[AY 25-26] Deep Learning for the classification of archaeological pottery

As part of its teaching offer for the 2025-2026 academic year, LAD, in collaboration with the Doctoral School in Archaeology and the School of Specialization in Archaeological Heritage at Sapienza Università di Roma, is organising a theoretical-practical teaching lab on the application of Computer Vision and Deep Learning methods for the study and classification of pottery.

Course objectives

The lab pursues two main objectives:

1. Mastering AI tools for the study of archaeological pottery, following the entire workflow: from digitisation to publication, using the open-source software PyPottery.
2. Building a dataset: contributing to the creation of a shared dataset to “teach” AI to see and classify finds like an archaeologist.

Programme

The lab will provide practical skills in:

• Introduction to Artificial Intelligence and its applications in archaeology.
• Installation and advanced guidance on the use of PyPottery.
• Creating and curating datasets for training deep learning models.

This approach makes it possible to automate and speed up the documentation and analysis of archaeological materials, supporting new forms of digital management of legacy data (Legacy Data), helping to create new forms of knowledge and improving the accessibility of information. The course provides all the tools needed to master these techniques and apply them independently in your own research. Participation in the lab leads to the recognition of 2 CFU, where applicable.

Location and format

The activities will be held in person at Sapienza Università di Roma, in the LAD lab (Faculty of Letters and Philosophy building, CU003, 3rd floor), alternating with independent work sessions.

Coordinators

• Julian Bogdani (julian.bogdani@uniroma1.it)
• Lorenzo Cardarelli (lorenzo.cardarelli@uniroma1.it)

Registration

Registration closed as the maximum number of participants has been reached

To register, you need to fill in the Google Form by Sunday 8 March 2026 at the following address: […].

In case of withdrawal or complications, it is essential to notify us at lorenzo.cardarelli@uniroma1.it.

Lecture schedule

Three introductory lectures are planned:

• 13 March: Introduction to Artificial Intelligence in archaeology.
• 19 March: Presentation of PyPottery and introduction to the case study.
• 26 March: Defining the dataset and dividing up the material.

During the lab, periodic sessions will be scheduled to address any questions or issues (also available remotely). After the independent work phase, a final meeting is planned for model implementation and training.

Eligibility

The lab is open to anyone interested in exploring the use of computing technologies and automation in data management in greater depth.

Just need CFU?

Do you need course credits but can’t attend the whole course? A specific supplementary activity is available for those who only need to complete their CFU. This option is designed for non-specialist students or those with specific curricular needs.

Write to julian.bogdani@uniroma1.it to request participation in this option.

Additional information

Lab activities will be carried out under the BYOD (Bring Your Own Device) policy; it is therefore necessary to bring your own laptop.

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• Download the poster in PDF