Luca Di Persio

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Foto, January 26, 2015
Position
Associate Professor
Academic sector
MATH-03/B - Probability and Mathematical Statistics
Research sector (ERC-2024)
PE1_13 - Probability

Research sector (ERC)
PE1_13 - Probability

Office
Ca' Vignal 2,  Floor 2,  Room 10.A
Telephone
+39 045 802 7968
E-mail
luca|dipersio*univr|it <== Replace | with . and * with @ to have the right email address.
Curriculum

The research activity of Luca Di Persio is mainly focused on the following topics:
  •  Stochastic Partial Differential Equations (SPDEs) both in finite and infinite dimensions 
  • Asymptotic Expansion of finite-infinite Integrals
  •  Interacting Particle Systems, Random Walk in Random Media 
  •  Mean Field Games
  •  Time series Analysis and applications to Mathematical Finance 
  • Numerical Methods for Mathematical Finance 
  • Neural networks and applications 

His articles are published by journals mainly devoted to Stochastic Analysis and its applications, particularly with respect to the modelisation of problems arising in the context of Mathematical Finance. Whitin the same ambit takes place his congressual activity, both as organizer and invited speaker to internationally recognized consesses.

His didactic activity, which extends to the organization of courses and lectures within the Stochastic Analysis and applications framework, is mainly devoted to the Theory of Probability and time series analysis. In particular, Luca Di Persio is in charge for the didactic path in Mathematical Finance (Master degree in Mathematics) and he teaches, or  he has taugtht, the following courses: Probability, Stochastic Systems, Stochastic Differential Euqations, Mathematical Finance.

Luca Di Persio is also
  • member of the PhD School in Mathematics, jointly organised by the Mathematics Department of the University of Trento and by the College of Mathematics of the Computer Science Department of the University of Verona
  • coordinator for the European mobility program Erasmus+, activated with the universities of Bielefeld, Munich, Oslo and Wuppertal.

Modules

Modules running in the period selected: 43.
Click on the module to see the timetable and course details.

Course Name Total credits Online Teacher credits Modules offered by this teacher
Master's degree in Mathematics Mathematical finance (2024/2025)   6  eLearning 6 
Master's degree in Data Science Statistical models for Data Science (2024/2025)   6  eLearning 3 
Master's degree in Mathematics Stochastic Calculus (2024/2025)   6  eLearning 6 
Master's degree in Mathematics Mathematical finance (2023/2024)   6  eLearning 6 
Master's degree in Data Science Statistical models for Data Science (2023/2024)   6  eLearning 3 
Master's degree in Mathematics Stochastic Calculus (2023/2024)   6  eLearning 6 
Master's degree in Mathematics Mathematical finance (2022/2023)   6  eLearning 6 
Master's degree in Data Science Statistical models for Data Science (2022/2023)   6  eLearning 3 
Master's degree in Mathematics Stochastic Calculus (2022/2023)   6  eLearning 6 
Master's degree in Mathematics Mathematical finance (2021/2022)   6  eLearning 6 
Master's degree in Data Science Statistical models for Data Science (2021/2022)   6  eLearning 3 
Master's degree in Mathematics Stochastic Calculus (2021/2022)   6  eLearning 6 
Master's degree in Mathematics Advanced topics in financial engineering (2020/2021)   6  eLearning 1 
Master's degree in Mathematics Mathematical finance (2020/2021)   6  eLearning 6 
Master's degree in Data Science Probability for Data Science (2020/2021)   12  eLearning 1  (Teoria)
Master's degree in Mathematics Stochastic Calculus (2020/2021)   6  eLearning 6 
Bachelor's degree in Applied Mathematics Stochastic systems (2020/2021)   6  eLearning 1 
Master's degree in Mathematics Advanced topics in financial engineering (2019/2020)   6  eLearning 1 
Master's degree in Mathematics Mathematical finance (2019/2020)   6  eLearning 6 
Master's degree in Mathematics Stochastic Calculus (2019/2020)   6  eLearning 6 
Bachelor's degree in Applied Mathematics Stochastic systems (2019/2020)   6  eLearning 1 
Master's degree in Mathematics Mathematical finance (2018/2019)   6  eLearning 4  (Parte 2)
2  (Parte 1)
Master's degree in Mathematics Stochastic differential equations (2018/2019)   6  eLearning 6 
Bachelor's degree in Applied Mathematics Stochastic systems (2018/2019)   6  eLearning 5  (Teoria)
Master's degree in Mathematics Mathematical finance (2017/2018)   6  eLearning 2 
Master's degree in Mathematics Stochastic differential equations (2017/2018)   6  eLearning 6 
Bachelor's degree in Applied Mathematics Stochastic systems (2017/2018)   6  eLearning 5 
Master's degree in Mathematics Mathematical finance (2016/2017)   6  eLearning 2 
Bachelor's degree in Applied Mathematics Stochastic systems (2016/2017)   6    5 
Master's degree in Mathematics Mathematical finance (2015/2016)   6    2  (Teoria 1)
Bachelor's degree in Applied Mathematics Stochastic systems (2015/2016)   6    3  (Catene di Markov in tempo discreto)
2  (Analisi di serie temporali)
Master's degree in Mathematics Mathematical finance (2014/2015)   6    1  (Teoria 1)
1  (Esercitazioni)
Bachelor's degree in Applied Mathematics Probability (2014/2015)   6    5  (Teoria)
Master's degree in Mathematics Mathematical finance (2013/2014)   6    1  (Teoria 1)
1  (Esercitazioni)
Bachelor's degree in Applied Mathematics Probability (2013/2014)   6    5  (Teoria)
Bachelor's degree in Applied Mathematics Probability (2012/2013)   6    1  (Esercitazioni)
5  (Teoria)
Bachelor's degree in Applied Mathematics Probability (2011/2012)   6    6 
Bachelor's degree in Computer Science Probability and Statistics (2011/2012)   6    4  (Teoria)

