Ecole polytechnique, Institut Polytechnique de Paris
Department: Computer Science
City: Palaiseau (Greater Paris area)
Posted on: Tuesday, 24 January 2023
Application Deadline: Wednesday, 15 March 2023
Job Language Requirements: English or French
Ecole polytechnique, leading engineering school in France, member of Institut Polytechnique de Paris, welcomes applications for several academic positions, jobs starting in september 2023
1 Monge Assistant Professor in Computer Science, specialty "Foundation of Computer Science", full-time tenure track position 1 Professor or Monge Assistant Professor in Computer Science, specialty "Quantum information and computing", full-time tenure or tenure track position
The recruits are expected to join LIX, the joint CS lab of Ecole Polytechnique and CNRS, partner of Inria.
Learn about us:
Institut Polytechnique de Paris, https://www.ip-paris.fr/en/home-en/
Ecole Polytechnique, https://www.polytechnique.edu/en
DIX (CS department), https://portail.polytechnique.edu/informatique/en
LIX (CS lab), https://www.lix.polytechnique.fr
Precise informations (and in particular contacts) regarding each of these job offers are available following the link:
Applications are open until March 15, 2023.
Addressing the problem of fairness is crucial to safely use machine learning algorithms to support decisions with a critical impact on people’s lives such as job hiring, child maltreatment, disease diagnosis, loan granting, etc. Several notions of fairness have been defined and examined in the past decade, such as statistical parity and equalized odds. The most recent fairness notions, however, are causal-based and reflect the now widely accepted idea that using causality is necessary to appropriately address the problem of fairness.
The main objective of our research is to measure discrimination as accurately as possible. To this end, we make a distinction between the concepts of “bias” (a deviation of an estimation from the quantity it estimates) and “discrimination” (the unjust or prejudicial treatment of different categories of people on the ground of race, age, gender, disability, etc.).
In this seminar we start by illustrating why causality is essential to reach this objective of accurately measuring fairness. Then, we show how causality can be used to characterise and quantify four types of bias, namely, representation bias, confounding bias, selection bias, and measurement bias. Finally, we briefly present the different research directions we are pursuing at Comète team related to ethical/responsible AI.
Sami Zhioua is an advanced researcher at Comète team (INRIA Saclay-Île-de-France) since September 2021. His current research work focuses on ethical aspects of Machine Learning and AI. In particular, he is working on measuring and mitigating discrimination (fairness) and privacy leaks in automated decision systems using causality. Previously, he worked on privacy enhancing technologies such as Tor, malware analysis, industrial control system (SCADA) security, and using reinforcement learning (RL) to solve software engineering problems. He holds a Ph.D. in Computer Science from Laval University, Québec, Canada and his academic experience includes research and teaching positions at McGill University, KFUPM, and HCT Dubai.
Lix is co-organising the conference “21th EU/ME meeting x Quantum School-Emerging optimization methods: from metaheuristics to quantum approaches” Troyes 17th - 21th april 2023. https://perso.isima.fr/~lacomme/GT2L/EUME_JE/EUME_Joint_Event.php
Le département d’informatique de l’École polytechnique (DIX) a organisé, le 5 décembre 2022, une journée de rencontres étudiants-entreprises au laboratoire d’informatique (LIX). Cet événement a permis aux élèves et étudiants en informatique de l’École de rencontrer un panel d’entreprises, pour la plupart partenaires du laboratoire, qui ont présenté leurs activités ainsi que les grands enjeux opérationnels et de recherche auxquels elles sont confrontées.