholm, Sweden
- Built an end-to-end pipeline to clean and process high-res spatial omics images, boosting signal quality for downstream analysis.
- Applied ML techniques including normalizing flow models, Graph Attention Networks (GATs), and clustering to extract insights from protein marker data.
- Automated image processing with Nextflow and developed interactive tools for scientists using napari + scverse.
- Reduced processing time and improved accuracy of spatial cell-cell interaction analysis.
The University of Edinburgh
PhD student
October 2020 - July 2024
Edinburgh
The focus of my PhD was to find an EEG biomarker for rare neurodevelopmental disorders with supervised machine learning. Features were calculated from EEG recordings collected from rat models and human patients to explore translational possibilities such as data augmentation. XAI techniques identified the critical features influencing these models’ predictions, opening up exciting possibilities: Could this technology accurately assess how rodent models mimic human disorders? Or could it enhance medical diagnostics and deepen our understanding of the cellular impacts of particular mutations?
Skills List
Skills List
Selected Publications:
- Single-Channel EEG Artifact Identification with the Spectral Slope (IEEE BIBM) [view]
- Face-valid phenotypes in a mouse model of the most common mutation in EEF1A2-related neurodevelopmental disorder (Disease Models and Mechanisms) [view]
- Spike-to-excite: photosensitive seizures in artificial neural networks
- Identifying Translatable EEG Biomarkers for SYNGAP1 Haploinsufficiency with Explainable Machine Learning (In preparation)
Grants & Awards:
- Simons Trust Imbizo Follow Up Grant (2024)
- PhD scholarship (tuition and stipend) awarded by the Engineering and Physical Research Council (EPSRC) (2020)
Conference Presentations:
- Single-Channel EEG Artifact Identification with the Spectral Slope IEEE International Conference on Bioinformatics and Biomedicine (December, 2023)
- Identifying Translatable EEG Biomarkers for SYNGAP1 Haploinsufficiency International League Against Epilepsy, Newcastle (September 2023)
- Quantifying the Spectral Slope in Neurodevelopmental Disorders IEEE Engineering in Medicine and Biology, Glasgow (2022)
Teaching:
- Mentor: undergraduate Neuroscience Honours student, undergraduate BEng and Computer Science Student (January - April 2023)
- Teaching Assistant: Statistics Practical in R (October - December 2022)
IBRO-Simons Computational Imbizo
Student
July 2022 - September 2022
Cape Town
The Imbizo is a machine learning and computational neuroscience school in Cape Town. Alongside lectures on neuronal biophysics, network dynamics and machine learning, I worked on building a sleep scorer using a Convolutional Neural Network (CNN) to distinguish between sleep and wake states from spectrogram images.
Key Skills:
- Computer Vision, PyTorch, CNNs
Presentation:
- Exploring autoencoders to classify EEG recordings into sleep stages IBRO-Simons Computational Neuroscience Imbizo, Cape Town (2022)