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Diana Mangalagiu Reims Management School, France Institute for Scientific Interchange Foundation, Italy [email protected] [email protected]. My background. Engineer, Polytechnic University, Bucharest, Romania (1992) MSc in Microelectronics, University of Strasbourg, France (1994) - PowerPoint PPT Presentation
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Diana Mangalagiu
Reims Management School, France
Institute for Scientific Interchange Foundation, Italy
My background
Engineer, Polytechnic University, Bucharest, Romania (1992)
MSc in Microelectronics, University of Strasbourg, France (1994)
PhD in Artificial Intelligence, Ecole Polytechnique, Paris (1999)
MSc in Management, University of Sorbonne, Paris (2000), in Sociology, University of Sorbonne, Paris (2001)
Reader, HEC School of Management, Paris
Manager, Centre for Central and Eastern European Studies
Expert, World Bank, EU and UN agencies
Higher education reform, collaborative learning, entrepreneurship capabilities and business incubators
development, (Argentina, Brazil, Chile, Kazakhstan, Latvia, Lithuania, Moldova, Poland, Romania, Russia,
USA)
My research interests
Social and spatial interactions between socio-economic agents (individuals, firms or groups of economic entities)
Diffusion / contagion / segregation phenomena
Organizational dynamics: co-evolution of hierarchy and informal networks in organizations
Corporate social responsibility
Market dynamics: social influence on real estate price dynamics
Innovation
Reims Management School
Founded in 1928
Master, Bachelor, MBA, PhD, Executive Education programs
3500 students
25% of the students from abroad
15 years of collaboration with China (Fudan, Tsinghua)
Double Degree Bachelor and Master programs (Fudan)
MBA students exchange (Tsinghua)
PhD students
I.S.I. (Institute for Scientific Interchange) Foundation
International Center of Excellence on Complex Systems
http://www.isi.it
Four divisions:
Epidemiology and Life Sciences Division (11 researchers)
Multi-Agent Systems Division (20 researchers)
Quantum physics Division (7 researchers)
Statistical Physics Division (16 researchers)
Epidemiology and Life Sciences Division
Environmental Epidemiology
Genetic susceptibility to chronic disease
Development of biomarkers
Bioethics
Multi-Agent Systems Division
Biological systems
Financial and real estate markets
Socio-economic systems
Quantum physics Division
Properties of matter at the microscopic scale
Quantum algorithms
Statistical Physics Division
Computational Neuroscience
Combinatorial optimization algorithms, medical imaging
I.S.I. Foundation
Objectives:
Coordinate activities of the Complexity Pathfinder in NEST
Support recruiting and rising of the young researchers
Discover, connect and transfer complexity information
Find, catalogue, rank and present relevant activity
Initiate and coordinate new complexity research
GIACSGeneral Integration of the Applications of Complexity in Science
NEST Coordination Action(http://www.giacs.org/)
Biophysics Biochemistry and Informatics
Brain, respiration and cardiaccausalities in anaesthesia:BRACCIAAneta StefanovskaExperimental measurement,time series analysis andmathematical modeling ofanaesthesia.
Complexity: Agents, Volatility,Evidence and Scale: CAV ESScott MossModelling procedures for theformation of social policy inconditions of uncertainty.
Financial Markets and Complexity:Uncertainty, Heterogeneous MicroAgentsand Aggregate Outcomes:ComplexMarketsMark Salmonrisk , welfare and stability, growth,efficient resources and informationtransfer. Financial phenomena:volatility excess, crashes, speculativebubbles, departures from equilibrium
Common Complex CollectivePhenomena in StatisticalMechanics, Society , Economics,and Biology: Co3Sorin SolomonAdaptation of autocatalyticfluctuations to noise.Localized objects with complexadaptive properties not explained byPDE distinction between the typicaland the average behavior; rare events
Starlings in flight: understandingpatterns of animal groupmovements: StarFlagGiorgio ParisiLarge number of heterogeneousagents that interact exchanginginformation-> pattern formation
Measuring and ModellingComplex Networks AcrossDomains: MMCOMNETFelix Reed-TsochasUnified and cross-disciplinaryunderstanding of the behaviourand functional properties ofcomplex networks: BiologicalSupply chains, High-techinnovation,
Critical Events in EvolvingNetworks CREENJanusz Holystscientific community and itsepidemic-like behaviour (scientificavalanches).Spreading of information inscientific and publiccommunication networks.
Emergent organisation in complexbiomolecular systems EMBIORobert GlenAssimilate molecular data fromsources world-wide. Linking andanalysing data - extract knowledge -predict properties.
Extreme Events: Causes and Consequences: E2-C2 (Michael Ghil)Extract the distribution of these events from existing data sets.Reproduce the data-derived distribution of events. Predict thelikelihood of extreme events in prescribed time intervals.
Interacting Agents and Markets Networks and Social Self-organization
Human behaviour ThroughDynamics of Complex SocialNetworks : and InterdisciplinaryApproach: DYSONET PanosArgyrakisStatistical Physics concepts ->panic, search, traffic, humanrelationship,epidemics, Economicsand Finance, and EnvironmentOptimization principle?
