dr. ir. Q. (Qingyi) Feng
External Cooperation Coordinator
Operational management - Onderzoek- en Valorisatiebeleid
Gegenereerd op 2018-08-21 02:20:12


Coordinator and researcher at the Centre for Complex Systems Studies (CCSS), Utrecht University, The Netherlands

Research Interest: Complexity theories and their applications in real-world systems, such as ecosystems, economics, health care, climate systems, etc.

Short Bio:                                  

I’m a passionate-for-life-and-dedicated-to-work complexity scientist with backgrounds in Climate Dynamics (PhD degree), Complex Systems Science (Double Master degree), and Environmental Science (Master degree). I have lived in 6 countries (CN, UK, FR, NL, DE and IL) and visited many other places through studies and traveling. My inter-disciplinary and multi-cultural experience shaped me into a proactive team-player, who is fast in learning and adapting, and efficient in communication and coordination.

Strategic themes / Focus areas
C, Python, Fortran, Matlab, NetLogo, Academic Writing, Writing Grant Proposals, Organising Workshops

Visualization of a climate network. Figure from [Tominski et al., 2011]

The temporal changes of the depression pattern of a depressed individual. Figure from [Feng et al., 2012]
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Curriculum vitae


07/2012-06/2015     PhD in Climate Dynamics, Universiteit Utrecht, NL

09/2011-06/2012     MSc in Cognition and Complex Systems, École Polytechnique, FR

10/2010-08/2011     MSc in Complex Systems Science, University of Warwick, UK

09/2008-06/2010     MEng in Environmental Science, Tianjin University, CN

09/2004-06/2008     BSc in Environmental Science, Tianjin University, CN


Academic Experience:

09/2017-present   Centre for Complex Systems Studies (CCSS), Utrecht University, Postdoctoral Researcher

Investigating the connections between microscopic and macroscopic scales to improve the understanding of emergence in complex systems; applying complexity theories to other fields (i.e., privacy law) through collaborative efforts.

07/2015-08/2017   Complexity Lab Utrecht (CLUe), Utrecht University, Postdoctoral Researcher

Improved the skills of climate predictions by investigating new features of complex networks; supervised master students on measuring climate resilience and vulnerability.

07/2012-06/2015   Institute for Marine and Atmospheric Research (IMAU), Utrecht University, PhD Researcher (Funded by Marie-Curie Initial Training Network)

04/2014-05/2014    Secondment in Bar-Ilan University, Israel

03/2013-04/2013    Secondment in Potsdam Institute for Climate Impact Research, Germany

PhD thesis title    “A Complex Network Approach to Understand Climate Variability”

Developed new mechanistic indicators based on complex network analysis, which are crucially important in the interpretation and evaluation of climate models and observations.

03/2011-12/2012   Diamond Cohort Study, University of Warwick (Collaborated with The University of Melbourne), Junior Researcher

Introduced a new way to identify depression patterns based on statistical mechanics and machine learning, which may lead to tailored medical interventions for depression.

01/2012-06/2012   U943 INSERM, Université Pierre et Marie Curie (Collaborated with École Polytechnique), Junior Researcher

Proposed a more comprehensive measure based on nonlinear dynamics to capture the full picture of HIV epidemic.

02/2007-10/2010   National Basic Research Program & National Natural Science Foundation, Tianjin University, Student Researcher

Proposed several new models for complex systems based on nonlinear dynamics and statistical mechanics, which have been applied in ecosystems, biology, and economics.


Non-Academic Positions:                                                   

09/2017-present   Centre for Complex Systems Studies (CCSS), Coordinator

Proactively supporting various activities within the CCSS, seeking financing opportunities, potential collaborations and relevant networks which are involved in the development of complex systems studies.

09/2017-04/2018   Netherlands Platform Complex Systems (NPCS), Coordinator

Played an active role in strengthening the complex systems community within The Netherlands by supporting NPCS activities and advising the board on the relevant developments in research, business, government, and society.

