There will be an associated school on complex networks and graph models from December 7-8. The schedule for the school is available here.

On Wednesday, December 9 we offer two (optional) possibilities.

1. Collaboration day at EURANDOM. No talks are scheduled, the space is available. It's designed for people who have existing collaborations to work at the meeting, or for people to start new ones.
2. A tutorial day at WINE2015 in Amsterdam. If you are interested to attend the tutorial day, please send us e-mail and indicate this on your registration for WAW2015. (An additional fee up to 20 euro for coffee and lunch may apply.) More information for the interested participants will follow.

• Robustness of spatial preferential attachment networks. Emmanuel Jacob and Peter Mörters.
• Local clustering coefficient in generalized preferential attachment models. Alexander Krot and Liudmila Ostroumova Prokhorenkova.
• Hyperbolicity, degeneracy, and expansion of random intersection graphs. Matthew Farrell, Timothy Goodrich, Nathan Lemons, Felix Reidl, Fernando Sánchez Villaamil and Blair D. Sullivan.
• Degree-degree distribution in a power law random intersection graph with clustering. Mindaugas Bloznelis.
• Upper bounds for number of removed edges in the erased configuration model. Pim van der Hoorn and Nelly Litvak.
• The impact of degree variability on connectivity properties of large networks. Lasse Leskelä and Hoa Ngo.
• Navigability is a robust property. Dimitris Achlioptas and Paris Siminelakis.
• Local majority dynamics on preferential attachment graphs. Mohammed Abdullah, Michel Bode and Nikolaos Fountoulakis.
• Rumours spread slowly in a small world spatial network. Abbas Mehrabian and Jeannette Janssen.
• A note on modeling retweet cascades on Twitter. Ashish Goel, Kamesh Munagala, Aneesh Sharma and Hongyang Zhang.
• The robot crawler number of a graph. Anthony Bonato, Rita M. Del Rio-Chanona, Calum MacRury, Jake Nicolaidis, Xavier Perez-Gimenez, Pawel Pralat and Kirill Ternovsky.
• PageRank in undirected random graphs. Konstantin Avrachenkov, Arun Kadavankandy, Liudmila Ostroumova Prokhorenkova and Andrei Raigorodskii.
• Bidirectional PageRank estimation: from average-case to worst-case. Peter Lofgren, Siddhartha Banerjee and Ashish Goel.
• Distributed algorithms for finding local clusters using heat kernel PageRank. Olivia Simpson and Fan Chung Graham.
• Strong localization in personalized PageRank vectors. Huda Nassar, Kyle Kloster and David Gleich.