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LO IUSS DIDATTICA RICERCA OPPORTUNITÀ

Programma

Approfondimenti

N.B. IL MASTER NON SARA' ATTIVATO NELL'A.A. 2011 - 2012

Contatti Segreteria del Master:
master.mcs@iusspavia.it

Profilo partecipanti

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SEMINARI 2008
Prof. Kruse - 16/04
Prof. Kucera - 25/01

WORKSHOP 2007: 
Workshop-11/10/07
Workshop-05/10/07
Workshop-04/10/07
Workshop-24/9/07
Workshop-10/5/07

Eventi delle scorse edizioni (pdf)

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Stampa:
(21-03-2008) Il Corriere della Sera

Pubblicazioni:

- Essays on the economics and management of innovation
- Aspetti teorici generali: la complessità
- Complessità: una nuova frontiera

Collaborazioni

Durata: 12 mesi, full-time (dal lunedì al venerdì).
Frequenza: obbligatoria (minimo 85%).
Materiale didattico e lezioni: lingua inglese.
 

Il Master si divide in due fasi:
 

     
  • Fase I - DIDATTICA: ha una durata di circa 6 mesi, è svolta a Pavia e comprende approssimativamente 400 ore di lezioni frontali e seminari;
     
  • Fase II - STAGE: comprende una parte applicativa interdisciplinare all’interno di un’azienda o di un centro di ricerca. Il periodo non può essere inferiore a 3 mesi e superiore a 6 mesi.
     
     

Al termine del periodo svolto in azienda i partecipanti dovranno redigere un "Project Report" che sarà valutato dal Comitato Scientifico.

Al completamento del programma, i candidati riceveranno l'attestato di conseguimento del Master Universitario di II livello in "Metodi per la Gestione di Sistemi Complessi".

_______________________________________
 

 


I - DIDATTICA
(Gennaio-Luglio 2008) 

Fondamenti

  1. Physical and Mathematical Modeling (50 h)
  2. Software Tools and Programming (50 h) 
  3. Probability and Statistics (50 h) 
  4. Business, Management and Finance I (50 h)

 

Metodi

 

  1. Classical Computational Methods (40 h)
  2. Soft Computing and other advanced computational techniques (40 h)
  3. Business Management and Finance II (40 h)
  4. Dynamics of Complex Systems (40 h)
  5. Computational and Statistical Data Mining Methods (40 h)

 

Applicazioni interdisciplinari (decimo corso)

 

Si tratta di lezioni focalizzate su applicazioni interdisciplinari di quanto appreso nei precedenti 9 corsi; i temi trattati spaziano dalla finanza quantitativa ai nuovi trend dell’ICT, dalla gestione dei rapporti coi clienti alle nano-tecnologie e al genomic mining.

 

Il programma di tali lezioni è aggiornato di anno in anno, in linea con le  tendenze ed i problemi del mercato  del momento. Professionisti provenienti dalle aziende partner coinvolgono gli alunni proponendo loro lo sviluppo di progetti, case studies, e trasmettendo le proprie esperienze acquisite sul campo.

CALENDARIO A.A. 2007-2008 (pdf)

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II - STAGE (Luglio-Dicembre 2008)

 


AREE DI SPECIALIZZAZIONE:
 

  • Area Finanziaria (Gestione del Rischio Finanziario; Analisi dei Dati e statistica)
  • Area Industriale (Applicazioni Industriali; Tecnologie dell'Informazione e della Comunicazione)


AZIENDE / ENTI DI RICERCA
per l'a.a. 2007-2008

  • Enel S.p.A. (Roma)
     
  • STMicroelectronics (Agrate - MI)
     
  • FMR Consulting (Voghera - PV)
  • Numonyx (Agrate - MI)
  • Data Mining Lab (Università di Pavia)
  • Laboratorio di informatica medica (Università di Pavia)
  • Laboratorio di identificazione e controllo dei sistemi dinamici (Università di Pavia)


SCORSE EDIZIONI, STAGE:

 

 


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DETTAGLIO CORSI (in inglese)

1-Physical and Matematical Modelling

Referee: Giuseppe De Nicolao (Dip. di Ingegneria, Univ. di Pavia)
 

PROGRAM
Dynamical systems; physical systems modelling; stability; properties of linear systems; transfer function; frequency response; simulation; discrete-time systems; feedback control of linear time-invariant systems; feedback control design: synthesis by loop shaping in the frequency domain.
 

