Dynamics On and Of Networks

Lyon JUNE 20-22, 2016

ENS de Lyon, Site Monod, Room Fontaine

Program

Day 1: June 20, 2016
9:30 — 10:00 Registration & Coffee
10:00 — 10:50 Alejandro Ribeiro. Graph Signal Processing Tools for Distributed Sampling and Topology Inference
10:50 — 11:15 Michael Rabbat. Models that Generate Approximately Band-limited Graph Signals
11:15 — 11:35 Coffee Break
11:35 — 12:00 Elvin Isufi and Geert Leus. Distributed 2-Dimensional Autoregressive Moving Average Graph-Temporal Filters
12:00 — 12:25 Ronan Hamon, Pierre Borgnat, Patrick Flandrin and Celine Robardet. Networks as signals: Extraction of dynamical network structures
12:45 — 14:00 Lunch
14:00 — 15:00 Hamid Krim (IEEE SPS Distinguished Lecturer). Sensor and Social Networks: A Case for Topological Data Analysis
15:00 — 15:25 Catherine Matias and Vincent Miele. Statistical clustering of human and animal contact networks through a dynamic stochastic block model
15:25 — 15:50 Marco Corneli, Pierre Latouche and Fabrice Rossi. Clustering in dynamic networks via non homogeneous Poisson processes and exact ICL
15:50 — 16:10 Coffee Break
16:10 — 17:00 Renaud Lambiotte. Burstiness and spreading on networks: models and predictions
17:00 — 17:25 Philippe Nain. Multilayer graphs: percolation, asymptotics and exact results
18:00 — 19:00 Cocktail
Day 2: June 21, 2016
9:30 — 10:20 Rajmonda Caceres. Window selection in dynamic networks
10:20 — 10:50 Coffee Break
10:50 — 11:15 Babak Fotouhi and Michael Rabbat. Evolution of the Nearest-Neighbor Degree Distribution in the Preferential Attachment Model of Network Growth
11:15 — 11:40 Diane Peurichard. Modelling of cross-linked networks
11:40 — 12:05 Tiphaine Viard and Noé Gaumont. LinkStreamViz: a drawing tool for link streams
12:05 — 12:30 Fakhteh Ghanbarnejad and Nahid Azimi-Tafreshi. How cooperation may behave differently in interacting SIS-SIR dynamics
12:45 — 14:00 Lunch
14:00 — 14:50 Nicola Perra. Modelling dynamical processes on time-varying networks
14:50 — 15:15 Klaus Wehmuth, Artur Ziviani and Eric Fleury. Modelling Dynamic Multilayer Networks as MultiAspect Graphs
15:15 — 15:45 Coffee Break
15:45 — 16:35 Kimmo Kaski. Social Physics Approach to Human Sociality: Computational Analysis and Modeling
16:35 — 17:00 Manuel Jimenez Martin. Structural balance drive in the evolution of international relationships
Day 3: June 22, 2016
9:30 — 10:20 Céline Robardet. Mining patterns in augmented graphs
10:20 — 10:50 Coffee Break
10:50 — 11:15 Charles Huyghues-Despointse, Binh-Minh Bui-Xuan and Clemence Magnien. Strong Delta-connectivity in Link Streams
11:15 — 11:40 Aurore Payen, Lionel Tabourier and Matthieu Latapy. Identifying key spreading nodes in temporal networks
11:40 — 12:05 Arnoux Thibaud, Latapy Matthieu and Tabourier Lionel. Prediction in link streams
12:05 — 12:30 Sami Jouaber, Yannick Leo, Carlos Sarraute, Eric Fleury, Marton Karsai. Impact of university admission on freshmen’ egocentric network
12:45 — 14:00 Lunch
14:00 — 14:50 Camille Roth. Calibration and validation of dynamic interaction models
14:50 — 15:15 Alessio Cardillo and Alberto Antonioni. The Evolutionary Kuramoto’s Dilemma

Registrations

Registration are now open : click here How to register:

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The registration to the workshop will be free but mandatory. Registration will include lunch and breaks and one social event/cocktail.

