Previous Fora / 2011

KASKI, Kimmo

Aalto University School of Science, Finland

Vice Dean of School of Science & Professor of Computational Science & Director of the Centre of Excellence in Computational Complex Systems Research (COSY), Dept.  of  Biomedical  Engineering  and  Computational  Science  (BECS),  Aalto University  (AALTO  former  Helsinki  University  of  Technology  (HUT))  & Supernumerary Fellow of Wolfson College, Oxford University.
Academic Degrees and Qualifications:

1973:  MSc,  in  Electron  Physics,  Helsinki  University  of  Technology  (HUT);  1977:  Licentiate  in Technology,  in  Electron  Physics,  HUT;  1981:  Doctor  of  Philosophy  (D.Phil.),  in  Theoretical Physics, Oxford University; 1984: Adjunct Professor in Physics, Department of Physics, Jyväskylä University;  1985-86:  Associate  Professor  in  Microelectronics,  Temple  University,  Philadelphia (tenured);  1987-96:  Professor  in  Microelectronics,  Tampere  University  of  Technology  (tenured); 1996:  Professor  in  Computational  Science,  AALTO,  (tenured,  current  position);  1996-2001  & 2001-2006: Academy Professor in Computational Science, Academy of Finland, (two 5 year terms).

Awards and Honours:

  • •  British Council Fellowship for Oxford University, UK, 1978-81
  • •  Fellow of the American Physical Society, USA, 1994
  • •  Academy Professor, Academy of Finland, (two five year terms) 1996-2001 and 2001-06
  • •  Fellow of Finnish Academy of Technical Sciences, 1997
  • •  Fellow of the Institute of Physics, UK and granted the title of Chartered Physicist, 1998
  • •  Laboratory of Computational Engineering chosen as Centre of Excellence by the Academy of Finland, Director for 2000-05 and 2006-11
  • •  Member of Academia Europeae, Section of Physics and Engineering Sciences, 2001
  • •  Supernumerary Fellow, Wolfson College, University of Oxford, 2001
  • •  Member of Finnish Academy of Sciences and Letters, 2002

Degrees Supervised:

PhD: 62 (of which 3 in USA, 3 in UK and 56 in Finland); Licentiate: 23, MSc: 126.

Publication Profile and Presentations:

Refereed journals: > 250, with > 3400 citations (116 (2004), 156 (‘05), 142 (‘06), 270 (’07), 273 (’08), 384 (’09), 410 (’10), 300 (9/’11), and h-index = 31 (Web of Science); Articles in books: > 30; Conference proceedings: > 120; Reports:  > 100. Plenary and invited talks: > 70.a



11:00-13:00 18 NOVEMBER
THEMATIC SESSION II. Hungarian Academy of Sciences:“Networks”

Social Complexity: Can it be analysed and modelled?

Over the past decade or so Network Theory has turned out to be a powerful methodology to investigate complex systems of various sorts. Through data analysis, modelling, and simulation quite an unparalleled insight into their structure, function, and response can be obtained. In human societies individuals are linked through social interactions, which today are increasingly mediated electronically by modern Information Communication Technology thus leaving "footprints" of human behaviour as digital records. For these datasets the network theory approach is a natural one as we have demonstrated by analysing the dataset of multi-million user mobile phone communication-logs. This social network turned out to be modular in structure showing communities where individuals are connected with stronger ties and between communities with weaker ties. Also the network topology and the weighted links for pairs of individuals turned out to be related. These empirical findings inspired us to take the next step in network theory, by developing a simple network model based on basic network sociology mechanisms to get friends in order to catch some salient features of meso-scale community and macro-scale topology formation. Our model turned out to produce many empirically observed features of large-scale social networks. Thus we believe that the network theory approach combining data analysis with modeling and simulation could open a new perspective for studying and even predicting various collective social phenomena such as information spreading, formation of societal structures, and evolutionary processes in them.