Docenti AA 2024-2025
ANDREINI PAOLO
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Codice: 2016226 -
[2016226] INTRODUCTORY COURSE FOR MSC DEGREES -
Crediti: 0
Altre informazioni e materiale didattico
Orario del corso dall' 12-09-2024 al 27-09-2024:
lunedì, martedì, giovedì, venerdì ore 14-18
BARTOLINI SANDRO
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Codice: 2000203 -
[2000203] DESIGN OF APPLICATIONS, SERVICES AND SYSTEMS -
Crediti: 9
Altre informazioni e materiale didattico
For any doubt, drop an email to the teacher.
BIANCHINI GIANNI
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Codice: 2016827 -
[2016827] ADVANCED CONTROL SYSTEMS -
Crediti: 12
Altre informazioni e materiale didattico
Website (Part 1): https://www3.diism.unisi.it/~giannibi/teaching/
Website (Part 2): http://control.dii.unisi.it/anc/
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Codice: 2016828 -
[2016828] ROBUST AND PREDICTIVE CONTROL -
Crediti: 6
Altre informazioni e materiale didattico
For further information and course material, please refer to the course page on the Unisi e-learning platform.
BIANCHINI MONICA
- Codice: 2000189 - [2000189] BIOINFORMATICS - Crediti: 6
CASINI MARCO
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Codice: 2016823 -
[2016823] SYSTEM IDENTIFICATION -
Crediti: 6
Altre informazioni e materiale didattico
More info about the course are available in the web page:
https://control.dii.unisi.it/sysid/ -
Codice: 2016827 -
[2016827] ADVANCED CONTROL SYSTEMS -
Crediti: 12
Altre informazioni e materiale didattico
Website (Part 1): https://www3.diism.unisi.it/~giannibi/teaching/
Website (Part 2): http://control.dii.unisi.it/anc/
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Codice: 2016829 -
[2016829] APPLIED NONLINEAR CONTROL -
Crediti: 6
Altre informazioni e materiale didattico
Website: http://control.dii.unisi.it/anc/
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Codice: 2017432 -
[2017432] SYSTEM IDENTIFICATION AND DATA ANALYSIS -
Crediti: 12
Altre informazioni e materiale didattico
More info about the course are available in the web pages:
http://www.dii.unisi.it/~control/sysid (**System Identification**)
http://www.dii.unisi.it/~control/sef (**State Estimation and Filtering**)
FALASCHI MORENO
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Codice: 2000207 -
[2000207] MODELS AND LANGUAGES FOR BIOINFORMATICS -
Crediti: 6
Altre informazioni e materiale didattico
Bioinformatics is a rapidly developing research field which is fundamental for the future development of biotechnologies.
Bioinformatics research is relevant for the territory of Siena and Tuscany, in which there are several major industries which have a bioinformatic unity. Bioinformatic research is currently under a quick development all over the world.
FORT ADA
- Codice: 109163D - [109163D] SENSORS AND MICROSYSTEMS - Crediti: 6
GARULLI ANDREA
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Codice: 2017431 -
[2017431] STATE ESTIMATION AND FILTERING -
Crediti: 6
Altre informazioni e materiale didattico
More info about the course are available in the web page:
http://www.dii.unisi.it/~control/sef -
Codice: 2017432 -
[2017432] SYSTEM IDENTIFICATION AND DATA ANALYSIS -
Crediti: 12
Altre informazioni e materiale didattico
More info about the course are available in the web pages:
http://www.dii.unisi.it/~control/sysid (**System Identification**)
http://www.dii.unisi.it/~control/sef (**State Estimation and Filtering**)
GIANNITRAPANI ANTONIO
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Codice: 2016825 -
[2016825] DYNAMIC PROGRAMMING AND REINFORCEMENT LEARNING -
Crediti: 6
Altre informazioni e materiale didattico
More information about the course can be found at
GIORGI ROBERTO
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Codice: 109156D -
[109156D] HIGH PERFORMANCE COMPUTER ARCHITECTURE -
Crediti: 9
Altre informazioni e materiale didattico
The teaching material is the reference text book and the lesson slides that are available on the site: https://hpca.diism.unisi.it/lezioni.htm
Suggestions for a better preparation: both in the written and oral exams (but also in the projects) the student is mainly required to show his/her detailed understanding of the topic, at least at the level shown by the teacher during the lesson. It's greatly appreciated the capacity of reasoning on the problem, rather then a mechanical (pedant) description of the topic.
In case of written exercise, we mainly look at the correctness of the solution (in terms of numbers) and a very short justification of the chosen way to carry out the exercise (lengthy general wording is completely unnecessary).
