Romeo Lanzino ☕️
Romeo Lanzino

Post-doc Researcher

Sapienza University of Rome

About Me

I am a Post-doc of Artificial Intelligence at Sapienza University of Rome, with a keen interest in pushing the boundaries of Computer Vision. My research lies in developing and applying innovative techniques such as Deep, Meta-, Few-shot, and Continual Learning to real-world problems. With a solid background in Computer Science, I possess the ability to design, implement, and refine models that drive meaningful impact. I am excited to bring my skills and experience to the forefront of AI research, driving innovation and advancing the field through collaborative and cutting-edge projects.

Interests
  • Artificial Intelligence
  • Deep Learning
  • Computer Vision
  • Meta-learning
  • Bioinformatics
Education

  • National PhD in Artificial Intelligence

    Sapienza University of Rome & others

  • MSc in Computer Science

    Sapienza University of Rome

  • BSc in Computer Science

    Sapienza University of Rome

Education

  1. National PhD in Artificial Intelligence

    Sapienza University of Rome & others
    Thesis titled “Sparking Light on Deep Learning in EEG Research”.
    Read thesis

  2. MSc in Computer Science

    Sapienza University of Rome
    Thesis titled “Laplacian-regularized Transductive Inference for Few-shot Object Detection”.

  3. BSc in Computer Science

    Sapienza University of Rome
    Thesis titled “Design and development of the statistics section of the InfoProf mobile app”.
Skills & Hobbies
Research

Since 2021

Deep Learning

Since 2020

Data Science

Since 2019

Programming

Since 2016

Tabletop RPGs

Forever DM

Videogames
Languages
100%
Italian
100%
English
25%
Swedish
1%
R'lyehian
Publications
Romeo Lanzino, Danilo Avola, Federico Fontana, Luigi Cinque, Francesco Scarcello, Gian Luca Foresti (2024). SATEER: Subject-Aware Transformer for EEG-Based Emotion Recognition. Int J Neural Syst.
Cite URL
Romeo Lanzino, Federico Fontana, Anxhelo Diko, Marco Raoul Marini, Luigi Cinque (2024). Faster Than Lies: Real-time Deepfake Detection using Binary Neural Networks. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.
PDF Cite
Federico Fontana, Romeo Lanzino, Anxhelo Diko, Gian Luca Foresti, Luigi Cinque (2024). CycleBNN: Cyclic Precision Training in Binary Neural Networks.
Cite arXiv URL
Federico Fontana, Romeo Lanzino, Marco Raoul Marini, Danilo Avola, Luigi Cinque, Francesco Scarcello, Gian Luca Foresti (2024). Distilled Gradual Pruning With Pruned Fine-Tuning. IEEE Transactions on Artificial Intelligence.
Cite DOI URL
Danilo Avola, Luigi Cinque, Angelo Di Mambro, Romeo Lanzino, Daniele Pannone, Francesco Scarcello (2024). Multi-Stream 1D CNN for EEG Motor Imagery Classification of Limbs Activation. IEEE Access.
Cite DOI URL
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