07/2015-09/2017   Complexity Laboratorium Utrecht (CLUe), Coordinator

Involved in the proposal writing and the setup phase of the CLUe, organized regular meetings, training and workshops, designed and maintained the website and the server to facilitate the usage of concepts and techniques from complexity science.

03/2008-06/2010   Tianjin University Environmental Complex Systems Society (ECSS), Founder & Chairman

Founded the ECSS and provided an interdisciplinary platform to exchange research ideas by organizing symposiums, initiating and maintaining online discussions, etc.



Techniques:      Familiar with various complexity theories; have research experience in statistical mechanics, nonlinear dynamics, agent-based modeling, machine learning, and network theory; experienced with website builders Drupal and WordPress.

Programming:  C, Python, Fortran, Matlab, and NetLogo.

Languages:       English (full professional proficiency), Chinese (native proficiency), Dutch (limited working proficiency), and French (elementary proficiency).


Awards and Scholarships:                                              

10/2010       Erasmus Mundus International Scholarship (Worldwide, 10/120)

10/2009       “Outstanding Students” (The Highest Honor in Tianjin University, 5/27000)

06/2008       “Excellent Thesis” of Tianjin University

12/2007       "Talents Science Award" (Alias “Nobel Prize” in Tianjin University, 10/27000)

04/2007       Winner of “Challenge Cup” Tianjin University Student Extracurricular Academic Science & Technology Work Competition

Gegenereerd op 2018-08-21 02:20:13
  • Complexity Methodology (2007-2009)

Feng Q Y and Chai L H. The Function Law of Nature: The Research Progress of Maximum Flux Principle (In Chinese). Science & Technology Review, 2007, 25(24): 73-80.

Feng Q Y and Chai L H. Maximum Flux Principle: A New Method of Multivariate Statistical Analysis and Its Applications (In Chinese). Journal of Tianjin University of Technology, 2009, 25(1): 15-19.


  • Ecosystems & Complexity (2008-2010)

Feng Q Y and Chai L H. A New Statistical Dynamic Analysis on Vegetation Patterns in Land Ecosystems. Physica A: Statistical Mechanics and its Applications, 2008, 387(14): 3583-3593. http://dx.doi.org/10.1016/j.physa.2008.01.118

Feng Q Y and Chai L H. Ecosystem Evolution Dynamics Based on Generalized Entropy Principle (In Chinese). Science & Technology Review, 2009, 27(4): 36-41.


  • Biology & Complexity (2008-2010)

Feng Q Y and Chai L H. Riddle of Growth: A Principle for Growth Basing on Non Equilibrium Statistical Mechanics (In Chinese). Science & Technology Review, 2008, 26(4): 80-86.

Wang Y J, Feng Q Y, and Chai L H. A New Model on Origin and Evolution of Biology (In English & Chinese). Agricultural Science & Technology, 2009,10(4):4-7.

Wang Y J, Feng Q Y, Wang H, and Chai L H. New Simulation Method of Ecosystem Evolution Based on Neural Network. In: 6th International Conference on Natural Computation (ICNC’10) Vol.4, Yantai, China: 2010.1749-1753.


  • Economics & Complexity (2009-2010)

Wang Y J, Feng Q Y, and Chai L H. Evolution of Stock Markets Driven by Generalized Entropy Principles (In Chinese). Journal of Tianjin University of Technology, 2009, 25(5): 8-11.

Wang Y J, Feng Q Y, and Chai L H. Structural Evolutions of Stock Markets Controlled by Generalized Entropy Principles of Complex Systems. International Journal of Modern Physics B, 2010, 30(24): 5949-5971.

Wang Y J, Feng Q Y, Chen S J, and Chai L H. Simulation of Transportation-Economic Complex System Based on SOM Network. In: 6th International Conference on Natural Computation (ICNC’10) Vol.4, Yantai, China: 2010.1842-1846.


  • Health Care & Complexity (2012)

Feng Q Y, Griffiths F, Parsons N, and Gunn J. An Exploratory Statistical Approach to Depression Pattern Identification. Physica A: Statistical Mechanics and its Applications, 2012, 392(4): 889–901. http://dx.doi.org/10.1016/j.physa.2012.10.025.