BASIC REQUIREMENTS
Basics of integral calculus.
 

OBJECTIVES
Deriving dynamic models from physical laws, stability analysis of open-loop and closed-loop linear systems, design of feedback controllers.

DURATION: 50 hours
TERM: January 2008
EXAM: 4 February 2008
CREDITS: 6 ECTS

USEFUL READINGS:
1. T. Kailath, Linear Systems, Prentice Hall, 1980.
2. H. K. Khalil, Nonlinear systems, Prentice Hall, 1996.
3. K. Ogata, Modern control engineering, 4. ed. Prentice-Hall, 2001.
4. G. F. Franklin, J. D. Powell and A. E. Naeini, Feedback Control of Dynamic systems, Third Edition, 1994.
5. P. Bolzern, R. Scattolini and N. Schiavoni, Fondamenti di controlli automatici, McGraw-Hill, 1998 (in Italian).

FACULTY:
1. De Nicolao Giuseppe (University of Pavia)
2. Kucera Vladimir (Czech Technical University, Prague)
3. Ferrara Antonella (University of Pavia)
4. Magni Lalo (University of Pavia)
 

2 - Software Tools and Programming

Referee: Riccardo Bellazzi (Dip. di Ingegneria, Univ. di Pavia)
 

PROGRAM
The Software tools and programming will provide the basics of Matlab and SAS and elements of R. The course will be strictly linked with the Probability and Statistics and Physical and Mathematical modelling courses, and it will aim at providing the knowledge on software instruments which are fundamental for a practical understanding of the methodological topics treated in the Master.
A short introduction on computer networks and Internetworking will be also given in order to complete the students' curriculum in the light of their activities during the stage period.

BASIC REQUIREMENTS
Basic knowledge of PCs: Windows, Office. Basic mathematical skills.

OBJECTIVES
Matlab objectives: to learn how to simulate linear and non linear dynamical systems using Matlab e Simulink. To write simple scripts and function files.
SAS objectives: to learn the basic steps of data analysis using the SAS interface.
R: to perform statistical analysis and statistical tests from the command line and to write simple scripts.

DURATION: 50 hours
TERM: (part 1) January 2008
(part 2) February 2008
EXAM: (part 1) 5 February 2008
(part 2) 15 February 2008
CREDITS: 5 ECTS

USEFUL READINGS:
ON-line material about Matlab (www.mathworks.com) and R (http://www.r-project.org/).

FACULTY:
1. Bellazzi Riccardo (University of Pavia)
2. Panarese Paolo (The Mathworks)
3. Davide Raimondo (University of Pavia)
4. Favalli Lorenzo (University of Pavia)
5. Panzarasa Silvia (CBIM-Pavia)
6. Leonardi Giorgio (University of Pavia)
7. Sacchi Lucia (University of Pavia)

 

3 - Probability and Statistic

Referee: Antonietta Mira (Dip. di Economia, Università dell'Insubria, Varese)
 

PROGRAM
Exploratory data analysis. Advanced probability theory and statistical inference (classical and Bayesian approach): point estimation (properties of estimators; Maximum likelihood approach; Method of moments), confidence intervals (for the mean and the variance of a normal distribution; for the proportion of successes; for large samples), hypothesis testing (parametric and non-parametric approach). Linear regression model: least square estimators and properties; estimator of the error’s variance; inference on slope and intercept parameter (with a single explanatory variable and with more explanatory variables).

