Emanuele Guidotti

Emanuele Guidotti

Postdoctoral Researcher

USI Lugano


I am postdoctoral researcher with the Institute of Finance at USI Lugano. Among other things, I am the developer of COVID-19 Data Hub, have authored a classification algorithm inspired by Born’s rule, and maintain several R and Python packages including a package for high dimensional numerical and symbolic calculus in R. For my contributions, I have received grants and awards from IVADO, the R Consortium, and Google Cloud.

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Recent Publications

(2022). calculus: High Dimensional Numerical and Symbolic Calculus in R. Journal of Statistical Software, vol. 104(5), pag. 1–37.

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(2022). A worldwide epidemiological database for COVID-19 at fine-grained spatial resolution. Scientific Data, vol. 9(1), pag. 1-7. Nature Publishing Group.

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(2020). COVID-19 Data Hub. Journal of Open Source Software, vol. 5(51), pag. 2376.

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Recent & Upcoming Talks

Institute for Mathematical Statistics - Asia-Pacific Rim Meeting (IMS-APRM)
Seminar at EPFL, Swiss Finance Institute
Seminar at Linköping University, Machine Learning Series (IDA)

Grants & Awards

Awarded to enable performance tests on GPU for the paper Text Classification with Born’s Rule
Awarded to support the maintainance of COVID-19 Data Hub
Awarded to support the development of COVID-19 Data Hub