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The Department has a long-standing tradition of excellence in research in applied mathematics, probability and statistics. Its recent expansion to the areas of theoretical physics, machine learning and computer science has further strengthened the Department’s value in the area of data science and developed the intellectual breadth and diversity of the community of scholars it gathers. The research activities may be broadly traced back to the following, closely related, subject areas:

Applied Mathematics and Probability
Research in these disciplines focuses on the study of models relevant in diverse scientific fields, by means of advanced analytical and probabilistic techniques, and has led to highly innovative contributions in: applied probability, information theory, optimization, statistical physics, stochastic process theory and theoretical statistics. 

Statistics and Data Science
The research activity in this area investigates the core methodologies and principles for statistical learning from the data with emphasis on prediction and uncertainty quantification. It also addresses new challenging applied problems. Cutting-edge contributions have been given in: Bayesian inference, Bayesian nonparametric methods, computational statistics, statistical machine learning, networks analysis and neuroscience.

Computer Science
Research is focused on the development and analysis of algorithms in view of their implementation in several applied settings. Innovative contributions have been given in: artificial intelligence, computational biology, deep learning, machine learning, neural networks and scientific computing.

Decision Theory and Game Theory
Research in these areas is devoted to the development of the mathematical and theoretical foundations of models in economics. This has led to important contributions to: consumer theory, dynamical systems, game theory, mathematical economics, network analysis and optimization.

Operations Research
The area is focused on developing mathematical models for decision making and risk assessment. Relevant contributions have been provided to: agent-based simulation, decision and risk analysis and sensitivity analysis.

Some of these themes are investigated by the Department in collaboration with the Bocconi Institute of Data Science and Analytics and with the Innocenzo Gasparini Institute of Economic Research.

Last modified 16/10/2017 - 16:42:41
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