Motivation and Aims

Large-scale networks with complex interaction patterns between elements are found in abundance in both nature and man-made systems (e.g., genetic pathways, ecological networks, social networks, networks of scientific collaboration, WWW, peer-to-peer networks, power grid, biological networks, etc.). The main aim of this workshop is to explore the statistical dynamics on and of such networks. “Dynamics on networks” refers to the different types of so-called processes (e.g. proliferation, diffusion, random walk, etc.) that take place on networks. The functionality/efficiency of such processes is strongly affected by the topology as well as the dynamic behavior of the network. On the other hand, “Dynamics of networks” mainly refers to various phenomena that go on in order to bring about certain changes along time in the topology of the network. It has become clear that properties such as stability, robustness, information spreading,… depend of the time evolution of highly dynamical networks such as networks of mobile agents, and the study of dynamical processes on and of networks are among the hottest new theoretical challenges for Complex Network research. Accordingly, the workshop on Dynamics On and Of Complex Networks will focus on these topics. A motivation of the workshop is also to bring together scientists interested to the development of methodologies for studying networks and data on networks, especially in the domains of computer science, data analytics and processing, physics, or mathematics, or interesting in various applications. On way to address challenges about  complex networks is to deal with time evolving relationships between data, and graphs are a convenient data model for representing massive digital data sets in many applications. With such a unified representation, many information processing tasks become graph analysis problems. However, graphs are not only of interest for representing the data to facilitate its analysis, but also for defining graph-theoretical algorithms that enable the processing of data associated with both graph edges and vertices. Indeed, more generally, massive datasets represented as graphs can be seen as a set of data samples, with one sample at each vertex in the graph. In such a scenario, the high-dimensional data associated to vertices can be viewed as graph signals. There is emerging interest in the development of algorithms that enable the processing of graph signals: one might be interested in filtering, clustering, or compressing this structured type of signals. The analysis of graph signals has to address the combinatorial nature of the involved signals, that are not necessarily embedded in Euclidean spaces, and this is leading to the emergence of a new research field on “Graph Signal Processing” at the intersection of computer science, mathematics, and signal processing. This new research field aims at developing novel approaches enlarging the scope of traditional signal processing methods and applications, so that they can be applied to arbitrary graph signals. An open challenge is now to deal also with dynamics in graph signal processing.

Goals

The workshop expects burgeoning multi-disciplinary research contributions that combine methods from computer science, statistical physics, graph signal processing, nonlinear dynamics, epidemiology, econometrics and social network theory, to study common problems in systems exhibiting a complex network structure (e.g., biological systems, linguistic systems, social systems and various other man-made systems like the Internet, WWW, peer-to-peer systems etc.). The workshop will particularly promote research contributions on dynamical networks and dynamics on networks. Accordingly, one of the major goals of the workshop is to bring together different research areas (and their corresponding communities): network science, mathematics, computer science, signal processing and epidemiology.

