Alessandra Carbone
Professor, Sorbonne Université

Title: Deep Learning in protein-protein interactions

Abstract: Most proteins perform their biological functions by interacting with other molecules or themselves. Identifying protein-protein interactions (PPI) therefore provides biological information on protein functions, disease prevalence and the development of therapies. However, finding the interacting protein pairs using experimental approaches is time-consuming and labor-intensive due to the diversity of proteins. Deep Learning methods have enabled major advances in predicting the three-dimensional structure of proteins from genomes, predicting the functions and attributes of a protein and in modifying and designing new task-specific proteins. During this talk, various methods and recent breakthroughs in Deep Learning enabling unprecedented results in reconstructing protein-protein interactions networks and estimating changes in binding affinity will be presented.

Biography: A. Carbone is Professor of Computer Science at Sorbonne University, Director of the Laboratory of Computational and Quantitative Biology (LCQB) and co-director of the Bioinformatics and Modeling (BIM) Master’s program. She develops deep learning methods, mathematical models based on statistics and combinatorics, and algorithmic approaches to study the fundamental principles of cellular functioning from genomic data. Its projects aim to understand the principles of evolution and co-evolution of molecular structures. It concerns genome evolution, ancient genomes and adaptation, protein-protein interactions and their evolution.

Oana Goga
Chargée de Recherches CNRS

Title: Measuring and mitigating risks with online platforms

Abstract: In this talk, I will discuss risks associated with online platforms and present methodological approaches for measuring and mitigating these risks. I will provide insights from some of our latest results on political ad micro-targeting, marketing to children, and exposure to misinformation. I will discuss how our measurement studies informed European lawmaking, how citizens can help, and how laws can help detection algorithms.

Biography: Oana Goga is a tenured research scientist at the French National Center for Scientific Research (CNRS), and a member of the Inria CEDAR team and the Laboratoire d’Informatique d’Ecole Polytechnique (LIX). She investigates risks for humans and society brought by online platforms and their deployments of AI, such as advertising technologies. Her research is interdisciplinary, and she works with economists, social scientists, and legal scholars. Her work has influenced European law, and she currently serves as an external expert for the European Commission on problems related to data access and online platforms regulations. She received the Lovelace-Babbage Award from the French Science Academy and the French Computer Society in 2023; and she received an ERC Starting Grant in 2022 that aims to measure and mitigate the impact of AI-driven information targeting. Her research received several awards, including the Honorable Mention Award at The Web Conference in 2020 and the CNIL-Inria Award for Privacy Protection 2020.

Anthony Coutant
Cofounder | Co-CEO | CTO
HephIA

Title: Trajectoire d’une Startup Deep Tech en IA : De l’IA Exploratoire pour les Industries à l’IA Générative pour le Droit

Abstract: Dans cette présentation, nous explorerons le parcours d’HephIA, notre entreprise, depuis ses premiers pas dans la recherche en intelligence artificielle jusqu’à son engagement actuel dans le développement d’outils génératifs pour le secteur juridique. Vous comprendrez comment nous, chez HephIA, avons progressivement transformé des concepts de pointe en prototypes fonctionnels, contribuant à innover dans la pratique du droit. Cette présentation soulignera nos efforts et notre détermination à surmonter les défis scientifiques et technologiques, tout en illustrant notre engagement envers une technologie transformative.

Biography:

Harley Davis
Athena Decision Systems

Title: AI Agent Precision: Maximizing Decision Accuracy with Business Rules Integration

Abstract:

Biography: