Research on drug discovery using LLMs and agentic workflows.

• Multi-agent reasoning and orchestration (cf. emerging “Deep Research” type of inference).
• Contributed to GSK’s GenAI system, Jules
• Acceleration of multi-node inference for LLMs pre-trained in-house, focusing on parallelisation and constrained decoding for agentic use.

Developed and deployed deep learning methods for spectral demixing, image segmentation, and super-resolution towards new product offerings. This involved R&D and MLOps. In addition to this, I have also contributed to a web-based acquisition and analysis software which involves several technologies spanning front-end, back-end and deployment.

Together with a colleague from my research group, I co-founded Wizion AI, a company offering image processing products utilising deep learning methods inspired by research in our lab. In 2020, we were selected for the Cambridge Accelerate accelerator programme at the Judge Business School. After three years of efforts towards the development of two products, we decided to shift our focus to other opportunities.

Part-time involvement in non-profit organisation. Started as a research project during master’s degree and spun out in 2019 with five fellow PhD students.

• Open-source hardware design of air quality monitor.
• Aggregate data analysis and predictive modelling.
• Deployment of sensor networks in several countries across South America, Africa, Europe and Asia. More information https://open-seneca.org

Within the Tesco Data Science department, I worked with the computer vision team on large-scale image classification for product recognition at the till to prevent theft.

I worked with Professor Phillip Stanley-Marbell, head of the Physical Computation Lab. In the research project, I modelled lightness illusions in the human visual system by attempting to reproduce them with artificial neural networks.

Researched and developed a machine learning system for a novel laser based fire detector. This involved optical engineering and signal processing using machine learning techniques.

Alongside my MSc studies, I worked part-time on a number of consultant jobs including:

• Developed a system for image analysis of a continuous video feed at a production facility overseen by food industry technology provider GEA.
• Performed data mining on a big dataset for Danish television broadcaster TV2 with results used in a program about fitness level.

Further researched the topic of my BSc thesis and wrote it up as a publication.