Dear all,
Next Tuesday (14/04/2026) we will host Dr. Edoardo Pasca, Head of the Computed Tomography and Imaging group at the Scientific Computing division of the national UK Science and Technology Facilities Council (STFC). He is an expert in solution methods and software for inverse problems in image reconstruction. See below for a more complete biography.
Dr. Edoardo Pasca leads a team of scientists that develop the Core Imaging Library software (CIL). CIL is an open source, mainly Python, framework for tomographic imaging originally developed for X-ray Computed Tomography. CIL has been used in various fields such as Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and Synthetic Aperture Radar (SAR).
Here are the events scheduled for the day:
Workshop (hands on session) on CIL for CT reconstruction.
TIME: 9:15-11:00 (morning session), 14:00-16:30 (afternoon session)
LOCATION: TBD, Dipartimento di Matematica
Address: Largo Bruno Pontecorvo, 5 – 56127 Pisa
The event is free but registration is mandatory: if you’d like to attend, please fill in this form
by 12/04/2026.
ABSTRACT: We will run a group-based practical session using CIL in Python for X-ray CT data manipulation and reconstruction. An introduction on concepts of X-ray CT data acquisition, optimization, iterative reconstruction algorithms and regularization will be given, followed by exercises in CIL.
No software installation will be required: the sessions will be based on our Jupyter notebook training material, and participants will have access to the material in the cloud.
Knowledge of Python or object oriented programming is not mandatory to attend the event.
By the end of the session you will know more about computational imaging and potentially be ready to use CIL for your research.
Seminar (part of the Numerical Analysis seminar series)
TITLE: Stochastic Optimisation algorithms in CIL
TIME: 11:00-12:00
LOCATION: Dipartimento di Matematica (Aula Magna (DM))
Address: Largo Bruno Pontecorvo, 5 – 56127 PisaABSTRACT: Stochastic optimization algorithms are commonly used in the training of machine learning models because they ensure progress towards the solution while reducing the per-iteration computational costs. In this seminar, I will talk about the Stochastic Optimization algorithms available in the Core Imaging Library (CIL) and show some usage on real data at scale.
Biography:
Edoardo Pasca graduated in Physics and obtained a PhD in material science and technology at the University of Florence. After working as a post-doc in experimental condensed matter physics, he transitioned to software development and imaging. He now leads the Computed Tomography and Imaging group in the Scientific Computing of the Science Technology Facilities Council (STFC). The group supports material-science and medical-imaging scientists as well as UK national facilities such as the ISIS Neutron and Muon source, the UK synchrotron Diamond Light Source, the Central Laser Facility (CLF) and their users.
Please do not hesitate to contact me if you need any additional information.
Best wishes,