Final papers/theses represent the last step of your experience in a Bachelor of Science/Master of Science program. You are required to demonstrate your personal and intellectual growth and your ability to apply the concepts you have studied during your degree program at Bocconi.
Final papers, and theses in particular, require effort and dedication: you will need to commit a suitable amount of time and serious planning.
Each final paper/thesis should begin with a preliminary analysis of possible research topics, which should be innovative, interesting and feasible.
This page aims to be a starting point for students interested in choosing a topic referring to the areas of interest for faculty members in the Department of Decision Sciences:
- Mathematical analysis
- Mathematical methods of economy, finance and actuarial sciences
- Probability and mathematical statistics
- Machine learning and data science
Below you can find a list of more specific sectors within the areas mentioned above. By selecting a specific sector, you will get a list of the faculty members you may contact as potential Tutors for the Final Paper or as Advisors for the MSc Thesis.
Please remember that both Final Papers and MSc Theses may be written in English or in Italian, according to the indications of each degree program. Students should read the general instructions for writing a final paper and a thesis.
Regarding administrative procedures, all information is available online in the Guide to the University (Chapter 10 in particular):
For more information, please contact Prof. Rebecca Graziani (rebecca.graziani@unibocconi.it).
You can check the following guides designed by the Library to create your research strategy and find relevant resources and tools: Decision Sciences, Bibliographic Research Skills, Writing your dissertation
B
Topics: Decision Analysis, Mathematical Finance and Financial Calculus, Operation Research
Topics: Decision Analysis, Machine Learning, Operation Research, Sensitivity Analysis
Topics: Behavioral Economics, Business Analytics, Decision Analysis, Decision Theory, Game Theory, Management Sciences, Mathematical Finance and Financial Calculus, Operation Research, Optimization, Sensitivity Analysis
Topics: Calculus of Variations and Optimal Control, Convex Analysis and Optimization, Dynamical Systems and Gradient Flows, Measure Theory, Optimization Transport, Partial Differential Equations (PDE), Real and Functional Analysis
C
Topics: Decision Theory, Dynamical Systems and Gradient Flows, Mathematical Finance and Financial Calculus
D
Topics: Calculus of Variations and Optimal Control, Convex Analysis and Optimization, Dynamical Systems and Gradient Flows, Measure Theory, Optimization Transport, Partial Differential Equations (PDE), Real and Functional Analysis
Topics: Dynamical Systems and Gradient Flows, Mathematical Finance and Financial Calculus, Optimization
Topics: Applied Bayesian Nonparametrics, Computational Statistics, Data Science, High-Dimensional Statistics, Machine Learning, Network Science, Parametric and Nonparametric Inference, Statistical Modeling of Complex Data, Stochastic Processes
F
Topics: Asymptotic Theory, Bayesian Nonparametric Theory, Parametric and Nonparametric Inference, Probability Theory, Stochastic Processes
G
Topics: Business Analytics, Computational Statistics, Data Science, Machine Learning, Mathematical Finance and Financial Calculus, Parametric and Nonparametric Inference, Probability Theory, Stochastic Processes
L
Topics: Calculus of Variations and Optimal Control, Convex Analysis and Optimization, Measure Theory, Numerical Analysis, Optimization Transport, Partial Differential Equations (PDE), Real and Functional Analysis
Topics: Applied Bayesian Nonparametrics, Bayesian Nonparametric Theory, Machine Learning, Parametric and Nonparametric Inference, Probability Theory, Statistical Modeling of Complex Data, Stochastic ODE and PDE
M
Topics: Bayesian Nonparametric Theory, Parametric and Nonparametric Inference
Topics: Business Analytics, Data Science, Econometrics and Causal Inference, Machine Learning, Management Science, Management Sciences
O
Topics: Dynamical Systems and Gradient Flows, Mathematical Finance and Financial Calculus, Optimization, Real and Functional Analysis
P
Topics: Applied Bayesian Nonparametrics, Asymptotic Theory, Bayesian Nonparametric Theory, Biostatistics, Computational Statistics, Data Science, Econometrics and Causal Inference, Extreme Value Theory, High-Dimensional Statistics, Inverse Problems, Machine Learning, Measure Theory, Network Science, Parametric and Nonparametric Inference, Probability Theory, Statistical Modeling of Complex Data, Stochastic ODE and PDE, Stochastic Processes
Topics: Computational Statistics, Data Science, Econometrics and Causal Inference, High-Dimensional Statistics, Machine Learning, Network Science, Statistical Modeling of Complex Data
Topics: Business Analytics, Data Science, High-Dimensional Statistics, Machine Learning
Topics: Calculus of Variations and Optimal Control, Convex Analysis and Optimization, Measure Theory, Optimization Transport, Partial Differential Equations (PDE), Probability Theory, Real and Functional Analysis
Topics: Behavioral Economics, Business Analytics, Econometrics and Causal Inference, Statistical Modeling of Complex Data
Topics: Applied Bayesian Nonparametrics, Bayesian Nonparametric Theory, Machine Learning, Parametric and Nonparametric Inference, Probability Theory, Statistical Modeling of Complex Data, Stochastic Processes
R
Topics: Business Analytics, Computational Statistics, Data Science, Econometrics and Causal Inference, Machine Learning, Operation Research, Parametric and Nonparametric Inference
S
Topics: Calculus of Variations and Optimal Control, Convex Analysis and Optimization, Dynamical Systems and Gradient Flows, Optimization Transport, Partial Differential Equations (PDE)
Topics: Asymptotic Theory, Bayesian Nonparametric Theory, High-Dimensional Statistics, Inverse Problems, Machine Learning, Parametric and Nonparametric Inference, Probability Theory, Stochastic ODE and PDE, Stochastic Processes
T
Topics: Biostatistics, Data Science, Machine Learning, Statistical Modeling of Complex Data
Topics: Data Science, High-Dimensional Statistics, Machine Learning