Imperial College London

ProfessorKimChristensen

Faculty of Natural SciencesDepartment of Physics

Professor of Theoretical Physics
 
 
 
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Contact

 

+44 (0)20 7594 7574k.christensen Website

 
 
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Assistant

 

Mrs Carolyn Dale +44 (0)20 7594 7579

 
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Location

 

812Blackett LaboratorySouth Kensington Campus

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Summary

 

Summary

Research interest

Theoretical and numerical aspects of complex systems, addressing the spontaneous emergence of patters and organisation in non-equilibrium systems composed of many interacting entities. My research has often been a integration of theoretical, computational and experimental studies of complex systems involving a rigorous mathematical approach to pioneer new ways of analysing such systems quantitatively. I have been working within the area of complexity science for about 30 years, developing and applying transferable tools and techniques to real world systems in many different contexts: geology (earthquake & reservoir engineering), atmospheric physics (rain), biology (evolution & social insects), sociology (organisational science), medicine (brain & heart) and fire safety (smouldering). In 2005, I co-authored together with Dr. Nicholas Moloney a pedagogical textbook entitled “Complexity and Criticality” that is used for teaching purposes world-wide in teaching. With more than 7400 citations (Google Scholar, November 2022), I have a proven track record of being able to identify generic key-research questions and of promoting knowledge transfer.

Keywords: Complexity & Networks Science. Interdisciplinary research.

Higher education

03.1993: Ph.D. degree in Science, Institute of Physics and Astronomy, University of Århus, Denmark.

05.1990: Master in Science, Institute of Physics and Astronomy, University of Århus, Denmark.

Publications

Journals

Shi X, Sau A, Li X, et al., 2023, Information theory-based direct causality measure to assess cardiac fibrillation dynamics, Journal of the Royal Society Interface, Vol:20, ISSN:1742-5662

Bolko AE, Christensen K, Pakkanen MS, et al., 2023, A GMM approach to estimate the roughness of stochastic volatility, Journal of Econometrics, Vol:235, ISSN:0304-4076, Pages:745-778

Yao Q, Ma S, Liang J, et al., 2023, Syndication network associates with specialisation and performance of venture capital firms, Journal of Physics-complexity, Vol:4

Falkenberg McGillivray M, Coleman JA, Dobson S, et al., 2022, Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps, Plos One, Vol:17, ISSN:1932-6203, Pages:1-24

Yao Q, Evans T, Chen B, et al., 2021, Higher-order temporal network effects through triplet evolution, Scientific Reports, Vol:11, ISSN:2045-2322, Pages:1-17

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