Alvise Raccanelli

Cosmology · Artificial intelligence

Alvise
Raccanelli

Portrait of Alvise Raccanelli
Cosmologist · AI researcher

Exploring the Universe
Understanding intelligence

I am a cosmologist and Associate Professor at the University of Padova, working on large-scale structure, gravitational waves and fundamental physics. I also research AI and machine learning, bringing the statistical and mathematical tools of cosmology to the study of intelligence.

Explore my researchAI research instituteAI ventures
Research interestsFoundations of intelligenceCosmology & fundamental physicsAI

Current & previous institutions

University of Padova CERN Johns Hopkins Caltech NASA JPL University of Barcelona Institute of Cosmology & Gravitation

Research

Cosmology & Intelligence

I study how we extract information from complex systems: the structure of the Universe, and the models that learn from data.

Cosmology & fundamental physics

Using the Universe
to test our theories

My cosmology research uses the large-scale structure of the Universe and gravitational waves to investigate gravity, dark matter and the early Universe.

Galaxy clustering & gravityModeling how galaxies cluster across cosmic time, including redshift-space distortions, relativistic and wide-angle effects, to test cosmological models.
Gravitational waves & dark matterConnecting gravitational-wave observations with galaxy surveys, and investigating primordial black holes as a possible component of dark matter.
Future cosmological observationsDeveloping methods for optical and radio surveys, intensity mapping and multi-messenger cosmology.
Explore my cosmology research
Large-scale structureGravitational wavesDark matter
AI & machine learning

Understanding how
intelligent systems learn

I apply the statistical and mathematical perspective of physics to questions in artificial intelligence, alongside work on practical AI systems.

Foundations of learningThe principles governing neural-network learning, the propagation of information and the development of useful representations.
Representation learning & scientific inferenceHow machine learning can capture structure in complex data while preserving the information needed to answer scientific questions.
Matching & recommendationSystems that connect people, opportunities and contexts, with objectives and evaluation grounded in the decisions they support.
AI research & applied projects
Learning dynamicsRepresentation learningApplied AI

Early exploration: CosmoJEPA. A recently started research project investigating joint embedding predictive architectures for cosmology, with the aim of developing it into a paper.

Fundamental AI research

1609 Institute

Foundations of intelligence

My initiative for fundamental AI research, focused on the mathematical, physical and statistical principles underlying intelligence and learning.

Explore 1609 Institute
Applied artificial intelligence

AI ventures

Consulting & intelligent systems

Through Gufo Intelligence and Gufo Oracle, I work on AI consulting, practical AI systems, and matching and recommendation technology.

Explore AI ventures

Experience & affiliations

Rooted in cosmology
Working across physics & AI

I am an Associate Professor in the Department of Physics and Astronomy “Galileo Galilei” at the University of Padova. My research career has focused on using cosmological observations to test fundamental physics.

That work has taken me through Caltech, NASA’s Jet Propulsion Laboratory, Johns Hopkins University, the University of Barcelona and CERN. The same questions of information, inference and model building now also inform my research in artificial intelligence.

Alongside my academic work, I develop AI projects and advise teams through Gufo Intelligence, and pursue fundamental AI research through the 1609 Institute.

Contact

Collaborations

For collaborations in cosmology or AI, consulting and technology projects

Academic inquiries