BASIC REQUIREMENTS
Probability Theory: (union, intersection, probability space, probability distribution and density function, law of total probability, conditional probability, independent events, Bayes theorem), combinatorics, discrete random variables (Uniform, Bernoulli, Binomial, Geometric, Poisson) and continuous variables (Uniform, Exponential, Gaussian, Student-T, Gamma).
Descriptive Statistics: concepts of frequency (relative and absolute), expected value, variance, standard deviation, covariance, correlation, histogram, two way contingency tables. Presenting data in tables, charts, histograms, Box-plots.
Inferential Statistics: concepts of population, sample and estimator.

OBJECTIVES
The course aims at reviewing the basic concepts of probability and statistics and advancing the knowledge on these topics by introducing high level modelling and hypothesis testing tools.

DURATION: 50 hours
TERM: February 2008
EXAM: 3 March 2008
CREDITS: 6 ECTS

USEFUL READINGS:
1. G. Casella, R.L. Berger, Statistical inference, 2nd ed., Pacific Grove (CA), Duxbury (2002).
2. A.M. Mood, F.A. Graybill, D.C. Boes, Introduction to the theory of statistics, 3rd ed., Auckland etc, McGraw-Hill (1974).
3. P.G. Hoel, S.C. Port, C.J. Stone, Introduction to statistical theory, Boston etc., Houghton Mifflin (1971).
4. D.A. Moore and G.P. McCabe, Introduction to the practice of statistics, 5th edition, W.H. Freeman and Co., New York.

FACULTY:
1. Mira Antonietta (University of Varese)
2. Marin Jean-Michel (Université d’Orsay)
3. Paola Cerchiello (University of Pavia)

4 - Business Managemente and Finance I

Referee: Antonella Zucchella (Dip. di Economia, Univ. di Pavia)
 

PROGRAM
Complexity in the economic system - Variety, complexity and economic development: innovation, new industries growth and economic change.
Complexity in business organizations - System theories and organizations. The firm as a complex system. Foundations of business administration and management. Business strategy and planning. Business modelling. Organizing and managing complex organizations in the knowledge economy.
Complexity in finance - An overview of the financial markets: Markets, instruments, interest rates, financial institutions. Financial market and net present value (NPV). How to value bond and stocks. NPV and capital budget. Strategy and analysis in using NPV. Capital Market theory. Return and risk and the CAPM. Risk, Return and capital budgeting. Application of the CAPM.

BASIC REQUIREMENTS
There is no basic requirement, because the course is intended to provide fundamental approaches and tools of firma management for students without previous background.

OBJECTIVES
To understand the firm management in the framework of complex systems and to develop an understanding of management problems and approaches.

DURATION: 50 hours
TERM: March 2008
EXAM: 17 March 2008
CREDITS: 6 ECTS

USEFUL READINGS:
1. R. Grant, Strategic management. Texts and cases, 6th edition, Blackwell.

FACULTY:
1. Zucchella Antonella (University of Pavia)
2. Majocchi Antonio (University of Pavia)
3. Denicolai Stefano (University of Pavia)

5 - Classical Computational Methods

Referee: Oreste Nicrosini (INFN - Pavia)
 

PROGRAM
Numerical differentiation and integration; root finding; matrices and linear algebraic equations; ordinary differential equations; spectral methods; partial differential equations; the Monte Carlo method. Computer labs with Matlab and other numerical libraries.

BASIC REQUIREMENTS
Undergraduate level courses on calculus. Elements of probability and statistics.

OBJECTIVES
To get accustomed with the mostly used numerical methods in modelling and simulation.

