Letizia Pellegrini

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Foto, May 29, 2018
Position
Full Professor
Academic sector
SECS-S/06 - MATHEMATICAL METHODS OF ECONOMICS, FINANCE AND ACTUARIAL SCIENCES
Research sector (ERC)
PE1_19 - Control theory and optimisation

Office
Polo Santa Marta,  Floor 1,  Room 1.29
Telephone
045 802 8345
E-mail
letizia|pellegrini*univr|it <== Replace | with . and * with @ to have the right email address.

Office Hours

Wednesday, Hours 3:00 PM - 5:00 PM,   Polo Santa Marta, Floor 1, room 1.29
Due to the current public health situation, office hours in presence are temporarily canceled. Office hours will be held on zoom platform, via e-mail arrangement.

Curriculum

Letizia Pellegrini is Full Professor of Mathematics for Economic Decisions at the University of Verona since 2006. Previously, she was Assistant Professor at the University of Pisa, where she graduated in Mathematics and specialized in Computer Science. The main area of research is optimization theory, in particular non-differentiable optimization, vector-optimization and set-valued optimization.

 

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
Bachelors' degree in Business Administration and Management Mathematics (2022/2023)   9  eLearning 9 
Ph.D. in Economics and Finance Mathematics (2022/2023)   7.5  eLearning 5 
Master’s degree in Economics and Data Analysis Quantitative methods for business and economics (2022/2023)   12  eLearning 4  MATHEMATICAL AND COMPUTATIONAL METHODS FOR BUSINESS AND ECONOMICS
Bachelors' degree in Business Administration and Management Mathematics (2021/2022)   9  eLearning 9 
Ph.D. in Economics and Finance Mathematics (2021/2022)   7.5  eLearning 5 
Master’s degree in Economics and Data Analysis Quantitative methods for business and economics (2021/2022)   12  eLearning 4  MATHEMATICAL AND COMPUTATIONAL METHODS FOR BUSINESS AND ECONOMICS
Bachelors' degree in Business Administration and Management Mathematics (2020/2021)   9  eLearning 9 
PhD in Economics and Management Mathematics (2020/2021)   7.5  eLearning 4.5 
Master’s degree in Economics and Data Analysis Quantitative methods for business and economics (2020/2021)   12  eLearning 3  MATHEMATICAL AND COMPUTATIONAL METHODS FOR BUSINESS AND ECONOMICS
Master’s degree in Economics Mathematical models for business and economics (2019/2020)   6  eLearning 4 
Bachelor's degree in Business Administration (Verona) Mathematics (2019/2020)   9  eLearning 9 
PhD in Economics and Management Mathematics (2019/2020)   7.5    1 
Master’s degree in Economics Mathematical models for business and economics (2018/2019)   6  eLearning 4 
Bachelor's degree in Business Administration (Verona) Mathematics (2018/2019)   9  eLearning 9 
PhD in Economics and Management INTRODUCTION TO MASS AND ENERGY BALANCES (2017/2018)   10    1 
Master’s degree in Economics Mathematical models for business and economics (2017/2018)   6  eLearning 6 
Bachelor's degree in Business Administration (Verona) Mathematics (2017/2018)   9  eLearning 9 
Master’s degree in Economics Mathematical models for business and economics (2016/2017)   6  eLearning 6 
Bachelor's degree in Business Administration (Verona) Mathematics (2016/2017)   9  eLearning 3  (esercitazione)
6  (lezione)
Master’s degree in Economics Mathematical models for business and economics (2015/2016)   6    6 
Bachelor's degree in Business Administration (Verona) Mathematics (2015/2016)   9    3  (esercitazione)
6  (lezione)
Master’s degree in Economics Mathematical models for business and economics (2014/2015)   6    4  (lezione 1)
Bachelor's degree in Business Administration (Verona) Mathematics (2014/2015)   9    3  (esercitazione)
6  (lezione)
Master’s degree in Economics Mathematical models for business and economics (2013/2014)   6    4 
Bachelor's degree in Business Administration (Verona) Mathematics (2013/2014)   9    3  (esercitazione)
6  (lezione)
Master’s degree in Economics Mathematical models for business and economics (2012/2013)   6    4 
Bachelor's degree in Business Administration (Verona) Mathematics (2012/2013)   9    3  (esercitazione)
6  (lezione)
Bachelor's degree in Business Administration (Verona) Subject requirements: memory, logical and mathematical skills (2012/2013)   0     
Bachelor's degree in Business Administration (Verona) Mathematics (2011/2012)   9    6  (lezione)
3  (esercitazione)
Bachelor's degree in Business Administration (Verona) Subject requirements: memory, logical and mathematical skills (2011/2012)   0     
Bachelor's degree in Business Administration (Verona) Mathematics (2010/2011)   9    6  (lezione)
2  (esercitazione)
Bachelor's degree in Applied Mathematics Operations Research (2010/2011)   6    6 
Bachelor's degree in Business Administration (Verona) Saperi minimi - Abilità mnemoniche e logico-matematiche (2010/2011)   0     
Bachelor's degree in Business Administration (Verona) Mathematics [Cognomi A-O] (2009/2010)   9    3  (2 - esercitazione)
6  (1 - lezione)
Bachelor's degree in Business Administration (category 17) (until 2008-2009) Mathematics [Cognomi A-K] (2008/2009)   10    7  1 - lezione
3  2 - esercitazione [A-D]
Degree in Applied Mathematics (until a.y. 2008/2009) Optimization (2008/2009)   6    6 
Bachelor's degree in Business Administration (category 17) (until 2008-2009) Mathematics [Cognomi A-K] (2007/2008)   10    7  Lezione
3  Esercitazione [A-D]
Degree in Applied Mathematics (until a.y. 2008/2009) Optimization (2007/2008)   6    6 
Degree in Applied Mathematics (until a.y. 2008/2009) Basic Mathematics (2006/2007)   4    4 
Bachelor's degree in Business Administration (category 17) (until 2008-2009) Mathematics [Cognomi A-K] (2006/2007)   10    3  esercitazione [A-D]
7  lezione
Bachelor's degree in Business Administration (category 17) (until 2008-2009) Mathematics [Cognomi A-K] (2005/2006)   10    3  ESERCITAZIONE [A-D]
7  LEZIONE
Bachelor in Economics and Management of the Service Industry (cat 17) Company Management Mathematics (2004/2005)   4    2  LEZIONE 1
Bachelor's degree in Business Administration (category 17) (until 2008-2009) Mathematics [Cognomi A-K] (2004/2005)   10    7  lezione
Bachelor's degree in Political Economics (cat. 28) Mathematics for the Economy (2004/2005)   4    4 
Bachelor in Economics and Management of the Service Industry (cat 17) Company Management Mathematics (2003/2004)   4     
Bachelor's degree in Company Economics (cat. 17) Mathematics [Cognomi A-K] (2003/2004)   6     
Bachelor's degree in Political Economics (cat. 28) Mathematics for the Economy (2003/2004)   4     
Bachelor in Economics and Management of the Service Industry (cat 17) Company Management Mathematics (2002/2003)   4     
Bachelor's degree in Company Economics (cat. 17) Mathematics [Cognomi A-K] (2002/2003)   6     
Bachelor's degree in Political Economics (cat. 28) Mathematics for the Economy (2002/2003)   4     
Specialized Degree in Quantitative Methods for Finance ( Cat. 91/S) Mathematics for the Economy and Finance (2002/2003)   4    4 
Bachelor in Economics and Management of the Service Industry (cat 17) Company Management Mathematics (2001/2002)   4     
Bachelor in Market Economics and Brokerage (cat. 17) Mathematics [Cognomi A-K] (2001/2002)   6     
Bachelor's degree in Political Economics (cat. 28) Mathematics for the Economy (2001/2002)   4     

