Team
Principal Investigator
The project is led by Luciano Dyballa, Assistant Professor of Computer Science. His research lies at the intersection of machine learning and computational neuroscience, with a focus on understanding how neural networks represent and process information. He completed his PhD at Yale University and has published work on neural representations, manifold learning, and large-scale neural data analysis in both artificial and biological systems.
Dr. Luciano Dyballa
Students
Caterina Barbero
Caterina Barbero is a student at IE University. She is investigating how the latest methods in the emerging field of AI interpretability can be improved using our encoding vs. decoding paradigm.
Collaborators
The project is embedded within the IE Intelligent Systems Research Group and benefits from interactions with researchers working in machine learning, artificial intelligence, and data science. It also connects with a broader network of collaborators across Europe and internationally, particularly in the areas of neuroscience and AI:
DAVID GÓMEZ-ULLATE
is professor of applied mathematics at IE University. His expertise in mathematical modelling, machine learning
JOHANNES BERTRAM
is a Master’s student at the University of Tübingen co-supervised by Dr. Dyballa.
GREG FIELD
is professor of neuroscience at the Jules Stein Eye Institute at UCLA.
T. ANDERSON KELLER
is a postdoctoral researcher at the Kempner Institute for the Study of Natural & Artificial Intelligence at Harvard.
SAVIK KINGER
is a PhD student at Yale University.
MICHAEL STRYKER
is a PhD student at Yale University.
STEVEN ZUCKER
is professor of computer science and biomedical engineering at Yale University.
Funded by the European Union under the Horizon Europe research and innovation programme.
This project has received funding from the European Union’s Horizon Europe research and innovation programme under the Marie Skłodowska-Curie grant agreement No 211063187