DURATION: 40 hours
TERM: March/April 2008
EXAM: 8 April 2008
CREDITS: 5 ECTS

USEFUL READINGS:
1. T. Pang, An Introduction to Computational Physics, Cambridge University Press, 1997.
2. A. Quarteroni, R. Sacco, F. Saleri, Numerical Mathematics, Springer, 2000.
3. S.S.M. Wong, Computational Methods in Physics and Engineering, World Scientific, 1997.

FACULTY:
1. Piccinini Fulvio (INFN-Pavia)
2. Perugia Ilaria (University of Pavia)
3. Boffi Daniele (University of Pavia)
4. Gianazza Ugo (University of Pavia)

6 - Soft Computing and other advanced computational techniques

Referee: Giuseppe De Nicolao (Dip. di Ingegneria, Univ. di Pavia)
 

PROGRAM
Function identification and reconstruction; cellular automata; non-linear statistical models; neural network based modelling; fuzzy logic and fuzzy control, neuro-fuzzy techniques; evolutionary computation; introduction to parallel computing; computer laboratory using Matlab.

BASIC REQUIREMENTS
Elements of Mathematics and Physics Probability and Statistics.

OBJECTIVES
Selecting the proper soft computing method best suited to a given learning problem, ability to apply soft computing methods to practical problems.

DURATION: 40 hours
TERM: April 2008
EXAM: 22 April 2008
CREDITS: 5 ECTS

USEFUL READINGS:
1. T. Hastie, R. Tibshirani and J. Friedman, The Elements of Statistical Learning. Springer-Verlag, 2001.
2. D. Nauck, F. Klawonn, R Kruse, Foundations of Neuro-Fuzzy Systems, Wiley, 1997.
3. K. Deb, Optimization for engineering design: Algorithms and examples. New Delhi: Prentice-Hall, 1995.

FACULTY:
1. Deb Kalyanmoy (Indian Institute of Technology, Kanpur)
2. Kruse Rudolf (Otto-von-Guericke-Universität, Magdeburg)
3. Verri Alessandro (University of Genova)
 

7 - Business Management and Finance II

Referee: Antonella Zucchella (Dip. di Economia, Univ. di Pavia)
 

PROGRAM
Knowledge management: Knowledge creation and utilisation in the knowledge based economy: the firm knowledge base, its influence on firm behaviour and performances, knowledge dynamics in innovation networks. Knowledge complexity and industrial organization.
Innovation management: Organising and managing knowledge intensive activities (R&D, VAS, Finance, health care). The role of HRM. Innovation management models. Managing the relationship between marketing intelligence and R&D. The innovation pipeline from product/service concept to marketing.
Project management: Approaches and models for PM. Group management, organisational and management issues.

BASIC REQUIREMENTS
The attendance and successful completion of Module 1.

OBJECTIVES
To provide a deeper understanding of selected issues regarding capital markets and firm management.

DURATION: 40 hours
TERM: May 2008
EXAM: 19 May 2008
CREDITS: 5 ECTS

FACULTY:
1. Bormetti Giacomo (IUSS-Pavia)
2. De Giuli Elena (University of Pavia)
3. Saviotti Pier Paolo (Université Pierre Mendès, Grenoble)
4. Onetti Alberto (University of Varese)

 

8 - Dynamics of Complex Systems

Referee: Guido Montagna (Dip. di Fisica, Univ. di Pavia)
 

PROGRAM
The course is divided into three main parts as follows:
Non-linear dynamics and chaos
Non-linear dynamics; limit cycles; maps: Lyapunov exponents; strange attractors; fractals; chaotic systems; time series analysis; bifurcations and catastrophes; evidences of chaos in complex systems.
Stochastic processes and econophysics:
Brownian motion and diffusion; random walks; Fokker-Planck equations; stochastic calculus and stochastic differential equations; application to option pricing (Black&Scholes theory); introduction to non-Gaussian stochastic processes; Levy stable distributions and power-laws; analysis of high frequence data and stylized facts in financial markets; recent advances in econophysics.
Complex networks.
Models of networks: random, small-world and scale-free networks; statistical measures for networks; complex networks in nature and society; epidemic spreading on networks; vulnerability and robustness of networks; applications of network science.
 