Di seguito sono elencati gli eventi e gli insegnamenti di Terza Missione collegati al docente:

  • Eventi di Terza Missione: eventi di Public Engagement e Formazione Continua.
  • Insegnamenti di Terza Missione: insegnamenti che fanno parte di Corsi di Studio come Corsi di formazione continua, Corsi di perfezionamento e aggiornamento professionale, Corsi di perfezionamento, Master e Scuole di specializzazione.

Research groups

INdAM - Research Unit at the University of Verona
We collect here the scientific activities of the Research Unit of Istituto Nazionale di Alta Matematica INdAM at the University of Verona
Research interests
Topic Description Research area
Intelligent agents Design and development of autonomous entities that can sense, model and interact with the environment in which they operate. These area focuses on the interaction and integration of solution technques for several research topics such as automated planning and reasoning, reinforcement learning, statistical learning and reasoning in face of uncertainty. Artificial Intelligence
Distributed artificial intelligence
Stochastic analysis Stochastic analysis, theory of stochastic partial differential equations in finite/infinite dimension, randomly interacting particle systems,with applications to Mathematical Finance. Mathematical methods and models
Stochastic analysis
Stochastic data-driven forecasting Stochastic Data-Driven Forecasting focuses on integrating stochastic analysis with data-driven methods to enhance predictive accuracy in systems governed by random processes. By utilizing stochastic models, such as stochastic differential equations and time series with noise components, and calibrating them through machine learning on observed data, this field aims to yield robust probabilistic forecasts. Applications include dynamic systems in finance, climatology, and energy, where accurate uncertainty quantification is essential for predictive reliability and risk evaluation. Information Systems and Data Analytics
Stochastic Differential Equations
Multi agent systems Design and development of multiagent systems, where intelligent agents can interact among them, with the environment and with humans. This area focuses on the interaction and integration of solution techniques related to multiagent planning, statistical learning, multi-agent reinforcement learning and game theory. Artificial Intelligence
Distributed artificial intelligence
Projects
Title Starting date
Study of the integration of stochastic analysis tools with Machine Learning models in the training and operation of Large Language Models (LLM). 2/7/24
Green Inspired Revolution for Optimal-Workforce Management - GIRO-WM 11/1/23
Development of Artificial Intelligence methods to support insurance policy sales. 11/21/22
Stochastic Modelling of Financial Markets aiming to develop new concepts for Goal-Based Investment Solutions during Decumulation Phase 5/1/21
Study and development of machine learning techniques for data prediction. 10/22/19
Metodi di controllo ottimo stocastico per l'analisi di problemi di debt-management 3/15/17
Energy markets management by stochastic methods 1/16/17
Advanced numerical methods for financial forecasting 1/12/17
Stochastic Approaches for Forecasting and Hedging in Energy Markets 12/1/16
Stochastic Partial Differential Equations and Stochastic Optimal Control with Applications to Mathematical Finance 3/21/16
Metodi di set-valued analysis e di teoria del trasporto ottimo per la modellizzazione di mercati finanziari con costi di transazione in ambito deterministico e stocastico. 3/12/15



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