Giacomo Albi

Foto_2,  October 19, 2017
Position
Associate Professor
Role
Associate Professor
Academic sector
MATH-05/A - Numerical Analysis
Research sector (ERC-2024)
PE1_18 - Numerical analysis

Research sector (ERC)
PE1_17 - Numerical analysis

Office
Ca' Vignal 2,  Floor 2,  Room 6
Telephone
+39 045 802 7913
E-mail
giacomo|albi*univr|it <== Replace | with . and * with @ to have the right email address.

Office Hours

Monday from 14:30 to 16:30. Or by appointment: giacomo.albi@univr.it

Curriculum

Giacomo Albi completed his academic training in Italy, earning his bachelor's degree in Mathematics in 2007 in Trento, his master's degree in Mathematics in Padua in 2010, and his PhD in Mathematics and Computer Science in Ferrara in 2014 with a thesis on kinetic approximation, simulation and control of self-organising systems. From 2014 to 2017 he worked as a research fellow at TU München within the ERC research project 'High-Dimensional Sparse Optimal Control'. Since November 2022 he has been Associate Professor in Numerical Analysis at the Department of Computer Science in Verona.

His main research interests are:

    Numerical methods for solving kinetic equations, Boltzmann-type equations, and hyperbolic systems.
    Optimal control of high-dimensional systems and non-linear differential systems.
    Mathematical and numerical modelling for multi-agent systems, with applications to socio-economic and biological dynamics.

His publications are mainly in international journals in the area of numerical analysis and applied mathematics.

Modules

Modules running in the period selected: 37.
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 Foundation of data analysis (2025/2026)   6   
Master’s degree in Supply Chain Management Logistic optimization (2025/2026)   9   
Bachelor's degree in Applied Mathematics Numerical analysis I with laboratory (2025/2026)   6   
Master's degree in Mathematics Numerical modelling and optimization (2025/2026)   6    NUMERICAL OPTIMIZATION
Master's degree in Mathematics Foundation of data analysis (2024/2025)   6  eLearning
Master’s degree in Supply Chain Management Logistic optimization (2024/2025)   9  eLearning
Bachelor's degree in Applied Mathematics Mathematical and Statistical Methods in Biology (2024/2025)   6  eLearning
Master's degree in Mathematics Mathematics mini courses (2024/2025)   0  eLearning  
Bachelor's degree in Applied Mathematics Numerical analysis I with laboratory (2024/2025)   6  eLearning
Master's degree in Mathematics Foundation of data analysis (2023/2024)   6  eLearning
Bachelor's degree in Applied Mathematics Mathematical and Statistical Methods in Biology (2023/2024)   6  eLearning
Master's degree in Mathematics Mathematics mini courses (2023/2024)   0  eLearning  
Bachelor's degree in Applied Mathematics Numerical analysis I with laboratory (2023/2024)   6  eLearning
Master's degree in Mathematics Numerical methods for partial differential equations (2023/2024)   6  eLearning
Master's degree in Mathematics Numerical modelling and optimization (2023/2024)   6  eLearning NUMERICAL OPTIMIZATION
Master's degree in Mathematics Foundation of data analysis (2022/2023)   6  eLearning
Bachelor's degree in Applied Mathematics Mathematical and Statistical Methods in Biology (2022/2023)   6  eLearning
Master's degree in Mathematics Numerical methods for partial differential equations (2022/2023)   6  eLearning
Master's degree in Mathematics Numerical modelling and optimization (2022/2023)   6  eLearning MODELLING SEMINAR
NUMERICAL OPTIMIZATION
Master's degree in Mathematics Foundation of data analysis (2021/2022)   6  eLearning
Bachelor's degree in Applied Mathematics Mathematical and Statistical Methods in Biology (2021/2022)   6  eLearning
Master's degree in Mathematics Numerical methods for partial differential equations (2021/2022)   6  eLearning
Master's degree in Mathematics Numerical modelling and optimization (2021/2022)   6  eLearning NUMERICAL OPTIMIZATION
Master's degree in Mathematics Foundation of data analysis (2020/2021)   6  eLearning
Bachelor's degree in Applied Mathematics Mathematical and Statistical Methods in Biology (2020/2021)   6  eLearning
Master's degree in Mathematics Numerical modelling and optimization (2020/2021)   6  eLearning NUMERICAL OPTIMIZATION
Master's degree in Mathematics Foundation of data analysis (2019/2020)   6  eLearning
Bachelor's degree in Applied Mathematics Mathematical and Statistical Methods in Biology (2019/2020)   6  eLearning
Master's degree in Mathematics Numerical modelling and optimization (2019/2020)   6  eLearning NUMERICAL OPTIMIZATION
Master's degree in Mathematics Advanced numerical analysis II (2018/2019)   6  eLearning (Esercitazioni)
Bachelor's degree in Applied Mathematics Mathematical and Statistical Methods in Biology (2018/2019)   6  eLearning (Parte 1)
Master's degree in Mathematics Research and modelling seminar (seminar course) (2018/2019)   6  eLearning
Master's degree in Mathematics Advanced numerical analysis II (2017/2018)   6  eLearning
Bachelor's degree in Applied Mathematics Numerical analysis I with laboratory (2017/2018)   6  eLearning
Master's degree in Mathematics Research and modelling seminar (seminar course) (2017/2018)   6  eLearning
Bachelor's degree in Applied Mathematics Numerical analysis I with laboratory (2016/2017)   6  eLearning

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

Contemporary Applied Mathematics
Development of advanced theoretical and computational mathematical methods for transport and diffusion phenomena in complex systems, multivariate approximation and high-dimensional control problems.
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
Numerical methods and models for multi-scale systems of interacting particles Analysis and implementation of mathematical methods and models for dynamics of systems of interacting particles on various scales and their control: data-driven control for high-dimensional systems with non-local interaction; particle methods for problems of global optimization and applications to machine learning; dynamics of opinions on social networks; multi-scale models for crowd dynamics, and optimal strategies for evacuation problems; socio-epidemiological models and strategies to mitigate the spread of infection; control problems for high energy particles for the confinement in plasmas, and for targeted radiotherapy in treatment of tumors. Mathematical methods and models
Numerical analysis
Numerical solution of partial differential equations Analysis and implementation of innovative and effective numerical methods for solving and controlling partial differential equations (PDEs) of parabolic type (diffusion-transport-reaction), hyperbolic type (e.g. Euler equations for gas dynamics and Einstein field equations for astrophysics), highly oscillatory (Schrödinger equations), and integro-differential equations (kinetic equations with term collision and mean-field equations with non-local interaction terms). Mathematical methods and models
Numerical analysis
Projects
Title Starting date
Data-driven discovery and control of multi-scale interacting artificial agent systems. 11/30/23
Efficient numerical schemes for control problems in nonlinear PDEs and computational social dynamics 9/28/23
Geometric Evolution of Multi Agent Systems 11/1/20
PRIN 2017 - Innovative numerical methods for evolutionary partial differential equations and applications 1/1/19
Numerical methods for multiscale control problems and applications 2/5/18




Organization

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