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Natural Language Processing (NLP) - with Prof. Faralli
When: Feb 20 till May 30 - Tuesday 4-7pm; Thursday 2-4pm
Where: Aula Magna Building C RM111
Course Website & Material: https://github.com/iacopomasi/NLP
Website for students: classroom.google.com/c/NTQwNjAzNDk5NjY2 (code given in the first lecture)
Exams: Exam dates are managed using the private classroom
Artificial Intelligence & Machine Learning - Unit II
When: Feb 20 till May 30 - Tuesday 2-4pm; Thursday 4-7pm
Where: Aula 1, Building RM018
Website for students: classroom.google.com/c/NTkxMzc5NDc1NzYw (code given in the first lecture)
Course Website & Material: https://iacopomasi.github.io/AI-ML-Unit-2
Exams: Exam dates are managed using the private classroom
Fondamenti di Programmazione
Quando: (solo in presenza) martedi 8.00-11.00 Canale 2 (M-Z), giovedi 11.00-13.00 Canale 2 (M-Z)
Dove: Edificio: CU046 Aula T2, Giurisprudenza. Piazzale Aldo Moro, 5 ROMA
Sito web: https://classroom.google.com/u/2/c/NTQ3OTYyNzY5NTQ3 (fornisco codice a lezione per entrare)
Forum: https://q2a.di.uniroma1.it/fondamenti-di-programmazione-22-23
Office hours/Ricevimento
I am always available to clarify concepts and help students via email. Most of the time email communication will be sufficient. If need be, we can also meet in person or remotely using Zoom. Just send an email and we will schedule a date.
Thesis/Tesi
For any information about the thesis, please see iacopomasi.github.io/workwithme.html
Comunicazione dalla segreteria didattica
La comunità studentesca quando non riesce a prenotare una prova di esame deve verificare che gli appelli siano stati aperti, quindi soprattutto se si è fuori corso o coorti occorre scrivere a segr.didattica@di.uniroma1.it con la email istituzionale studente ed indicare:
- corso di laurea
- anno di iscrizione al I anno
- insegnamento
- docente con il quale prenotare l'appello
| Course | Code | Year | Course - Attendance | Bulletin board |
|---|---|---|---|---|
| FONDAMENTI DI PROGRAMMAZIONE | 1015883 | 2023/2024 | ||
| NATURAL LANGUAGE PROCESSING | 1038141 | 2023/2024 | ||
| ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING | 10595618 | 2023/2024 | ||
| FONDAMENTI DI PROGRAMMAZIONE | 1015883 | 2022/2023 | ||
| NATURAL LANGUAGE PROCESSING | 1038141 | 2022/2023 | ||
| ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING | 10595618 | 2022/2023 | ||
| FONDAMENTI DI PROGRAMMAZIONE | 1015883 | 2021/2022 | ||
| COMPUTER GRAPHICS | 1047673 | 2021/2022 | ||
| ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING | 10595618 | 2021/2022 | ||
| FONDAMENTI DI PROGRAMMAZIONE | 1015883 | 2020/2021 | ||
| ARCHITETTURA DEGLI ELABORATORI | 1015881 | 2020/2021 | ||
| FONDAMENTI DI PROGRAMMAZIONE | 1015883 | 2019/2020 | ||
| FONDAMENTI DI PROGRAMMAZIONE | 1015883 | 2018/2019 | ||
| FONDAMENTI DI PROGRAMMAZIONE | 1015883 | 2017/2018 |
I am always available to clarify concepts and help students via email. Most of the time email communication will be sufficient. If need be, we can also meet in person or remotely using Zoom. Just send an email and we will schedule a date.
Dr. Iacopo Masi is Associate Professor in the Computer Science Department at Sapienza, University of Rome. Till August 2022, I was also Adjunct Research Assistant Professor in the Computer Science Department at the University of Southern California (USC). Previously Dr. Masi was Research Assistant Professor and Research Computer Scientist at the USC Information Sciences Institute (ISI). Dr. Masi earned his Ph.D. degree in Computer Engineering from the University of Firenze, Italy. Immediately after, he moved to California and joined USC, where he was a postdoctoral scholar. Dr. Masi has been Area-Chair of several conferences in computer vision (WACVs, ICCV 21, ECCV 22) and currently serves as Associate Editor for The Visual Computer - International Journal of Computer Graphics. He organized an International Workshop on Human Identification at ICCV 17 and was Workshop Chair at SIBGRAPI 18. Dr. Masi was awarded the prestigious Rita Levi Montalcini award by the Italian government in 2018. Dr. Masi s main research interest lies in solving the computer vision problem. His background covers topics such as tracking, person re-identification, 2D/3D face recognition, and modeling, adversarial robustness, and facial manipulation detection.