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.

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

• Data analytics with SAS base, ZHAW
• An Introduction to ML with SAS Viya, ZHAW
• Machine Learning 1, ZHAW
• 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

• Applied Data Analysis, ZHAW
• Modeling Extremes and Catastrophes, ZHAW
• Statistics and Probability for Quants (+Brain Teasers), New York University
• Extreme Value Theory, New York University
• 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, Postdoc and Professionals

• Applied Forecasting, MOFC University of Nicosia
• 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 private 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 24 bachelor students and 75 master students in mathematics, statistics and risk management.


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 is a quant at Optiver.
• 2017-2021: Dr. Shuaiqiang Liu, dealing with machine learning for graphical financial time series. Second supervisor. He is now a postdoc researcher at CWI Amsterdam.
• 2015-2022: Dr. Dan Cheng, working on urn models for credit risk, in particular from a Bayesian perspective. She is now on the job market.
• 2019-2023: Mr. Luis Souto, working on XVA modeling via urn models and Lorenz theory. Expected defense: Spring 2023.