Congratulations to postdoc Katharina Boudgoust, from the Crypto and Security group, who has won the Best early career research paper award at Crypto 2022 for ‘Some Easy Instances of Ideal-SVP and Implications to the Partial Vandermonde Knapsack Problem’. The paper is co-authored with Erell Gachon (Université de Bordeaux) and Alice Pellet-Mary (Université de Bordeaux, CNRS).

Later this month, Katharina will give a presentation of the paper at Crypto 2022, which takes place in Santa Barbara, USA from August 13-18. Crypto 2022 is organized by the International Association for Cryptologic Research (IACR).

From August 13-18, cryptographic researchers from all over the world will gather in Santa Barbara for the Crypto 22 conference. The conference recently announced all accepted papers, and 12 researchers from the department have co-authored 8 of the accepted papers.

This is a remarkable accomplishment as there is great competition at Crypto 22, and certainly underlines the strength and significance of the work done by the Cryptography and Security group.

Congratulations to professor Ioannis Caragiannis, who has won the 2022 𝐀𝐈𝐉 𝐏𝐫𝐨𝐦𝐢𝐧𝐞𝐧𝐭 𝐏𝐚𝐩𝐞𝐫 𝐀𝐰𝐚𝐫𝐝 for the paper "𝑶𝒑𝒕𝒊𝒎𝒂𝒍 𝒔𝒐𝒄𝒊𝒂𝒍 𝒄𝒉𝒐𝒊𝒄𝒆 𝒇𝒖𝒏𝒄𝒕𝒊𝒐𝒏𝒔: 𝑨 𝒖𝒕𝒊𝒍𝒊𝒕𝒂𝒓𝒊𝒂𝒏 𝒗𝒊𝒆𝒘" (Artificial Intelligence, 227:190-213, 2015), which is co-authored with Craig Boutilier, Simi Haber, Tyler Lu, Ariel Procaccia, and Or Sheffet. The AIJ Prominent Paper Award recognizes outstanding papers, published within the past 7 years in the Artificial Intelligence Journal, that are exceptional in their significance and impact.

According to the award certificate: This paper has made outstanding contributions to computational social choice by introducing a fundamentally novel approach to voting, now referred to as implicit utilitarian voting. It also initiated the prolific line of research on distortion, leading to survey and tutorial coverage of the topic as well as inclusion in graduate course material. Among its many contributions, the paper includes breakthrough results such as polynomial-time computability of the optimal randomized voting rule and a near-tight analysis of its distortion. It also provides an average-case analysis and learning-theoretic results, thus opening doors to a multi-faceted treatment of the subject.