Marco Caliari

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Foto, January 12, 2015
Position
Associate Professor
Academic sector
MAT/08 - NUMERICAL ANALYSIS
Research sector (ERC)
PE1_17 - Numerical analysis

Office
Ca' Vignal 2,  Floor 2,  Room 3
Telephone
+39 045 802 7904
E-mail
marco|caliari*univr|it <== Replace | with . and * with @ to have the right email address.
Personal web page
https://profs.scienze.univr.it/caliari

Office Hours

Tuesday, Hours 2:30 PM - 4:30 PM,   Ca' Vignal 2, Floor 2, room 3
Zoom personal meeting: https://univr.zoom.us/my/marco.caliari (protected by waiting room).

Curriculum

Marco Caliari works on:

  • matrix exponential approximation by polynomials and application to exponential integrators
  • numerical solution of nonlinear Schrödinger equations for the simulation of Bose-Einstein condensates and superfluids, by splitting methods

His publications are mostly on international journals in the field of numerical analysis.

Modules

Modules running in the period selected: 66.
Click on the module to see the timetable and course details.

Course Name Total credits Online Teacher credits Modules offered by this teacher
Bachelor's degree in Applied Mathematics Numerical analysis II with laboratory (2022/2023)   6  eLearning 1 
Bachelor's degree in Applied Mathematics Numerical analysis I with laboratory (2022/2023)   6  eLearning 2 
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2022/2023)   6  eLearning 6 
Master's degree in Mathematics Numerical methods for partial differential equations (2022/2023)   6  eLearning 5 
Bachelor's degree in Applied Mathematics Numerical analysis II with laboratory (2021/2022)   6  eLearning 1 
Bachelor's degree in Applied Mathematics Numerical analysis I with laboratory (2021/2022)   6  eLearning 2 
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2021/2022)   6  eLearning 6 
Master's degree in Mathematics Numerical methods for partial differential equations (2021/2022)   6  eLearning 5 
Master's degree in Mathematics Mathematics mini courses (2020/2021)   0  eLearning  
Bachelor's degree in Applied Mathematics Numerical analysis II with laboratory (2020/2021)   6  eLearning 1  (Laboratorio)
Bachelor's degree in Applied Mathematics Numerical analysis I with laboratory (2020/2021)   6  eLearning 2  (Laboratorio)
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2020/2021)   6  eLearning 6 
Master's degree in Mathematics Numerical methods for partial differential equations (2020/2021)   6  eLearning 4 
Bachelor's degree in Applied Mathematics Numerical analysis II with laboratory (2019/2020)   6    1  (Laboratorio)
Bachelor's degree in Applied Mathematics Numerical analysis I with laboratory (2019/2020)   6  eLearning 2  (Laboratorio)
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2019/2020)   6    6 
Master's degree in Mathematics Numerical methods for partial differential equations (2019/2020)   6  eLearning 4 
Master's degree in Mathematics Advanced numerical analysis II (2018/2019)   6  eLearning 3  (Teoria)
Bachelor's degree in Applied Mathematics Numerical analysis II with laboratory (2018/2019)   6    1  (Laboratorio)
Bachelor's degree in Applied Mathematics Numerical analysis I with laboratory (2018/2019)   6    2  (Laboratorio)
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2018/2019)   6    6 
Master's degree in Mathematics Scientific computing (seminar course) (2018/2019)   6    1 
Bachelor's degree in Applied Mathematics Stochastic systems (2018/2019)   6  eLearning 1  (Esercitazioni)
Master's degree in Mathematics Advanced numerical analysis II (2017/2018)   6  eLearning 3 
Bachelor's degree in Applied Mathematics Numerical analysis II with laboratory (2017/2018)   6    1 
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2017/2018)   6    6 
Master's degree in Mathematics Scientific computing (seminar course) (2017/2018)   6    1 
Bachelor's degree in Applied Mathematics Stochastic systems (2017/2018)   6  eLearning 1 
Master's degree in Mathematics Advanced numerical analysis II (2016/2017)   6    6 
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2016/2017)   6    6 
Master's degree in Mathematics Scientific computing (seminar course) (2016/2017)   6  eLearning 1 
Bachelor's degree in Applied Mathematics Stochastic systems (2016/2017)   6    1 
Master's degree in Mathematics Advanced numerical analysis II (2015/2016)   6    6 
