We are pleased to announce that Patrick Lederer, postdoc in the Computational Social Choice Group at the ILLC, received an Exemplary Paper Award at the 27th ACM Conference on Economics and Computation (EC'26), which took place in Rome this July.
The paper receiving the award studies the problem of guaranteeing proportional representation in rank aggregation using the methods of social choice theory. This problem arises, for instance, when you want to aggregate several rankings of hotels based on, say, price, location, and cleanliness into a single overall ranking that adequately accounts for the importance you ascribe to each of these criteria. Thus, for instance, if you are looking for an overall ranking that is to 50% based on price, to 30% on location, and to 20% on cleanliness, then the overall ranking should agree with the price ranking on at least 50% of all pairs of hotels (and accordingly for location and cleanliness). In his paper, Patrick showed that existing methods of aggregation do not satisfy this seemingly simple requirement and designed new methods that do. The paper is available at https://arxiv.org/abs/2508.16177.
Télécom Paris, a founding member of Institut Polytechnique de Paris (IP Paris), is inviting applications for a tenure-track faculty position associated with the prestigious Hi! PARIS Chairs.
This position comes with attractive hiring packages and offer the opportunity to contribute to world-class research in Embedded and Distributed AI, with a particular focus on future robotic systems spanning humanoid robots, autonomous aerial and ground vehicles, and embodied AI platforms.Research topics include, but are not limited to, efficient AI models, distributed and multi-agent systems, reinforcement learning, and formal methods for AI verification.
KU Leuven’s Declarative Languages and Artificial Intelligence (DTAI) section is seeking outstanding researchers to advance the field of combinatorial optimization within Bart Bogaerts’ research group. Two fully-funded positions are available: a PhD role focused on developing human-understandable explanations for optimization decisions, and a postdoc role aimed at ensuring end-to-end correctness guarantees for combinatorial solvers. Both projects leverage breakthroughs like proof logging and machine-verifiable certificates to enhance reliability, auditability, and trust in AI-driven decisions—critical for high-stakes applications and compliance with regulations like GDPR. Candidates will contribute to innovative research, such as debugging via proofs, rigorous algorithm evaluation, and domain-specific explanation methods.
Applications for the PhD role close September 30, 2026, and for the postdoc role, October 30, 2026.