The Logic of Risk
 <i>Homines dum</i><i> docent discunt</i>
 <i>Homines dum</i><i> docent discunt</i>
  • © 2020 Pasquale Cirillo 0

Homines dum docent discunt

About my teaching

Over the years, I have taught several mathematical and financial courses, at all university levels and also for professionals, including online education, a field in which I consider myself a pioneer.

I like teaching and interacting with students. From their feedback I often get inspiring ideas for my research and work.

I believe that a good university researcher also needs to be a good teacher, who must be capable to express complex concepts and ideas in a clear and direct way. A good academic researcher should indeed not only be able to discover new results and communicate them to the scientific community, but also to make them available to a broader audience.

Teaching is a fantastic opportunity to foster students’ curiosity and interests, to make them get the maximum out of their studies, and to discover who may be interested in continuing his/her career in research.

In teaching, I like to combine new technologies, such as videos, podcasts, interactive talks and computer simulations, with more traditional pedagogical tools (front lectures, case studies, and the old reliable blackboard).

As a student I never liked detached professors, who seemed not to care about me and my understanding of the course topics. For these reasons, I always try to be a supportive teacher and I am always ready to help students in facing their difficulties. I only ask my students to be proactive: you only learn if you are willing to. If you do not understand something, just ask!

Qualifications and awards

  • 2012: Habilitation (venia docendi) in Applied Statistics from the University of Bern.
  • 2015: I got a special praise from the Board of Directors of TU Delft, for my online teaching.
  • 2015: I received my EWI-KO university teaching qualification in mathematics.
  • 2018: I was nominated TU Delft Education Fellow, as recognition of my teaching activities, obtaining a grant of €50'000 to further develop my projects in education.

And now, the word to the students. How would you improve the course?

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Teaching Portfolio

Here below a list of courses I have developed and taught since 2010.

For my online teaching, have a look here.

Bachelor level

  • Modeling and Simulation, Applied Mathematics, TU Delft
  • Risk Management, Minor Finance, TU Delft
  • Probability for Finance, Applied Mathematics, TU Delft
  • Probability and Statistics, Electrical Engineering, TU Delft
  • Calculus 1, Aerospace Engineering, TU Delft
  • Linear Algebra 1, Aerospace Engineering, TU Delft

Master level

  • Quantitative Risk Management, Applied Mathematics, TU Delft
  • Financial Mathematics (stochastic calculus), Applied Mathematics, TU Delft
  • Risk Management, Finance and Risk Engineering, New York University
  • Credit Risk Modeling, Applied Mathematics, TU Delft
  • Time Series and EVT, Applied Mathematics, TU Delft
  • Statistical Methods for Climate Sciences, Climate Sciences, University of Bern
  • An Introduction to Urn Models, Statistics, University of Bern

PhD and Postdoc

  • Reading Group on Lévy processes, Mathematics, TU Delft
  • Validation of AB Models, Statistics, Wehia Summer School
  • Advanced Credit Risk Modeling, Mathematics, Romanian Institute of Advanced Mathematics

Professional courses

I have also created more than a dozen of courses for companies and professionals, answering their needs for training in machine learning, data analysis and risk management. Interested? Contact me.

Supervision of students

Bachelor and Master level

So far, I have supervised 11 bachelor students and 32 master students in mathematics, statistics and risk management. Most of their works can be found on TU Delft Repository.

PhD students

  • 2015-2019: Dr. Andrea Fontanari, who worked on new risk measures beyond VaR, using tools from inequality theory and statistical physics. He is now a postdoc researcher at CWI Amsterdam.
  • 2015-2020: Ms. Dan Cheng, working on urn models for credit risk, in particular from a Bayesian perspective. Scheduled defense: Summer 2020.
  • 2017-2021: Mr. Shuaiqiang Liu, dealing with machine learning for graphical financial time series. Expected defense: Winter 2020 (co-supervisor).
  • 2019-2023: Mr. Luis Souto, working on XVA modeling via urn models and Lorenz theory. Expected defense: Spring 2023.

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