Luca Moschella

Luca Moschella

Ph.D. student in Computer Science

Gladia research group, Sapienza University of Rome

About me

I am a Ph.D. student at the Sapienza University of Rome in the Gladia research group led by Professor Emanuele Rodolà.

I’m excited by many Computer Science fields and, in particular, by Artificial Intelligence. I am passionate about frontier research, crossing the boundaries of AI and other applied disciplines. Currently, my research focuses on geometric deep learning, representation learning, and reasoning.

I’m a strong believer of reproducibility in science, and make an effort to write clean, well organized and documented code. I strive to keep up to pace with the latest technological advancements and I like to think of myself as an early adopter.

I am a long time Linux user and open source enthusiast. When I can, I try to give back to the open-source community.

  • Artificial Intelligence
  • Geometric Deep Learning
  • Representation Learning
  • Reasoning


Teaching Assistant
Jan 2020 – Present Rome
  • Designed the course lab sessions to explain and show to the students fundamentals and cutting-edge techniques in many areas of deep learning.

  • Latest course material with interactive notebooks available here.


Open Source

NN Template
Popular template to bootstrap the scaffolding for your PyTorch project with PyTorch Lightning, Hydra, DVC, Weights and Biases, and Streamlit.
NN Template
Ultrawide Windows

Expose useful shortcuts to move windows, an easy-to-use middle ground between the default behavior and the tiling approach.

Currently, the 5th most popular Kwin script.

Ultrawide Windows


Reinforcement Learning Specialization
The Reinforcement Learning Specialization consists of 4 courses exploring the power of adaptive learning systems and artificial intelligence (AI).
See certificate
Student Volunteer
Selected volunteer student to help in the organization of the conference.


Memory Networks at AIDA
Mediterranean Machine Learning summer school
AAAI Conceptual Abastraction and Analogy in Natural and Artificial Intelligence
ACDL: 3rd Advanced Course on Data Science & Machine Learning
Machine Learning for Non-Matrix Data


Spectral Unions of Partial Deformable 3D Shapes
Mediterranean Machine Learning summer school
Spectral Unions of Partial Deformable 3D Shapes
Learning Set Operations for Deformable Shapes
ELLIS Workshop on Geometric and Relational Deep Learning
Learning Set Operations for Deformable Shapes