In case of oral question, the topic is typically one of the concepts illustrated during the lesson. Elements that are required are, for instance: the proof of the concept/theorem, precise schematic of the system, detailed behavior and functioning, reasons why this solution is used in the real-world.To follow the lessons online, refer to the most up-to-date information available on the course website https://hpca.diism.unisi.it/lezioni.htm
Office hours are each Monday 16:30-19:00 or on appointment (giorgi@unisi.it), either in room 110 (S. Niccolò) or via telco.
GORI MARCO
- Codice: 2016821 - [2016821] FUNDAMENTALS OF MACHINE LEARNING - Crediti: 6
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Codice: 2016821 -
[2016821] FUNDAMENTALS OF MACHINE LEARNING -
Crediti: 6
Altre informazioni e materiale didattico
Informazioni sul corso:
Webpage of the course on classroom at
https://classroom.google.com/u/0/c/NzEyNTkxMjA2MzM5
class code: rk34cam -
Codice: 2016822 -
[2016822] MACHINE LEARNING -
Crediti: 12
Altre informazioni e materiale didattico
Informazioni sul corso:
https://classroom.google.com/u/0/c/NzEyNTkxMjA2MzM5
class code: rk34cam
II modulo: vedi campo relativo.
MAGGINI MARCO
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Codice: 2000194 -
[2000194] LANGUAGE PROCESSING TECHNOLOGIES -
Crediti: 6
Altre informazioni e materiale didattico
The course material (lecture slides and example code) is available on the USienaIntegra (Moodle) site:
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Codice: 2013578 -
[2013578] BIG DATA -
Crediti: 6
Altre informazioni e materiale didattico
Relevant material is available on the course page in unisi moodle platform.
MECOCCI ALESSANDRO
- Codice: 2017429 - [2017429] DIGITAL IMAGE PROCESSING - Crediti: 6
MELACCI STEFANO
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Codice: 2014376 -
[2014376] NEURAL NETWORKS -
Crediti: 6
Altre informazioni e materiale didattico
The course webpage is available on the USienaIntegra platform,
https://elearning.unisi.it/course/view.php?id=11749 -
Codice: 2016822 -
[2016822] MACHINE LEARNING -
Crediti: 12
Altre informazioni e materiale didattico
Informazioni sul corso:
https://classroom.google.com/u/0/c/NzEyNTkxMjA2MzM5
class code: rk34cam
II modulo: vedi campo relativo.
MOCENNI CHIARA
- Codice: 2017398 - [2017398] COMPLEX SYSTEMS - Crediti: 6
PANZARDI ENZA
- Codice: 109163D - [109163D] SENSORS AND MICROSYSTEMS - Crediti: 6
PAOLETTI SIMONE
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Codice: 109151D -
[109151D] DISCRETE-EVENT SYSTEMS -
Crediti: 6
Altre informazioni e materiale didattico
Lecture notes, video recordings, past written exams and exercises with solutions, and software are available on the Moodle space of the course:
https://elearning.unisi.it/course/view.php?id=12989
PRANZO MARCO
- Codice: 109161D - [109161D] NETWORK OPTIMIZATION - Crediti: 6
PRATTICHIZZO DOMENICO
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Codice: 2000184 -
[2000184] HUMAN-CENTERED ROBOTICS -
Crediti: 6
Altre informazioni e materiale didattico
Bibliographic references will be provided during the course.
SALVIETTI GIONATA
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Codice: 2016830 -
[2016830] INDUSTRIAL ROBOTICS -
Crediti: 6
Altre informazioni e materiale didattico
Numerous tools for simulating industrial robots will be made available.
SCARSELLI FRANCO
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Codice: 2016824 -
[2016824] ADVANCED MACHINE LEARNING -
Crediti: 6
Altre informazioni e materiale didattico
More information is available on home page of the course on unisi moodle platform.
TRENTIN EDMONDO
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Codice: 109148D -
[109148D] ARTIFICIAL INTELLIGENCE -
Crediti: 9
Altre informazioni e materiale didattico
See the official webpage at http://www.dii.unisi.it/~trentin/Teaching.html
Video-presentation of the 6EC module (LM-40): https://www.youtube.com/watch?v=vmysauk1Pnw
-Disclaimer (for ERASMUS students)
Erasmus students are welcome. Nonetheless, tThere are NO DISCOUNTS for Erasmus students. All students are required to come through the exam FULLY positively in order to get their credits.
ZANVETTOR GIOVANNI GINO
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Codice: 2016226 -
[2016226] INTRODUCTORY COURSE FOR MSC DEGREES -
Crediti: 0
Altre informazioni e materiale didattico
Orario del corso dall' 12-09-2024 al 27-09-2024:
lunedì, martedì, giovedì, venerdì ore 14-18