Professors AY 2024-2025
Professors
ANDREINI PAOLO
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Code 2016226 -
[2016226] INTRODUCTORY COURSE FOR MSC DEGREES -
Credit(s): 0
More information and training material
Orario del corso dall' 12-09-2024 al 27-09-2024:
lunedì, martedì, giovedì, venerdì ore 14-18
BARTOLINI SANDRO
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Code 2000203 -
[2000203] DESIGN OF APPLICATIONS, SERVICES AND SYSTEMS -
Credit(s): 9
More information and training material
For any doubt, drop an email to the teacher.
BIANCHINI GIANNI
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Code 2016827 -
[2016827] ADVANCED CONTROL SYSTEMS -
Credit(s): 12
More information and training material
Website (Part 1): https://www3.diism.unisi.it/~giannibi/teaching/
Website (Part 2): http://control.dii.unisi.it/anc/
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Code 2016828 -
[2016828] ROBUST AND PREDICTIVE CONTROL -
Credit(s): 6
More information and training material
For further information and course material, please refer to the course page on the Unisi e-learning platform.
BIANCHINI MONICA
- Code 2000189 - [2000189] BIOINFORMATICS - Credit(s): 6
CASINI MARCO
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Code 2016823 -
[2016823] SYSTEM IDENTIFICATION -
Credit(s): 6
More information and training material
More info about the course are available in the web page:
https://control.dii.unisi.it/sysid/ -
Code 2016827 -
[2016827] ADVANCED CONTROL SYSTEMS -
Credit(s): 12
More information and training material
Website (Part 1): https://www3.diism.unisi.it/~giannibi/teaching/
Website (Part 2): http://control.dii.unisi.it/anc/
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Code 2016829 -
[2016829] APPLIED NONLINEAR CONTROL -
Credit(s): 6
More information and training material
Website: http://control.dii.unisi.it/anc/
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Code 2017432 -
[2017432] SYSTEM IDENTIFICATION AND DATA ANALYSIS -
Credit(s): 12
More information and training material
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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Code 2000207 -
[2000207] MODELS AND LANGUAGES FOR BIOINFORMATICS -
Credit(s): 6
More information and training material
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
- Code 109163D - [109163D] SENSORS AND MICROSYSTEMS - Credit(s): 6
GARULLI ANDREA
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Code 2017431 -
[2017431] STATE ESTIMATION AND FILTERING -
Credit(s): 6
More information and training material
More info about the course are available in the web page:
http://www.dii.unisi.it/~control/sef -
Code 2017432 -
[2017432] SYSTEM IDENTIFICATION AND DATA ANALYSIS -
Credit(s): 12
More information and training material
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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Code 2016825 -
[2016825] DYNAMIC PROGRAMMING AND REINFORCEMENT LEARNING -
Credit(s): 6
More information and training material
More information about the course can be found at
GIORGI ROBERTO
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Code 109156D -
[109156D] HIGH PERFORMANCE COMPUTER ARCHITECTURE -
Credit(s): 9
More information and training material
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
- Code 2016821 - [2016821] FUNDAMENTALS OF MACHINE LEARNING - Credit(s): 6
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Code 2016821 -
[2016821] FUNDAMENTALS OF MACHINE LEARNING -
Credit(s): 6
More information and training material
Informazioni sul corso:
Webpage of the course on classroom at
https://classroom.google.com/u/0/c/NzEyNTkxMjA2MzM5
class code: rk34cam -
Code 2016822 -
[2016822] MACHINE LEARNING -
Credit(s): 12
More information and training material
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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Code 2000194 -
[2000194] LANGUAGE PROCESSING TECHNOLOGIES -
Credit(s): 6
More information and training material
The course material (lecture slides and example code) is available on the USienaIntegra (Moodle) site:
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Code 2013578 -
[2013578] BIG DATA -
Credit(s): 6
More information and training material
Relevant material is available on the course page in unisi moodle platform.
MECOCCI ALESSANDRO
- Code 2017429 - [2017429] DIGITAL IMAGE PROCESSING - Credit(s): 6
MELACCI STEFANO
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Code 2014376 -
[2014376] NEURAL NETWORKS -
Credit(s): 6
More information and training material
The course webpage is available on the USienaIntegra platform,
https://elearning.unisi.it/course/view.php?id=11749 -
Code 2016822 -
[2016822] MACHINE LEARNING -
Credit(s): 12
More information and training material
Informazioni sul corso:
https://classroom.google.com/u/0/c/NzEyNTkxMjA2MzM5
class code: rk34cam
II modulo: vedi campo relativo.
MOCENNI CHIARA
- Code 2017398 - [2017398] COMPLEX SYSTEMS - Credit(s): 6
PANZARDI ENZA
- Code 109163D - [109163D] SENSORS AND MICROSYSTEMS - Credit(s): 6
PAOLETTI SIMONE
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Code 109151D -
[109151D] DISCRETE-EVENT SYSTEMS -
Credit(s): 6
More information and training material
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
- Code 109161D - [109161D] NETWORK OPTIMIZATION - Credit(s): 6
PRATTICHIZZO DOMENICO
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Code 2000184 -
[2000184] HUMAN-CENTERED ROBOTICS -
Credit(s): 6
More information and training material
Bibliographic references will be provided during the course.
SALVIETTI GIONATA
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Code 2016830 -
[2016830] INDUSTRIAL ROBOTICS -
Credit(s): 6
More information and training material
Numerous tools for simulating industrial robots will be made available.
SCARSELLI FRANCO
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Code 2016824 -
[2016824] ADVANCED MACHINE LEARNING -
Credit(s): 6
More information and training material
More information is available on home page of the course on unisi moodle platform.
TRENTIN EDMONDO
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Code 109148D -
[109148D] ARTIFICIAL INTELLIGENCE -
Credit(s): 9
More information and training material
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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Code 2016226 -
[2016226] INTRODUCTORY COURSE FOR MSC DEGREES -
Credit(s): 0
More information and training material
Orario del corso dall' 12-09-2024 al 27-09-2024:
lunedì, martedì, giovedì, venerdì ore 14-18
