Notizie
Thesis
For any information about thesis, email me!
Principles of Computer Science I - 24/25
Google Classroom Code: 5lmqhuk
First semester, starting from: 05 October 2024.
Lectures:
- Thursday, 9:00 - 11:00
- Friday, 9:00 - 12:00
Classroom Psicologia I, Fisiologia Generale e Antropologia Farmacia e Medicina (CU026, E01PS1L101).
To reach the classroom please enter the brown gate in front of the café of the Viale Regina Elena main entrance, walk through the path and enter the door where there is written Psicologia Aula on the top. The classroom is the first door on the left.
The lessons will be 100% in presence, according to Sapienza rules: https://www.uniroma1.it/en/notizia/covid-19-phase-3-person-and-online-classes-exams-and-graduation-sessions
Please, refer to the Google Classroom of the course for further information about study material and exams.
AI Lab: Computer Vision and NLP 24/25
Course Classroom Code: ilb3y2t
Second semester, starting from 26 February 2025.
Wednesday: 13:00 - 16:00
Friday: 15:00 - 17:00
The class for the lecture is Aula 3 De Lollis, RM158-E01PTEL003. The class entrance is in Via Tiburtina 205.
Study material and course announcements can be found at the Google Classroom of the course.
Exam Dates
-
TBA
Orari di ricevimento
English
It is possible to book an appointment by mail. Due to the pandemic situation, the appointment will be held online by using any of the common communication software, e.g. meet, zoom.
Italiano
È possibile prenotare il ricevimento inviando una mail. Data la corrente situazione pandemica, il ricevimento si svolgerà in forma online utilizzando i più comuni software di comunicazioni quali meet e zoom.
Curriculum
Daniele Pannone is an Assistant Professor at the Department of Computer Science, Sapienza University (Rome). Since 2015, he is a member of the Computer Vision Laboratory (VisionLab) in the same department, and he has obtained the Ph.D. in 2018 under the supervision of Professor Luigi Cinque and Professor Danilo Avola, working on algorithms for smart environment monitoring through drones. Daniele's research topics are mainly focused on Computer Vision, Machine/Deep Learning and Signal Processing.
Daniele is a member of IAPR, CVPL and IEEE.