The 11th International Conference on Prestigious Applications of Intelligent Systems, PAIS 2022, will take place on July 25th, 2022 in Vienna, Austria, as a subconference of IJCAI-ECAI 2022, the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence.
The PAIS 2022 Programme chairs invite papers describing innovative applications of AI techniques to real-world systems and problems. Artificial Intelligence (AI) is a central topic in contemporary computer science and has enabled many groundbreaking developments which have significantly influenced our society. Techniques, concepts, and results developed under the banner of AI research have proven to be of fundamental importance in areas such as medicine, biology, economics, philosophy, linguistics, psychology and engineering; furthermore, they have proven to have a significant impact on several real-world applications, such as e-commerce, tourism, e-government, national security, manufacturing and other economic sectors. Consequently, AI has become increasingly important in neighbouring fields.
Papers highlighting all aspects of the application of intelligent systems technology are most welcome. Our aim is to provide a forum for academic and industrial researchers and practitioners to share experience and insight on the applicability, development and deployment of intelligent systems. PAIS is the largest showcase of real applications using AI technology worldwide and is the ideal place to meet developers of successful applications.
The call for papers is available here.
May 6, 2022: Abstract submission deadline
May 13, 2022: Paper submission deadline
June 3, 2022: Notification of paper acceptance
June 17, 2022: Camera-ready papers due
July 25, 2022: PAIS conference
Note: all deadlines are 23:59 Central European Time (CET), UTC +1, Paris, Brussels, Vienna.
The proceedings of PAIS are freely available here (https://dx.doi.org/10.3233/
9:05 Best paper: Orbit Slot Allocation in Earth Observation Constellations. Sara Maqrot, Stephanie Roussel, Gauthier Picard and Cédric Pralet.
9:40 Optimizing Laser-Induced Graphene Production. Lars Kotthoff, Sourin Dey, Jake Heil, Vivek Jain, Todd Muller, Alexander Tyrrell, Hud Wahab and
10:05 Learning Path Constraints for UAV Autonomous Navigation under Uncertain GNSS Availability. Marion Zaninotti, Charles Lesire, Yoko Watanabe and Caroline P. C. Chanel.
10:30 Sensor-based Moisture Prediction for Flat Roofs. Giacomo Da Col, Marco Hudelist, Christoph Schinko, Erich Teppan, Eva Eggeling and Christof
10:45 Coffee Break
11:15 Parallel scheduling of complex requests for a constellation of Earth observing satellites. Samuel Squillaci, Stéphanie Roussel and Cédric Pralet.
11:40 Automating the resolution of flight conflicts: Deep reinforcement learning in service of air traffic controllers. George Vouros, George Papadopoulos, Alevizos Bastas, José Manuel Cordero and Rubén Rodríguez Rodríguez.
12:05 Supervised Anomaly Detection in Crude Oil Stabilization. Mattia Silvestri, Michele Lombardi, Emiliano Mucchi, Luca Cadei, Giovanna Magnago,
Marco Piantanida, Valentina D’Ottavio, Nguyen Van Tu, Simona Duma, Silvia Taddei, Annagiulia Tiozzo, Andrea Corneo, Lorenzo Lancia, Laura Rocchi and Pietro Coffari di Gilferraro.
12:30 Lunch Break
14:00 Point of Interest Category Prediction with Under-Specified Hierarchical Labels. Nikolaos Lagos, Salah Ait-Mokhtar and Ioan Calapodescu.
14:25 Constrained Hardware Dimensioning for AI Algorithms. Allegra De Filippo and Andrea Borghesi.
14:40 Interpretable Identification of Mild Cognitive Impairment Progression using Stereotactic Surface Projections. Misgina Tsighe Hagos, Ronan P. Killeen, Kathleen M. Curran and Brian Mac Namee.
15:00 Coffee Break
15:30 Informed Deep Learning for Epidemics Forecasting. Federico Baldo, Michele Iannello, Michele Lombardi and Michela Milano.
15:55 Few-shot Question Generation for Personalized Feedback in Intelligent Tutoring Systems. Devang Kulshreshtha, Muhammad Shayan, Robert Belfer, Siva Reddy, Iulian Vlad Serban and Ekaterina Kochmar.
16:20 Do you like dancing robots? AI can tell you why. Allegra De Filippo, Paola Mello and Michela Milano.
Andrea Passerini (Università degli Studi di Trento, Italy)
Thomas Schiex (INRAE, France)
Peter Flach (University of Bristol, UK)
Tristan Cazenave (LAMSADE Université Paris Dauphine PSL CNRS, France)
Andrea Galassi (University of Bologna, Italy)
Philipp Slusallek (DFKI, Germani)
Pascal Van Hentenryck (Georgia Institute of Technology, USA)
Peter Haddawy (Mahidol University, Thailand)
Manon Ruffini (Aibstract, France)
Paolo Bouquet (University of Trento, Italy)
Simon de Givry (INRAE – MIAT, France)
Marco Lippi (University of Modena and Reggio Emilia, Italy)
Gregory Provan (University College Cork, Ireland)
Nathalie Vialaneix (INRAE – MIAT, France)
Barry O’Sullivan (University College Cork, Ireland)
Michela Milano (DISI Universita’ di Bologna, Italy)
Andre Augusto Cire (University of Toronto, Italy)
Georgiana Ifrim (University College Dublin, Ireland)
Louise Travé-Massuyès (LAAS-CNRS, France)
Fabrice Rossi (CEREMADE – Université Paris Dauphine PSL, France)
Meelis Kull (University of Tartu, Estonia)
Nicolas Dobigeon (University of Toulouse, France)
Ramya Srinivasan (Fujitsu Research of America, USA)
Andreas Hotho (University of Wuerzburg, Germany)
Sébastien Destercke (CNRS, UMR Heudiasyc, France)
Régis Sabbadin (INRAE – MIAT, France)
Cédric Pralet (ONERA Toulouse, France)
Isabelle Bloch (ENST – CNRS – LTCI, France)
Florent Teichteil-Königsbuch (Airbus Central Research & Technology, France)
Jacopo Staiano (LIP6, UPMC – Sorbonne Université)
Mathieu Serrurier (IRIT, Toulouse, France)
For any question about PAIS please write to email@example.com