NEWS: I am currently a postdoctoral fellow at the University of Regina, working with Sandra Zilles and Howard Hamilton until December 2010. From January 2011 I will take an assistant professorship position at Aalborg University.
From 2008 to August 2010 I was a postdoc at the University of Toronto working with Craig Boutilier on topics of utility elicitation, decision making under uncertainty and optimization. I hold a PhD in Artificial Intelligence from EPFL, Lausanne, Switzerland (obtained in 2007). My interests are within the following areas: recommender systems, constraint and planning systems, personal agents, preferences and user modeling, intelligent interfaces, machine learning, adaptive systems. You can download my full CV or look at my research page.
current research interests
I am currently investigating preference reasoning and elicitation for automatic tools like personal agents or recommender systems. In our opinion, preference-elicitation should be open-ended allowing a diversity of modalites to acquire user models and target recommendations. Users should be allowed to state preferences in a way that is natural and convenient to them. At the same time, AI systems need to optimize their actions reasoning with a partial model of the user preferences or utility function. These topics are elaborated in my research statement.
selected publications:
- Paolo Viappiani, Craig Boutilier. Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets. NIPS 2010. [PDF]
- Craig Boutilier, Kevin Regan, Paolo Viappiani. Simultaneous Elicitation of Preference Features and Utility. AAAI 2010 [PDF].
- Paolo Viappiani, Craig Boutilier. Regret-based Optimal Recommendation Sets in Conversational Recommender Systems. ACM Recommender Systems 2009 [PDF].
- Paolo Viappiani, Pearl Pu, Boi Faltings: Preference-based search with adaptive recommendations. AI Communications 21(2-3): 155-175 (2008) [PDF].
- P. Viappiani, B. Faltings and P. Pu. Preference-based Search using Example-Critiquing with Suggestions. Journal of Artificial Intelligence Research (JAIR), 27, 2006, pp. 465-503. [PDF]