  • Climate Dynamics & Complexity (2013-2018)

Van der Mheen M, Dijkstra H A, Gozolchiani A, Den Toom M, Feng Q, Kurths J, and Hernández-García E. Interaction network based early warning indicators for the Atlantic MOC collapse. Geophysical Research Letters, 2013, 40(11): 2714–2719. https://doi.org/10.1002/grl.50515.

Feng Q Y and Dijkstra H A. Are North Atlantic Multidecadal SST Anomalies Westward Propagating? Geophysical Research Letters, 2014, 41(2): 541–546. https://doi.org/10.1002/2013GL058687.

Feng Q Y, Viebahn J P, and Dijkstra H A. Deep Ocean Early Warning Signals of an Atlantic MOC Collapse. Geophysical Research Letters, 2014, 41(16): 6009–6015. https://doi.org/10.1002/2014GL061019.

Feng Q Y and Dijkstra H A. Climate network stability measures of El Niño variability. Chaos: An Interdisciplinary Journal of Nonlinear Science, 2017, 27(3): 035801. http://dx.doi.org/10.1063/1.4971784.

van Zalinge B C, Feng Q Y, Aengenheyster M, and Dijkstra H A. On determining the Point of no Return in Climate Change. Earth System Dynamics, 2017, 8: 707-717. https://doi.org/10.5194/esd-8-707-2017.

Feng Q Y and Dijkstra H A. What Have Complex Network Approaches Learned Us About El Niño? In: Tsonis A (eds). Advances in Nonlinear Geosciences, 2018, Springer, Cham. https://doi.org/10.1007/978-3-319-58895-7_7.

Nooteboom P D, Feng Q Y, López C, Hernández-García E, and Dijkstra H A. Using Network Theory and Machine Learning to predict El NiñoEarth System Dynamics, 2018, 9: 969-983. https://doi.org/10.5194/esd-9-969-2018.

Aengenheyster M, Feng Q Y, van der Ploeg F, and Dijkstra H A. Risk and the Point of No Return for Climate Action. Earth System Dynamics, 2018. https://doi.org/10.5194/esd-2018-17 (accepted).


  • Complexity Tools (2015-2016)

Donges J F, Heitzig J, Beronov B, Wiedermann M, Runge J, Feng Q Y, Tupikina L, Stolbova V, Donner R V, Marwan N, Dijkstra H A, and Kurths J. Unified Functional Network and Nonlinear Time Series Analysis for Complex Systems Science: The pyunicorn Package. Chaos: An Interdisciplinary Journal of Nonlinear Science,  2015, 25(113101): http://dx.doi.org/10.1063/1.4934554.

Feng Q Y, Vasile R, Segond M, Gozolchiani A, Wang Y, Abel M, Havlin S, Bunde A, and Dijkstra H A. ClimateLearn: A machine-learning approach for climate prediction using network measures. Geoscientific Model Development, 2016: https://doi.org/10.5194/gmd-2015-273.


  • Law & Complexity (2018)

Rhoen M and Feng Q Y. Why the “Computer says no”: illustrating big data's discrimination risk through complex systems science. International Data Privacy Law, 2018, 8(2): 140–159. https://doi.org/10.1093/idpl/ipy005. Short report on this article is available via https://www.uu.nl/en/news/can-the-gdpr-prevent-that-the-computer-says-no

All publications
  2018 - Scholarly publications
Nooteboom, P.D., Feng, Q., López, Cristóbal, Hernández-García, Emilio & Dijkstra, H.A. (23.07.2018). Using network theory and machine learning to predict El Niño. Earth System Dynamics, 9 (3), (pp. 969-983) (15 p.).


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Full name
dr. ir. Q. Feng Contact details

Leuvenlaan 4
Room 412
The Netherlands

Phone number (direct) +31 30 253 1019
Mo Tue Wed Thu Fr

On Wednesdays I work as a researcher. All coordination related issues will be answered on other working days.

Gegenereerd op 2018-08-21 02:20:13
Last updated 13.08.2018