Status : PhD Student
Title of thesis : "Assessing Intellectual Property Relevant Similarities In Images Through Algorithmic Decision Systems"
Research Topic / Interests : This PhD Thesis is at the crossroads of Deep-Learning and Intellectual Property. This project aims at assessing Intellectual Property (IP) relevant similarities, with a focus on image recognition technologies. Current Algorithmic decisions systems are developed by private companies for the purposes of IP enforcement (monitoring infringing goods online, filtering out content) and registration by IP Offices. We aim at exposing the biases of such systems, and propose new, unbiased and open-source algorithms for these decisions systems.
ARIAC Work Package : WP1 -interactions between humans and AI: interactive/human-in-the-loop algorithms, user assistance/AI-in-the-loop, consensus mechanisms, imperfect multi-expert labels, explainable AI