Andrew Dai

I am an AI Researcher at Aleph Alpha, where I work on Large Language Models (LLMs), Quality Diversity (QD), and open-endedness.

My humble beginnings started with Mechanical Engineering in Trinity College Dublin, where I co-founded Formula Trinity Autonomous with amazing close friends and teammates.

After reading Ken and Joel's book, I've learned that ambitious objectives can deceive us from greatness, inspiring me on a collaborative journey to reflect on the way that I (and artificial systems that I build with my team) can "achieve our highest goals by being willing to abandon them", ultimately making us more creative.

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Research

Authors marked with an asterisk (*) denote equal contribution first authors. Representative works are highlighted.

QDAIF utilizes LMs to both vary texts and evaluate subjective quality/diversity of creative texts, enabling search of diverse high-quality solutions in vast spaces of subjectivity.

MF image-gen system enables expression of complex, nuanced concepts with arbitrarily interleaved inputs of multiple modalities and languages.

ViTs applied to behavioural cloning for AVs from offline video data, lending itself to more interpretable decision-making.

Other Projects

These include coursework, side projects and unpublished research work.

Applying advancements in NeRF (e.g. NeX-MPI, PlenOctrees) to AR demos within a home (and notebook).

Autonomous Racing (Formula Student Driverless racing, F1TENTH) is cool - co-founded with Jakub Pyszka, Senan Stanley, Katherine Hardgrave, and curious TCD students

Control, state estimation, perception, path planning on sim robots. Project done while on exchange in Year 4.

Design and source code from Jon Barron's website. Jekyll Now fork of design from Leonid Keselman