Advanced teaching activities
Name Online
Activities PhD Course In Economics and Management (35° ciclo - PhD in Economics and Management)
Mathematics (28° Ciclo - GSEM - PhD in Economics and Business Administration (last activated in 2013))

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Research interests
Topic Description Research area
JEL C61 - Optimization Techniques; Programming Models; Dynamic Analysis Covers theory and methods for optimization problems. Linear programming and mathematical programming. Vector optimization and duality models. Economic applications to the problems of optimal investment choices under conditions of uncertainty and portfolio optimization. Estimation of the parameters of financial models including a risk-neutral assumption and calibration of the models. Stochastic optimization for finding estimators of the volatility of a semimartingale with jumps. Quantitative Methods for Economics
Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
MSC 49J40 - Variational methods including variational inequalities Scalar and Vector Variational Inequalities applied to network equilibrium problems (transportation networks, computer networks, telecommunication networks). Vector formulation of the Wardrop equilibrium principle for traffic networks and relationships with Vector Variational Inequalities of Stampacchia and Minty. Quantitative Methods for Economics
Existence theories
MSC 49N15 - Duality theory Lagrangian duality for scalar and vector optimization problems. Duality gap for nonconvex problems. Sensitivity analysis and economic interpretation of the dual variables (shadow prices) for the linear vector case. Quantitative Methods for Economics
Miscellaneous topics
MSC 90C25 - Convex programming Generalizd convexity: convexlike, subconvexlike functions and image convexity. Linear and conic separation in the image space for G-semidifferentiable problems. Quantitative Methods for Economics
Mathematical programming
MSC 90C29 - Multi-objective and goal programming Image Space Analysis for Vector Optimization and Variational Inequalities. Scalarization methods. Vector saddle points. Set-valued optimization via Image Space Analysis. Quantitative Methods for Economics
Mathematical programming
MSC 90C46 - Optimality conditions, duality Optimality conditions for constrained and unconstrained extremum problems: sufficient and necessary conditions in the case of differentiable and non-differentiable functions. Image Space Analysis: sufficient and necessary optimality conditions for not convex and / or non-differentiable problems. Regularity conditions and constraint qualifications for scalar and vector optimization problems. Quantitative Methods for Economics
Mathematical programming
Projects
Title Starting date
Assegno: Convessità generalizzata in ottimizzazione vettoriale e nelle applicazioni economiche 4/1/12
Assegno: Dualità Langrangiana in Ottimizzazione Vettoriale. Applicazioni economiche 10/1/08
Ottimizzazione e Disequazioni Variazionali Vettoriali. Applicazioni a problemi di equilibrio. 10/1/05
Dualità Lagrangiana in Ottimizzazione Vettoriale. Applicazioni economiche 10/1/04
Sistemi informatici per la finanza 1/1/01
Ottimizzazione vettoriale mediante l'approccio dello spazio immagine. Metodi di scalarizzazione 1/1/01
Economia delle decisioni in sistemi complessi (2001) 1/1/01