Hello, visitor! 🖖

I am Tomo, aka Tomaso Trinci, a Data Scientist at Verizon Connect in Florence. My journey started at Target Reply in Milan before I headed back here to earn my Ph.D. in Machine Learning with the Global Optimization Laboratory.

With a background blending Math and Computer Engineering, I am currently focused on computer vision, intelligent vehicle applications, and multimodal models. In the past, I've also spent time diving into continual learning and sustainable AI.

When I'm not training models, I’m training my palate; I completed the first level of the sommelier course at FISAR, mostly because wine tasting is a task that machine learning (still) hasn't managed to solve. I'm also an avid comics reader, from manga to graphic novels, and my favorite author is Zerocalcare.

P.S. I know next to nothing about front-end. This page was realized by simply vibing with Gemini and Claude 🤖

Email GitHub LinkedIn Bluesky Google Scholar

Blog

Publications

FLaRA: Predicting Future Latent Representations for Accident Anticipation

L. Caselli, T. Trinci, T. Bianconcini, S. Magistri, L. Taccari, F. Sambo, A.D. Bagdanov (2026).

Preprint, Accepted at International Conference on Intelligent Transportation Systems (ITSC)

[PDF]

VZCrash: A Large-Scale IMU Dataset of Ego-Vehicle Crashes

T. Bianconcini, H. P. Monteagudo, A. Pjetri, T. Trinci, L. Taccari (2026).

Preprint, Accepted at International Conference on Intelligent Transportation Systems (ITSC)

[PDF] [Dataset]

Enhancing Multimodal Large Language Models for Safety-Critical Driving Video Analysis

T. Trinci, H. P. Monteagudo, L. Taccari (2026).

Preprint, Accepted at International Conference on Intelligent Transportation Systems (ITSC)

[PDF]

Color is not enough: dataset and method for identifying relevant traffic lights in driving scenes

T. Trinci, S. Magistri, T. Bianconcini, L. Sarti, L. Taccari, F. Sambo (2025).

IEEE Transactions on Intelligent Transportation Systems, pp. 1116-1125

[PDF] [Dataset]

EFC++: Elastic Feature Consolidation with Prototype Re-balancing for Cold Start Exemplar-free Incremental Learning

S. Magistri, T. Trinci, A. Soutif-Cormerais, J. van de Weijer, A.D. Bagdanov (2025).

[Under Review since July 2024]

[PDF] [Code]

How green is continual learning, really? Analyzing the energy consumption in continual training of vision foundation models

T. Trinci, S. Magistri, R. Verdecchia, A.D. Bagdanov. (2024).

Computer Vision – ECCV 2024 Workshops, Part XXII, pp. 300-317.

[PDF] [Code]

Elastic feature consolidation for cold start exemplar-free incremental learning

S. Magistri, T. Trinci, A. Soutif-Cormerais, J. van de Weijer, A.D. Bagdanov (2024).

The Twelfth International Conference on Learning Representations (ICLR).

[PDF] [Code]

Cross-Model Temporal Cooperation Via Saliency Maps for Efficient Recognition and Classification of Relevant Traffic Lights

T. Trinci, T. Bianconcini, L. Sarti, L. Taccari, F. Sambo. (2023).

International Conference on Intelligent Transportation Systems (ITSC), pp. 2758-2763.

[PDF] [Code]

Zeros of slice functions and polynomials over dual quaternions

G. Gentili, C. Stoppato, T. Trinci (2021).

Transactions of the American Mathematical Society, pp. 5509-5544.

[PDF]

Patents

Systems and methods for detecting traffic light violations

T. Trinci, T. Bianconcini, L. Sarti, L. Taccari, F. Sambo (2026).

US Patent App. 18/907,984.

[PDF]

Systems and methods for reducing power consumption of executing learning models in vehicle systems

T. Trinci, T. Bianconcini, L. Taccari, F. Sambo, L. Sarti, S. Magistri (2026).

US Patent 12,518,522.

[PDF]