Academic Library


  • W. Guo, M. Del Vecchio and G. Pogrebna (2017). Global Network Centrality of University Rankings, Royal Society Open Science, 4(10). doi: 10.1098/rsos.171172 [Link][Dryad Data]


  • A Not-So-Gentle Introduction to Machine Learning (Last revised on 08/09/2017). This is a short guide on some of the most used machine learning techniques. The guide is divided into two parts: (i) Supervised learning, where both regression and classification are tackled by introducing, inter-alia, probabilistic and non probabilistic linear regression models in the context of both the Maximum Likelihood and the Bayesian framework, K-NN, CART, and Support Vector Machines (ii) Unsupervised learning, where both clustering and dimensionally reduction are talked by introducing probabilistic (Gaussian Mixture Models) and non probabilistic (K-Means) clustering, Principal Component Analysis, and Multidimensional Scaling.

Lecture notes:

These are lecture notes for courses that I have taught.

  • The R Course (Last revised on 13/03/2017). These are the lecture notes that I have used to teach the R Course for the Warwick Morse Society in the 2016/2017 academic year. They cover the following topics in R Programming: (i) Operator Syntax; (ii) Data Structures; (iii) Subsetting; (iv) Control Structures; (v) Functions; (vi) Import Export; (vii) Graphics; (viii) Functional Programming; (ix) Functionals.

Workshops material:

These are the materials for the workshops that I have organised.

Conference Presentations:

  • Del Vecchio, M. (2017) The Michelin Curse: Expert Judgment Versus Public Opinion Presentation at the International Conference Of Undergraduate Research (ICUR). Slides available here.

Revision notes:

These are revision notes for modules taught at the Univeristy of Warwick.

  • ST301 Bayesian Statistics and Decision Theory (Last revised on 17/04/2017). This notes cover the following concepts in Bayesian Statistics and Decision Theory: (i) Decision Trees; (ii) Utility Theory; (iii) Extensive and Normal Form Analysis Of A Decision Problem; (iv) Sensitivity And Probability; (v) Bayesian Networks And Relevance.
  • EC220 Mathematical Economics 1A (Last revised on 1/06/2016). This notes cover the following topics in Game Theory: (i) Static Games of Complete Information; (ii) Dynamic Games of Complete Information; (iii)  Static Games of Incomplete Information; (iv) Dynamic Games of Incomplete Information; (v) Evolutionary Game Theory.
  • IB132 Foundations of Finance (Last revised on 31/05/2016). This notes cover the following concepts in Finance: (i) Present Value; (ii) Perpetuities and Annuities; (iii) Capital Budgeting; (iv) Bonds; (v) Uncertainty Default and Risk; (vi) Uncertainty Bonds and Equity; (vii) Risk and Reward; (viii) The Capital Asset Pricing Model (CAPM); (ix) Complications in Capital Budgeting; (x) Capital Structure in Perfect Markets; (xi) Capital Structure in Imperfect Markets; (xii) Equity Payout; (xiii) Option Contracts.