As part of the MICS Seminar series, Eyal Briman will present his research and academic journey.

Abstract: Collective decision-making lies at the core of many consequential systems in modern society, including democratic elections, online governance, resource allocation, and increasingly, AI systems that interact with human groups. Computational Social Choice (COMSOC) provides rigorous tools for studying how individual preferences can be aggregated into collective decisions, and how to evaluate the fairness, efficiency, and computational tractability of these processes. Despite major advances, existing COMSOC models remain too restrictive for many real-world settings. Classical frameworks typically assume that the outcome is simple, such as a single winner, a fixed set, or a static allocation, and that the alternatives are explicitly given in advance. In practice, however, collective decisions often involve complex, structured outputs, such as collaborative documents, ranked lists, or multi-period allocations. Moreover, alternatives may themselves need to be generated, negotiated, or arranged during the decision process, and preferences may be expressed indirectly through delegation, proxy voting, or AI-assisted intermediaries. My research addresses these challenges by studying two interconnected forms of complexity: complex outputs and complex inputs. Addressing them requires new theoretical models, algorithmic techniques, and applications spanning collaborative content creation, democratic governance, fair resource allocation, and AI-mediated deliberation.

Biography: Eyal Briman is a PhD student in the Faculty of Industrial Engineering and Management at Ben-Gurion University of the Negev (Israel), supervised by Prof. Nimrod Talmon. His research focuses on Computational Social Choice, with an emphasis on application-oriented social choice under structural constraints He is a recipient of the DATAIA Traveling research grant at Paris-Saclay University and a Pratt Fellow.