Our latest research has been published in the PeerJ Computer Science journal.

We predict age and gender just by how you move the mouse. Our models can infer demographics from initial interactions on a website—no sensors or personal data needed.

Read more: peerj.com/articles/cs-...

It was a true honor to meet with Sir Simon Baron-Cohen, a world authority on autism, and his team during our visit to Cambridge. We shared our ASD detection research and are incredibly grateful for their attention. Excited for potential synergies ahead!

At #AIH2025 (Jesus College, Cambridge) we presented our paper on an AI system using eye-tracking + ML for early screening of Autism Spectrum Disorder (ASD).
Proud to contribute to advancing healthcare with AI!

#HealthcareAI #AutismResearch #MachineLearning

Just published our latest research in the conference "Artificial Intelligence in Healthcare"! Our paper presents an innovative system that uses eye-tracking and machine learning to help with early screening for Autism Spectrum Disorder (ASD).

Full paper here: link.springer.com/chapter/10.1...

The effects of appearance and organization and information architecture on the continued intention to use MOOCs. Universal Access in the Information Society. Our new paper at doi.org/10.1007/s102...

A new contribution about automatic methods to generate local domain models in rich client applications!

www.sciencedirect.com/science/arti...

Very proud of our new research result! :D
link.springer.com/article/10.1...

PlangRec is a character-level deep-learning model that predicts the language of a line of code. It provides 95% accuracy and macro F1-score to classify 21 different languages, outperforming state-of-the-art systems for classifying code snippets.
doi.org/10.1016/j.fu...

CLAVE is a one-shot deep-learning model for source code authorship verification. Contrastive learning is used to learn stylometric representations. CLAVE outperforms the state-of-the-art systems with 0.9782 AUC.
doi.org/10.1016/j.ip...