I am currently a research scientist intern at Sakana AI and doing a PhD at Imperial College London in the Adaptive and Intelligent Robotics lab. My research focuses on building open-ended and self-improving systems.

I am driven by the quest to understand General Intelligence and replicate it in silico. I view this challenge not as one of manual design, but of discovering the minimal set of simple conditions and algorithms capable of bootstrapping themselves from simplicity to high-level intelligence.

This search for self-bootstrapping algorithms points inevitably toward Open-endedness, though its significance extends far beyond general intelligence. The pursuit of open-ended systems touches on fundamental questions regarding the nature of creativity, the potential for novel solutions to emerge in artificial systems that could inspire new technologies, and the emergence of complexity.

Central to understanding these systems is Emergence. My fascination lies in how intricate behaviors can self-organize from simple interactions — a phenomenon that offers key insights into the origins of life, the definition of artificial life, and the roots of intelligence itself. To model this, I develop high-performance substrates, using them to observe the spontaneous rise of complexity.

I am also deeply interested in the emergence of Consciousness. My exploration integrates philosophy, metamathematics, and physics. Furthermore, I am driven to understand the mind itself, investigating the nature of subjective experience through meditation and the study of psychedelics.

Complementing my scientific inquiry, I bridge the rigorous with the aesthetic through Art. I have a deep appreciation for digital art and creative computation, specifically regarding their ability to visualize the beauty of complex, self-organizing systems.

	OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in Code
	The AI CUDA Engineer: Agentic CUDA kernel discovery, optimization and composition
	Discovering Quality-Diversity Algorithms via Meta-Black-Box Optimization
	Toward Artificial Open-Ended Evolution within Lenia using Quality-Diversity
	CAX: Cellular Automata Accelerated in JAX
	Quality-Diversity Actor-Critic: Learning High-Performing and Diverse Behaviors via Value and Successor Features Critics

I am an organizer of ICARL (Imperial College Autonomous Reasoning & Learning), a student-led initiative at Imperial College London. Our goal is to foster a vibrant community for students and researchers interested in the future of AI.

Our main activities include:

• 🎥 Seminar Series: We invite leading researchers from academia and industry (sponsored by Google DeepMind, InstaDeep, and Iconic) to share their work. Past talks are uploaded to our YouTube channel.
• 📚 Reading Group: We meet bi-weekly to discuss recent publications in Deep Reinforcement Learning, Generative AI, and Autonomous Agents. The group is open to everyone—feel free to get in touch!

Follow our activities and join our community through our official channels: