Arnoldo Frigessi with the support of.

Presentasjon om: "Arnoldo Frigessi with the support of."— Utskrift av presentasjonen:

1 Arnoldo Frigessi with the support of

2 Many systems are very hard to understand
Science, industry and business possess the technology to  collect, store and distribute huge amounts of data

3 Fantastically precious data, yet complex and incomplete,
are ready to be used for scientific discovery, product development, optimised service.

4 Statistics provides the methods for
producing useful data, understanding data and learning about the world from data. Because knowledge is fragmented and data are incomplete, discoveries and decisions are uncertain. Statistics is the science to quantify risk and make decisions under uncertainty

5 Statistics is necessary brick in today's …
telecommunication transport and logistics insurance business pharmaco industry public health fishery management petroleum production and all the rest!

6 Statistics

7 Statistics is a service science.
Statistical methods We shall produce the next generation of statistical methodology for innovation

8 Statistics for tomorrow, statistics for innovation.
Statistics for today’s industry, science and service 2015 NOW TIME LINE

9 Mission: (sfi)2 develops core statistical methodologies,
strategically necessary to achieve innovation goals in four key sectors: petroleum marine resources health finance and insurance Vilje til Forskning Tjenestesektor

10 Common challenges to statistical science
Smerud Medical Research Finance Insurance Petroleum Health Marine Common challenges to statistical science

11 Challenges much data from different sources, but often few critical ones more complex data, because we measure more in depth systems to be understood or predicted are complex the easy part is done, necessary to discover “second order effects” evidence-based decision making is more and more required in society

12 we shall built strong, interdisciplinary teams, …
International network of collaborations Based on our competence, experience, traditions … we shall built strong, interdisciplinary teams, … working on ambitious research projects, … producing top results, … fundamentally needed to solve strategic innovation needs.

13 First! Best! What projects at (sfi)2 ?
Ambitious, very ambitious, innovation aims, where we have an advantage with respect to competitors, because of partner’s top know-how, market position, unique data or ideas; where we have a scientific advantage because of our unique competence in statistics where we can put together internationally leading interdisciplinary research teams. FindOil TotalRisk StatInsure Insurance Industry StatMarine Biomolecular Genome Browser MetaAnalysis CompareSeq MaleContracept Multicompare Survival Swing ComplexModels BiosearchTools Infectious diseases Statistical genomics First! Best!

14 FindOil: New method to compute the probability that an off-shore perforation will be successful. Update the probabilities of success of all other possible future drilling locations. (StatoilHydro, NR, UiO, NTNU)

15 StatMarine: Improve the management of marine resources, by better surveillance, based on new statistical models that describe the sea under environmental pressure, climatic change and commercial exploitation. (Havforskningsinstituttet, NR, UiO)

16 MetaAnalysis: Reduce the time to production of new drugs, combining published clinical studies and open data with own precious data material at individual patient level. (Smerud, NR, UiO, Rikshospitalet)

17 Industry and Academia Partnership and Pathways
Climate Change and Insurance Industry: What effect has climate change on the insurance industry? Methods to help the insurance companies to be less vulnerable to climate change. (Gjensidige, NR, UiO, LSE, Lloyd’s) Industry and Academia Partnership and Pathways

18 Highly interdisciplinary Strong synergies Top statistics!
1997 2007 2030 2050 time Predicted insurance losses Insurance losses Insurance industry Statistics Weather data Metereol. Climate model Climate researchers Climate model * Summarize data and motivate for claims models and predictions Highly interdisciplinary Strong synergies Top statistics!

19 Ingrid Hobæk Haff, Ola Lindqvist, Linda R
Ingrid Hobæk Haff, Ola Lindqvist, Linda R. Neef, Xeni Dimakos, Mathilde Wilhelmsen, Ola Haug, Kjersti Aas, Jofrid Frøland Vårdal, Lars Holden, Egil Ferkingstad, Magne Aldrin, David Hirst, Hanne Rognebakke, Bjørnar Mortensen, Marit Holden, Petter Abrahamsen, Ragnar Hauge, Heidi Kjønsberg, Odd Kolbjørnsen, Ingunn Fride Tvete, Bård Storvik, Marita Stien, Geir Storvik, Nils Lid Hjort, Steffen Grønneberg, Ingrid Glad, Ørnulf Borgan, Ståle Nygård, Ole Christian Lingjærde, Hege Bøvelstad, Inge Helland, Arne B. Huseby, Ida Scheel, Gunnhildur H. Steinbak, Nils Haavardsson, Hayat Mohammed, Egil Ferkingstad, Nina Gunnes, Trond Moger, Brigitte F. De Blasio, Bettina Kulle, Glenn Lawyer, Knut Liestøl, Arnoldo Frigessi, Marion Haugen, Odd Aalen Petter Laake, Morten Fagerland, Magne Thoresen, Marit Veierød, Tore Schweder. Alessandro Ottavi, Sara Martino, Henning Omre, Jo Eidsvik, Håkon Tjelmeland, Mette Langaas, Håvard Rue, Torbjørn Stølan, Arild Buland, Knut Birger Hjelle, Erling Siring, Isabel Saraiva, John Reidar Granli, Herve Babusiaux, Laurent Viguier, Frode Masdal Svendsen, Kristine Dybwad, Elisabeth Nyeggen, Elisabeth Meze, Tone Eilertsen, Monica Svendson, Lars Kvifte, Tove Krohn Sjursen, Gunnar Kvam, Marte Valde, Anders Øksendal, Roar Hoff, Idar Øsebak, Kari Reikvam, Nina Schjølberg, Sondre Aanes, Kjell Nedreeas, Michael Pennington, Asgeir Aglen, Åge Fotland, Eirik Næss-Ulseth, Fang Liu, Håvard Hauge, Torbjørn Rognes, Håvard Hauge, Bjørn Steen Skålhegg, Ken R. Rosendal, Tuva Holt Hereng, Gisle Grave, Nils Meland, Inge Christoffer Olsen, Knut Smedrud, Eivind Hovig, Eivind Tøstesen, Morten Johansen, Morten Mattingsdal, Geir Kjetil Sandve, Birgit Eliassen, Jon Myrseth, Ophélie Aussedat. People

20 Funding and Infrastructure

21 A new culture for statistical science An intense training programme.
Focus on innovation. New alliances, between academia and industry For the first time in the world, a centre like this.

22 (sfi)2 is a resource for the growth and competitiveness
of the Norwegian economy. (sfi)2 mirrors the fundamental priorities for research as in Vilje til Forskning. Plus tjenestesektor! (sfi)2 will impact the way exact sciences are perceived in the society. Important for recruitment and labour market. Please, tell others about us! sfi’s are an exciting adventure, interesting and rewarding to join, a new way to think and do science.