BASIC REQUIREMENTS
Elements of Mathematics and Physics Probability and Statistics, Basic notions of Finance and ICT.

OBJECTIVES
The aim of the course is to describe the theoretical and computational methods mostly used in the study and modelling of the dynamics of complex systems, both in nature and society. The three main theoretical frameworks considered are: non-linear dynamics and chaos; stochastic processes; complex networks. Particular emphasis is put on the applications of the methods to interdisciplinary problems of various kinds, ranging from population dynamics to catastrophic events, from financial risk management to the evolution and structure of technological, social and biological networks. Special attention is paid to those complex systems of increasing importance in modern society.

DURATION: 40 hours
TERM: May 2008
EXAM: 30 May 2008
CREDITS: 5 ECTS

USEFUL READINGS:
1. K.T. Alligood, T.D. Sauer and J.A. Yorke, Chaos: an Introduction to Dynamical Systems, Springer.
2. S.H. Strogatz, Nonlinear Dynamics and Chaos, Westview Press.
3. C.W. Gardiner, Handbook of Stochastic Methods for Physics, Chemistry and the Natural Sciences, Springer.
4. W. Paul and J. Baschnagel, Stochastic Processes from Physics to Finance, Springer.
5. R.N. Mantegna and H.E. Stanley, An Introduction to Econophysics: Correlations and Complexity in Finance, Oxford Univ. Press.
6. J.P. Bouchaud and M. Potters: Theory of Financial Risk and Derivative Pricing: from Statistical Physics to Risk Management, Cambridge Univ. Press.
7. S.N. Dorogovtsev and J.F.F. Mendes, Evolution of Networks from Biological Nets to the Internet and WWW, Oxford Univ. Press.
8. R. Pastor Satorass and A. Vespignani, Evolution and Structure of the Internet: A Statistical Physics Approach, Cambridge Univ. Press.
9. G. Caldarelli, Scale-Free Networks – Complex Webs in Nature and Technology, Oxford Univ. Press.

FACULTY:
1. Caldarelli Guido (University of Rome)
2. Piccardi Carlo (Politecnico di Milano)
3. Dercole Fabio (Politecnico di Milano)
4. Lillo Fabrizio (University of Palermo)
5. Montagna Guido (University of Pavia)
 

9 - Computational and Statistical Data Mining Methods

Referee: Paolo Giudici (Dip. di Statistica, fac. Scienze Politiche, Univ. di Pavia)

PROGRAM
Theory part: Exploratory data analysis; Association rules and models; Distance functions and cluster models; Linear and logistic regression models; Tree models; Multi-layer perceptrons; Model assessment and comparison.
Case-studies part (with R): market basket analysis, web usage mining; profiling; credit risk management; operational risk management; customer relationship management.

BASIC REQUIREMENTS
Fundamental notion of mathematics, statistics, software tools and programming. Elements of Mathematics and Physics.

OBJECTIVES
The course is an introduction to data mining methods. The methodology will be explained both theoretically and by means of practicals, where the R software will be employed.
The course will first describe the meaning and the application areas of data mining. It will then describe the main computational and statistical tools necessary to solve data mining problems: from the organisation of the data, to exploratory analysis, to model and pattern specification.
A particular attention will be devoted to the important theme of model comparison, by means of suitable diagnostic tools.

DURATION: 40 hours
TERM: June 2008
EXAM: 16 June 2008
CREDITS: 5 ECTS

USEFUL READINGS:
1. P. Giudici, Applied data mining, Wiley, 2003.
2. Hastie T., Tibshirani R., Friedman J., The elements of statistical learning, Springer Verlag, 2001.

FACULTY:
1. Giudici Paolo (University of Pavia)
2. Figini Silvia (University of Pavia)

 

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