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: 33.
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 (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

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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
Partial differential equations, initial value and time-dependent initial-boundary value problems Solution of non-linear Schrödinger, mean-field and Boltzmann-type equations by pseudo-spectral or meshless methods in space and splitting methods in time. Mathematics methods and models
Numerical analysis
Ordinary differential equations and applications Development of Implicit-Explicit schemes and asymptotic preserving schemes for time dependent problem. Applications in hyperbolic balance laws with diffusive limit and optimal control problems. Mathematics 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




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