AI-Descartes: Combining Data and Knowledge for Scientific Discovery

Speaker: Cristina Cornelio, Samsung Research

Abstract

Scientists aim to create mathematical models that accurately describe observed phenomena. In the past, models were manually created from domain knowledge and subsequently validated using data. More recently, models are automatically extracted from large datasets using machine learning algorithms. However, finding meaningful models from data remains an ongoing challenge. AI-Descartes is a scientific discovery framework that merges logical reasoning with symbolic regression, enabling the creation of interpretable models with minimal data requirements.

AI-Descartes website

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Bio

Cristina Cornelio is a Research Scientist at Samsung Research. Following her doctoral studies at the University of Padua (Italy), she spent five years as a research scientist at IBM Research, contributing her expertise to both the T.J. Watson research center in New York and the IBM Zurich lab. In 2021, she transitioned to a new position at the Samsung AI center located in Cambridge (UK). Her main research focus lies in neuro-symbolic integrations, which involve combining machine learning techniques with standard reasoning methods. In particular, her interest is dedicated to symbolic representation in neural models and automated scientific discovery.

Personal page: https://corneliocristina.github.io