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2015/2016)   6    6 
Master's degree in Mathematics Research and modelling seminar (seminar course) (2015/2016)   6    1 
Bachelor's degree in Applied Mathematics Stochastic systems (2015/2016)   6    1  (esercitazioni)
Master's degree in Mathematics Advanced numerical analysis II (2014/2015)   6    6 
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2014/2015)   6    2  (Laboratorio)
4  (Teoria)
Master's degree in Mathematics Scientific computing (seminar course) (2014/2015)   6    1 
Bachelor's degree in Applied Mathematics Stochastic systems (2014/2015)   6    1  (Esercitazioni)
Master's degree in Mathematics Advanced numerical analysis (2013/2014)   12    6  (Laboratorio)
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2013/2014)   6    4  (Teoria)
2  (Esercitazioni)
Bachelor's degree in Applied Mathematics Stochastic systems (2013/2014)   6    1  (Esercitazioni)
Master's degree in Mathematics Advanced numerical analysis (2012/2013)   12    3  (Laboratorio)
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2012/2013)   6    4  (Teoria)
2  (Esercitazioni)
Master's degree in Mathematics Scientific computing (seminar course) (2012/2013)   6    1 
Bachelor's degree in Applied Mathematics Stochastic systems (2012/2013)   6    1  (Esercitazioni)
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2011/2012)   6    4  (Teoria)
2  (Esercitazioni)
Master's degree in Mathematics Scientific computing (2011/2012)   6    1 
Bachelor's degree in Applied Mathematics Stochastic systems (2011/2012)   6    1  (Esercitazioni)
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2010/2011)   6    4  (Teoria)
Master's degree in Mathematics Scientific computing (2010/2011)   6    1 
Bachelor's degree in Applied Mathematics Stochastic systems (2010/2011)   6    1  (Esercitazioni)
Master's degree in Mathematics Metodi numerici avanzati per le equazioni differenziali alle derivate parziali (2010/2011)   6    1 
Bachelor's degree in Applied Mathematics Numerical methods for differential equations (2009/2010)   6    6 
Bachelor's degree in Applied Mathematics Stochastic systems (2009/2010)   6    1  (Laboratorio)
Degree in Applied Mathematics (until a.y. 2008/2009) Numerical Analysis (2008/2009)   8    2  Laboratorio
Degree in Applied Mathematics (until a.y. 2008/2009) Numerical methods for differential equations (2008/2009)   6    2  Laboratorio
Degree in Applied Mathematics (until a.y. 2008/2009) Stochastic systems (2008/2009)   6    1  Laboratorio
Degree in Applied Mathematics (until a.y. 2008/2009) Basic Mathematics (2007/2008)   4    4 
Degree in Applied Mathematics (until a.y. 2008/2009) Numerical Analysis (2007/2008)   8    2  Laboratorio
Degree in Applied Mathematics (until a.y. 2008/2009) Numerical methods for differential equations (2007/2008)   6    2  Laboratorio

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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
Mathematics - applications and modelling
Research interests
Topic Description Research area
Approximation of matrix exponential Polynomial approximation of matrix exponential by interpolation at special nodes. Mathematics - applications and modelling
Numerical analysis
Numerical approximation We implement algorithms to calculate a numerical approximation of a complicated function, defined either directly by an explicit formula or procedure or else, for example, defined indirectly as the solution of a differential equation of some type. Mathematics - applications and modelling
Numerical analysis
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
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
Approssimazione multivariata con basi polinomiali e radiali 2/29/12
Interpolazione multivariata con polinomi, RBF e altre basi e applicazioni (PRIN 2009) 7/15/11
Meshfree exponential integrators 1/1/11
Near Optimal Points for Multivariate Interpolation 1/1/10
Metodi numerici per equazioni di Schroedinger non lineari 2/9/09
Interpolazione ed Estrapolazione: nuovi algoritmi ed applicazioni 1/1/09
Interpolazione multivariata con polinomi e con funzioni radiali di base: analisi di stabilita`, implementazioni efficienti e applicazioni (PRIN 2007) 9/22/08
Modelli stocastici in dimensione finita e infinita e limiti di scala (PRIN 2004 biennale) 11/30/04



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