Hi! My name is Gabriel.

I'm a final-year undergraduate studying Computer Science and Sociology at the Ludwig Maximilian University of Munich (LMU). I’m interested in understanding how humans and animals think, learn, and make decisions—in order to engineer AI systems capable of 'reasoning' on tasks and adapting to new ones in the same ways we do.

Broadly, these are some of the research topics I've been thinking about/working on:
(Hover over list items for details.)

1. Bias.
   Manifested social and cognitive biases in both humans and AI, and how the cognitive sciences and psychology help to identify, quantify, and modify them.
2. Multimodal Machine Learning.
   Improving the integration of sensory inputs to build a coherent model of language and the world, through new learning mechanisms to overcome the limitations introduced by single data sources.
3. AI Transparency and Interpretability.
   What we can learn from human decision-making processes to improve explainability and trust.
4. Adaptability in AI Inspired by Biological Cognition.
   Machine learning techniques inspired by human and animal adaptability to uncertainty, new environments, and learning from limited and incomplete information.