Invited Speakers

Ramonja Caceres Rajmonda Caceres (MIT Lincoln Laboratory, Cyber Analytics and Decision Systems, Massachusetts)
Rajmonda is a member of the research staff at MIT Lincoln Laboratory, in the Cyber Analytics and Decision Systems Group. Her primary research interests are in the areas of machine learning, dynamic social networks, and network representation learning. Rajmonda earned her PhD degree in mathematics and computer science from the University of Illinois at Chicago in 2012. Her current research focuses on the development of data-driven analytics for analyzing and characterizing cyber entities and their interactions as well as development of methods for identifying detectability bounds in massive datasets with low signal-to-noise ratio.
Kimmo Kaski Kimmo Kaski (Aalto University, Finland)
Kimmo Kaski is Full Professor of Computational Science at Computer Science Department of Aalto University School of Science & Supernumerary Fellow of Wolfson College of Oxford University and Associate Fellow of Said Business School of Oxford University. He received his MSc in Electrical Engineering at Helsinki University of Technology and obtained his D.Phil. degree in Theoretical Physics at University of Oxford. He has been two five-year terms as Academy Professor of Academy of Finland, director of Centre of Excellence for two six year terms as well as holding other professorial positions in Finland and USA. He is Fellow of American Physical Society, of Institute of Physics (Chartered Physicist), of Academia Europeae, and a number of other learned societies. In research he has a broad experience in computational science and information technology in general, with current focus being on Complex Systems and Networks research, Data Science focusing on complexities of economic, techno-social, and societal systems. He is the author of more than 450 publications cited in ~12000 times (Scholar). In addition he has supervised 65 PhD students so far.
Hamid Krim Hamid Krim (NC State University Raleigh, USA)
Hamid Krim (F) received his degrees in Electrical Engineering. As a member of technical staff at AT&T Bell Labs, he has worked in the area of telephony and digital communication systems/subsystems. In 1991, he became a NSF Post-doctoral scholar at Foreign Centers of Excellence (LSS Supelec/Univ. of Orsay, Paris, France). In 1992, he joined the Laboratory for Information and Decision Systems, MIT, Cambridge, MA, as a Research Scientist performing/supervising research in his area of interest. In 1998, he joined the Electrical and Computer Engineering Department at North Carolina State University, Raleigh, N.C., where he is currently Professor and directing the Vision, Information, Statistical Signal Theories and Applications (VISSTA) Laboratory. Dr. Krim’s editorial activities include: Editorial Board Member, IEEE Transactions on Signal Processing(2002-2004); Editorial Board Member, IEEE Signal Processing Magazine (2014). Dr. Krim is an IEEE Fellow and was a Fellow, Japanese Foundation for the Advancement of Research in Science and Engineering at the University of Tokyo, Japan. Dr. Krim is a Member of SIAM and of Sigma Xi. He is an original contributor and now an Affiliate of the Center for Imaging Science, sponsored by the Army. He is a recipient, NSF Career Young Investigator Award. Dr. Krim’s research interests are in statistical signal processing and mathematical modeling with a keen emphasis on applications. He has been particularly interested in introducing geometric and topological tools to statistical signal processing problems and applications. His research has primarily centered on estimation theoretic problems and modeling. Dr. Krim has published extensively on these areas with an impact amounting to over 5000 citations to date.
Renaud Lambiotte Renaud Lambiotte (University of Namur, Belgium)
After a PhD in Physics at ULB, and Post-docs at ULg, UCLouvain and Imperial College, I am currently associate professor in the department of Mathematics of the University of Namur. My recent research includes the development of algorithms to uncover information in large-scale networks, the study of empirical data in social and biological systems, and the mathematical modelling of human mobility and diffusion on networks. I have authored more than 60 publications in peer-reviewed journals and conference proceedings, with around 5000 citations (Google Citations). I also act as an academic editor for PLoS One and the European Physical Journal B.
Nicola Perra Nicola Perra (Greenwich University)
Senior Lecturer in Network Science at the Business School of Greenwich University, London, UK. His main research interests are on: Dynamical Processes on Time-Varying Networks; Contagion Models and Adaptive Behavior; Epidemics in structured populations; Global Epidemic and Mobility Model: GLEaM; Modeling and Studying Online Social Networks; Resilience of Coevolving and Interdependent Networks and Centrality Measures on Complex Networks.
Alejandro Ribeiro Alejandro Ribeiro (University of Pennsylvania)
Alejandro Ribeiro is the Rosenbluth Associate Professor with the Department of Electrical and Systems Engineering at the University of Pennsylvania (Penn). He was born in Montevideo, Uruguay in 1975 where He lived until 2003. He received a B.Sc. degree in Electrical Engineering from the “Universidad de la Republica” in 1998 and worked for Bellsouth’s cellular operation in Uruguay for five years. He moved to Minneapolis, Minnesota on 2003 to study at the University of Minnesota (UoM). He received M. Sc. and Ph. D. degrees from the UoM on 2005 and 2007 and spent 1 year in a postdoctoral position. He started at Penn in 2008. He received the 2012 S. Reid Warren, Jr. Award presented by Penn’s undergraduate student body for outstanding teaching and the NSF CAREER award in 2010. Papers that He has coauthored received the 2014 O. Hugo Schuck best paper award and student paper awards at Asilomar 2015 (as adviser), ACC 2013 (as adviser), ICASSP 2005, and ICASSP 2006. He is also a Fulbright Scholar and a Penn Fellow. His research is in the application of signal processing to the study of networks. In particular, He has projects that involve optimal design of wireless networks, distributed signal processing and optimization, structured representations of network data, and graph signal processing.
Céline Robardet Céline Robardet (INSA de Lyon, LIRIS UMR 5205 CNRS)
Céline is a full professor at the National Institute of Applied Science in Lyon (France), member of the Laboratoire d’InfoRmatique en Image et Systèmes d’information (LIRIS, UMR 5205 CNRS) and coordinator of the Data Mining and Machine Learning team. She works on the analysis of complex systems — a broad category of data made of a large number of highly dynamic interconnected units — viewed as relational attributed dynamic graphs.
Camille Roth Camille Roth (CNRS-Centre Marc Bloch, Germany)
Camille Roth is currently a Tenured Researcher at the CNRS in Computer Science since 2008, after having been Associate Professor in Sociology at the University of Toulouse. He holds a PhD in social science (École Polytechnique, 2005), with a generalist background in maths, physics and computer science (“ingénieur des Ponts et Chaussées”, 2002) and cognitive science (MSc EHESS, 2002). Founder and current leader of the Digital Humanities / Computational Social Science team at Centre Marc Bloch Berlin, he also currently supervises an interdisciplinary team of post-doctoral and doctoral researchers at the interface between hard and social science. Author of about 50 peer-reviewed publications in both areas, He has been PI of various multi-partner projects at CNRS, including in particular Webfluence, Algopol and Algodiv (ANR 2008, 2012, 2015) and QLectives (EU IP FP7 2009) which are specifically linked to dynamic socio-semantic networks.

Submission of abstracts

We invite you to submit a one or two-page abstract.Submissions are done via our EasyChair submission link: https://easychair.org/conferences/?conf=do2net It is required that at least one author of each accepted paper register and attend the Workshop on Data Driven Approach to Networks and Language to present their work.

Important Dates

  • Abstract submission deadline: MARCH 11, 2016 (extended) FEBRUARY 24h, 2016
  • Notification to authors: MARCH 31th, 2016 (was 24th)
  • Conference date: JUNE 20-22, 2016

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