Dublin · Computer Science at Trinity

Neural decoding.
World models.

Noise Signal

I’m Finn. I study Computer Science at Trinity. Working in finance made me realise that I want to spend my life building technology that helps people. Neural decoding and world models are the areas I find most interesting.

Research direction

01 Research direction

Why these
two fields?

We get one life, and I want mine to be magnificent. To me, that means working on technologies with the potential to change the world and push the frontier of what humans can do—whether that is controlling the physical world with our minds or using deep learning to build intelligence that helps us solve our biggest problems. At Susquehanna, I was surrounded by brilliant maths and physics graduates, and I was disappointed to see so much of that raw talent focused on finding ever-smaller market edges.

INSIDE → OUT

Neural decoding

Neural decoding feels like magic. I want to think an instruction and have it happen, even something as simple as telling an AI agent to play a song through a speaker.

OUTSIDE → IN

World models

I think world models have a much higher ceiling than language models. Systems that learn how an environment works, predict consequences, and plan could become the most useful form of AI.

02 Work & experience