Unifying Networks for Science& Society: UniNet(Markus Kirkilionis)Links among entities on differentscales.Reinterpretation of transferredtheories in the context of differentapplications. Math.“unification of theoryfeedback cycle”
Collaborative Complexity – Collaborations as Complex SystemsCOLL-PLEXITY (Gunther Schuh, Aaachen)Production Industry. Failure Rate. Control networks system analysis.Individual companies as individuals in a network .From GenericNetwork models to problem-to-system match. Dynamical adaptivecollaborations networks
.Complexity and evolution of photonic nanostructures in bio-organisms: templates for material sciences. BIOPHOT (Jean Pol Vigneron). Physical explanation for biological complexity.Use of light scattering by living organisms
MEETING INSTRUMENTS
WP6 Think TanksWP7 Schools/ CoursesWP8 Conferences
CONNECTION TO THE “OUTER WORLD”
WP1 Politicians, Media,
Business leadersWP2 Economic Policy WP3 Industry
INPUT OF YOUNG RESEARCHERS
WP4 New EU member states WP5 Female ScientistsWP11 Connecting research and PhD programs
COORDINATION AND SELF_ORGANIZATION
WP9 Coordination of Data BasesWP10 Electronic CoordinationWP12 European Complexity SocietyWP13 Experts’ Report
WP14 ManagementWP15 Assessment and Evaluation
GIACS
STARFLAGSTARFLAG: : Starlings in flight, understanding patterns of animal group movements
Termini railway station, RomeEvening roosting time, November 2004
Understanding what are the rules governing coordination and what are the microscopic mechanisms that determine flocking pattern-formation in starlings.
Starling flocks are a perfect example of collective phenomenacollective phenomena, occurring in:
Physics: ordering transitions (ferrmagnetic, liquid/gas, superconductivity etc.)
Biology: bacteria, blood cells, insects swarms, fish schools, etc. Investigate flocking behaviour in terms of vigilance, antipredatory patterns, selection of safe
landing/food rich sites Understand brain mechanisms controlling social behaviour. Compare field data with laboratory observations.
Robotics: distributed autonoumous robots, swarm intelligence
Economics: panic events, herding behaviour in financial markets etc. Improve the herding benchmark in economics exploiting insights from flock models. Understand the contribution of collective effects (herding/feedback) on prices. Provide indications for regulatory strategies.
STARFLAG ObjectivesSTARFLAG Objectives
Researchers in mathematics, physics, environmental and socio-
economic sciences
€1.5M over three years (March 2005–Feb. 2008)
Coordinating institute: Ecole Normale Supérieure, Paris, France
17 partners in 9 countries
72 scientists + 17 postdocs/postgrads
Belgium France Germany Italy Luxembourg Romania Russia UK USA
Extreme Events: Causes and Consequences (E2-C2)
Extreme events, a key manifestation of complex systems. Describe, understand & predict extreme events. Combine expertise in complex systems with broad knowledge in the natural and social
sciences.
Main study areas include: Natural disasters (earthquakes, wildfires, landslides, climatic extremes, etc.) Socio-economic crises Interaction between economic & climatic changes
Six scientific work-packages bridging the natural and social sciences.
Expected outcomes include: Validated data sets Novel insights Forecast algorithms
Techniques used: Frequency-size distributions for natural hazards probabilistic hazard forecasting Pattern recognition of precursor clustering + simple-model understanding help beat purely
probabilistic prediction. Simple models (ODEs, cellular automata, and BDEs) can help us understand and predict complex
interactions in 'real' systems.
E2-C2 Summary & Key IdeasE2-C2 Summary & Key Ideas
Prof. Yi-Cheng Zhang, The Interdisciplinary Physics Group, University of Fribourg, Switzerland
Associate researcher, ISI Foundation
Topics: Statistical Physics of Information networks
Game theory and interacting competing complex systems
Physics approach to modeling economic processes: modeling
financial systems
Cooperation with China
Cooperation with China
Professor Yu Lu, Institute of Theoretical Physics &
Interdisciplinary Center of Theoretical Studies,
Chinese Academy of Science, Beijing
Strongly correlated systems and low-dimensional condensed
matter physics
Physical and mathematical issues in superstring theory,
applications to cosmology
Interactions and modeling in living systems
Quantum information physics
Prof. Shigang He, Institute of Biophysics, Chinese Academy of Science, Beijing
Research on complex biological systems Example: the rat retina
Prof. Meiqi Fang, Economic Science Lab, Renmin University of China
Research in complexity at ECOLAB
Cooperation with China
March 2006
Main aims of the meeting: Foster a high level scientific encounter of Chinese, Indian
and European scientists and science leaders
Identify areas of common interest and designing
agreements of cooperation
Promote joint research projects in the area of complexity
and complex systems
Particular attention to inter and multi-disciplinary projects
China-India-Europe triangular meeting