Giacomo Albi

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Foto_2, October 19, 2017
Position
Associate Professor
Academic sector
MAT/08 - 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

 


Lunedí dalle 14:30 alle 16:30.
Altrimenti su appuntamento: giacomo.albi@univr.it

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

 

Curriculum

Giacomo Albi ha completato la sua formazione accademica in Italia,  conseguendo la laurea triennale in Matematica nel 2007 a Trento,  la laurea magistrale in Matematica a Padova nel 2010, e il dottorato in Matematica e Informatica a Ferrara nel 2014 con una tesi sull'approssimazione cinetica, simulazione e controllo di sistemi autorganizzanti. Dal 2014 al 2017 ha lavorato come research fellow presso la TU München all'interno del progetto di ricerca ERC 'High-Dimensional Sparse Optimal Control'. Dal 2017 è Ricercatore a Tempo Determinato presso il Dipartimento di Informatica di Verona.

I suoi principali interessi di ricerca sono:

  • Metodi numerici per la risoluzione di equazioni cinetiche,  equazioni di  tipo Boltzmann, e  sistemi iperbolici.
  • Controllo ottimo di sistemi ad alta-dimensionalità e sistemi differenziali non-lineari.
  • Modellistica matematica e numerica per sistemi multi-agente, con applicazioni alle dinamiche socio-economiche e biologiche.

Le sue pubblicazioni si collocano prevalentemente sulle riviste internazionali nell'area dell'analisi numerica e della matematica applicata. 

Modules

Modules running in the period selected: 26.
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 (2023/2024)   6    6 
Bachelor's degree in Applied Mathematics Mathematical and Statistical Methods in Biology (2023/2024)   6    3 
Master's degree in Mathematics Numerical methods for partial differential equations (2023/2024)   6    2 
Master's degree in Mathematics Numerical modelling and optimization (2023/2024)   6    3  NUMERICAL OPTIMIZATION
Master's degree in Mathematics Foundation of data analysis (2022/2023)   6  eLearning 6 
Bachelor's degree in Applied Mathematics Mathematical and Statistical Methods in Biology (2022/2023)   6  eLearning 3 
Master's degree in Mathematics Numerical methods for partial differential equations (2022/2023)   6  eLearning 1 
Master's degree in Mathematics Numerical modelling and optimization (2022/2023)   6  eLearning 2  MODELLING SEMINAR
3  NUMERICAL OPTIMIZATION
Master's degree in Mathematics Foundation of data analysis (2021/2022)   6  eLearning 6 
Bachelor's degree in Applied Mathematics Mathematical and Statistical Methods in Biology (2021/2022)   6  eLearning 3 
Master's degree in Mathematics Numerical methods for partial differential equations (2021/2022)   6  eLearning 1 
Master's degree in Mathematics Numerical modelling and optimization (2021/2022)   6  eLearning 3  NUMERICAL OPTIMIZATION
Master's degree in Mathematics Foundation of data analysis (2020/2021)   6  eLearning 6 
Bachelor's degree in Applied Mathematics Mathematical and Statistical Methods in Biology (2020/2021)   6  eLearning 3 
Master's degree in Mathematics Numerical modelling and optimization (2020/2021)   6  eLearning 3  NUMERICAL OPTIMIZATION
Master's degree in Mathematics Foundation of data analysis (2019/2020)   6  eLearning 6 
Bachelor's degree in Applied Mathematics Mathematical and Statistical Methods in Biology (2019/2020)   6  eLearning 3 
Master's degree in Mathematics Numerical modelling and optimization (2019/2020)   6  eLearning 3  NUMERICAL OPTIMIZATION
Master's degree in Mathematics Advanced numerical analysis II (2018/2019)   6  eLearning 3  (Esercitazioni)
Bachelor's degree in Applied Mathematics Mathematical and Statistical Methods in Biology (2018/2019)   6  eLearning 3  (Parte 1)
Master's degree in Mathematics Research and modelling seminar (seminar course) (2018/2019)   6  eLearning 1 
Master's degree in Mathematics Advanced numerical analysis II (2017/2018)   6  eLearning 3 
Bachelor's degree in Applied Mathematics Numerical analysis I with laboratory (2017/2018)   6  eLearning 2 
Master's degree in Mathematics Research and modelling seminar (seminar course) (2017/2018)   6  eLearning 1 
Bachelor's degree in Applied Mathematics Numerical analysis I with laboratory (2016/2017)   6  eLearning 6 

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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 - applications and modelling
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 - applications and modelling
Numerical analysis
Projects
Title Starting date
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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