Viappiani Paolo - CV


Viappiani Paolo

Chargé de recherche CNRS


Paolo Viappiani is a CNRS researcher since 2012, affiliated with LIP6 (Sorbonne Université) until September 2021, and since then affiliated with LAMSADE (Université Paris Dauphine). He holds an engineering diploma from Politecnico di Milano and a PhD in Computer Science from EPFL.

His research interests span algorithmic decision theory, artificial intelligence, recommender systems.



Vandeputte J., Herold P., Kuslii M., Viappiani P., Muller L., Martin C., Davidenko O., Delaere F., Manfredotti C., Cornuéjols A., Darcel N. (2023), Principles and Validations of an Artificial Intelligence-Based Recommender System Suggesting Acceptable Food Changes, The Journal of Nutrition, vol. 153, n°2, p. 598-604

Communications avec actes

Pourkhajouei S., Toffano F., Viappiani P., Wilson N. (2023), An Efficient Non-Bayesian Approach for Interactive Preference Elicitation Under Noisy Preference Models, in Zied Bouraoui ; Srdjan Vesic, Berlin Heidelberg, Springer International Publishing, 308-321 p.

Bronzini M., Robbi E., Viappiani P., Passerini A. (2023), Environmentally-Aware Bundle Recommendation Using the Choquet Integral, in Kobi Gal . Ann Nowé ; Grzegorz J. Nalepa ; Roy Fairstein ; Roxana Rădulescu, Amsterdam, IOS Press, 3182-3189 p.

Konieczny S., Moretti S., Ravier A., Viappiani P. (2022), Selecting the Most Relevant Elements from a Ranking over Sets, in Florence Dupin de Saint-Cyr, Meltem Öztürk-Escoffier, Nico Potyka, Springer, 172-185 p.

Napolitano B., Cailloux O., Viappiani P. (2021), Simultaneous Elicitation of Scoring Rule and Agent Preferences for Robust Winner Determination, in Dimitris Fotakis, David Ríos Insua, Springer, 51-67 p.

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