Imperial College London

DrSimoneCenci

Business School

Advanced Research Fellow - Data Scientist
 
 
 
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Contact

 

s.cenci Website CV

 
 
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Location

 

Business School BuildingSouth Kensington Campus

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Summary

 

Summary

Simone Cenci is an Advanced Research Fellow at the Leonardo Centre at Imperial College Business School. His research lies at the intersection of firms' behaviour, environmental social science, and applied statistics. It primarily focuses on (1) understanding what publicly traded companies in high-emission sectors are doing to lower their environmental impact and (2) identifying the factors driving heterogeneous behavioural choices.

More information about his research can be found on his personal website.

Before joining Imperial College, Simone was a postdoctoral research associate at DCI, LLC, an independent asset management firm now acquired by Blackstone Credit. At DCI, he worked on statistical and causal inference methods to explain and predict firms' capital structure dynamics. Simone obtained his Ph.D. at the Massachusetts Institute of Technology, working on nonparametric statistical inference from nonlinear time series data to understand how populations respond and adapt to environmental changes. His PhD thesis received the Best Doctoral Thesis Award.

Selected Publications

Journal Articles

Cenci S, Burato M, Rei M, et al., 2023, The alignment of companies' sustainability behavior and emissions with global climate targets, Nature Communications, Vol:14, ISSN:2041-1723

Burato M, Tang S, Vastola V, et al., 2023, Organizational system thinking as a cognitive framework to meet climate targets, Proceedings of the National Academy of Sciences of the United States of America, Vol:120, ISSN:0027-8424

Cenci S, 2023, A large-scale analysis of the heterogeneity of markets' reactions to the disclosure of nonfinancial information, Journal of Sustainable Finance & Investment, ISSN:2043-0795, Pages:1-28

Cenci S, Kealhofer S, 2022, A causal approach to test empirical capital structure regularities, The Journal of Finance and Data Science, Vol:8, ISSN:2405-9188, Pages:214-232

Cenci S, Medeiros LP, Sugihara G, et al., 2020, Assessing the predictability of nonlinear dynamics under smooth parameter changes, Journal of the Royal Society Interface, Vol:17, ISSN:1742-5689

Cenci S, Saavedra S, 2019, Non-parametric estimation of the structural stability of non-equilibrium community dynamics, Nature Ecology and Evolution, Vol:3, ISSN:2397-334X, Pages:912-918

Cenci S, Saavedra S, 2018, Structural stability of nonlinear population dynamics, Physical Review E, Vol:97, ISSN:2470-0045

More Publications