Teaching

Academic teaching in Economics and Finance

• 1. Deep Learning for Solving Dynamic Models (May 22nd - 24th). A Ph.D. course at the Central-German Doctoral Program Economics, University of Leipzig (teaching materials here).

  2. Advanced Data Analytics, HEC Lausanne (February - May 2024).  A course on machine learning (supervised, unsupervised, and reinforcement learning) is available (syllabus here).

  3. Advanced Programming, HEC Lausanne (February - May 20224).  A course covering Python,  parallel, and high-performance computing (syllabus here).

  4. Introduction to Deep Learning & Deep Equilibrium Nets  (21.8. 2023, at the Econometric Society summer school in dynamic structural estimation)

  5. Ph.D. course on Quantitative MacroEconomic Theory "a.k.a. Computational Economics" (19.1. - 27.4. 2023 at Department of Economics, University of Pennsylvania). A course on advanced computational methods to solve and estimate dynamic stochastic economic models.

  6. Advanced Methods in Computational Economics (14.11. - 22.11.2022 at CREST/ENSAE). A course on Sparse Grids, Deep Equilibrium Nets, Deep Structural Estimation.

  7. Introduction to Deep Equilibrium Nets & Deep Structural Estimation (11. - 21.7.2022 - at the CSCS-USI HPC/Data Analytics Summer University 2022)

  8. Advanced Data Analytics, HEC Lausanne (February - May 2022).  A course on Machine learning (supervised, unsupervised, and reinforcement learning - syllabus here).

  9. Advanced Programming, HEC Lausanne (February - May 2022).  A course covering Python, C++, OpenMP, MPI, and Hybrid parallel Programming (syllabus here).

  10. Introduction to Deep Equilibrium Nets & Deep Structural Estimation (22.8.2021 - at the Econometric society on dynamic structural estimation)

  11. Deep Learning (a 2 day module at the CSCS-USI Summer school on HPC, 19.7. - 30.7.2021).

  12. Advanced Data Analytics, HEC Lausanne (February - May 2021).  A course on Machine learning (supervised, unsupervised, and reinforcement learning ).

  13. Programming, HEC Lausanne (February - May 2021).  A course covering Python, C++, OpenMP, MPI, CUDA, OpenACC, and Hybrid parallel Programming.

  14. Digitise, Optimise, Visualize (Model 4 -- a five-day crash course on applied machine learning in economics and finance, USI Lugano, 10.2. - 16.2.2021)

  15. Deep Learning (a 2 day module at the CSCS-USI Summer school on HPC, 13.7. - 24.7.2020).

  16. Advanced Data Analytics, HEC Lausanne (February - May 2020).  A course on Machine learning (supervised, unsupervised, and reinforcement learning).

  17. Programming, HEC Lausanne (February - May 2020).  A course covering Python, C++, OpenMP, MPI, CUDA, OpenACC, and Hybrid parallel Programming.

  18. Lecture Suite on “Global Solution Methods and Machine Learning in Economics and Finance”. Department Finance, MIT Sloan (October - November 2019).

  19. Lecture suite on advanced scientific computing and parallel programming, Open Source Macroeconomics Laboratory, BFI, University of Chicago (July 2018).  

  20. Advanced Data Analytics, HEC Lausanne (February - May 2019).  A course on Machine learning (supervised, unsupervised, and reinforcement learning).

  21. Programming, HEC Lausanne (February - May 2019).  A course covering Python, C++, OpenMP, MPI, CUDA, OpenACC, and Hybrid parallel Programming.

  22. A Crash-course in high-performance computing, sparse grids, and machine learning, MIT Sloan Finance (February 2019).

  23. Global Solution Methods, Cowles Foundation, Department of Economics, Yale (January/February 2019). A Lecture suite on how to apply Python, Adaptive Sparse Grids, Supervised Machine Learning, Unsupervised Machine Learning to solve large-scale dynamic stochastic models. 

  24. Introduction to Parallel & high-performance computing, Cowles Foundation, Department of Economics, Yale (September 2018). 

  25. Lecture suite on advanced scientific computing and parallel programming, Open Source Macroeconomics Laboratory, BFI, University of Chicago (July 2018).  

  26. Introduction to Parallel Programming & high-performance computing, Copenhagen Centre for Computational Economics, University of Copenhagen (June 2018).  

  27. Introduction to Adaptive Sparse Grids,  Copenhagen Centre for Computational Economics, University of Copenhagen (May 2018). 

  28. Introduction to Programming in Python for Ph.D. students, University of Zurich (February 2018).  

  29. Introduction to Programming in Python, University of Zurich (October 2017, part of the Macro-Finance for Msc. students lecture by F. Kübler).  

  30. Introduction to Parallel Programming in Economics and Finance. Open Source Macroeconomics Laboratory, Becker Friedman Institute, University of Chicago (July - August 2017, Summer School). 

  31. Introduction to adaptive sparse grids applied to economics and finance. Open Source Macroeconomics Laboratory, Becker Friedman Institute, University of Chicago (July - August 2017, Sommer School).

  32. Lecture suite on advanced scientific computing and parallel programming for graduate students in finance and economics. Swiss Finance Institute, University of Geneva (November 2016). 

  33. Introduction to Parallel Programming & high-performance computing. Institute for Computational Economics, University of Zurich (February 2017, Winter school for graduate students).

  34. Introduction to Adaptive Sparse Grids. Institute for Computational Economics, University of Zurich (February 2017, Winter school for graduate students).

  35. Introduction to Parallel Programming & high-performance computing. Institute for Computational Economics, University of Zurich (February 2016, Winter school for graduate students).

  36. Introduction to Adaptive Sparse Grids. Institute for Computational Economics, University of Zurich (February 2016, Winter school for graduate students).

  37. Introduction to Financial Economics. University of Zurich (Spring 2015. Tutorials for undergraduate students)

  38. Introduction to Adaptive Sparse Grids. Institute for Computational Economics, University of Zurich (February 2015, Winter school for graduate students).

  39. Introduction to Financial Economics. University of Zurich (Spring 2014. Tutorials for undergraduate students)

  40. Introduction to Financial Economics. University of Zurich (Spring 2013. Tutorials for undergraduate students)

Executive education

• 1. Global solution methods VII. Central Bank of Colombia, Bogota, Colombia (September/October 2017).

  2. Global solution methods VI. Central Bank of Colombia, Bogota, Colombia (March 2017).

  3. Lecture suite on high-dimensional function approximation & integration, parallel computation, machine learning. IMF, Washington D.C. (July 2016). 

  4. Global solution methods V. Central Bank of Colombia, Bogota, Colombia (May 2016).

  5. Global solution methods IV. Central Bank of Colombia, Bogota, Colombia (September 2015).