Research
Selected research projects at the intersection of AI, scientific communication, NLP, and digital media.
Selected Work
2026
Personal ProjectAn NLP and Computer Vision study of emotional bias in speech-driven facial animation benchmarks
Sole researcher
This project investigates a key limitation of speech-driven facial animation: the reliance on phonetically balanced datasets that lack emotional diversity. It introduces cinematic dialogue as a stress test, comparing VOCASET with a curated Disney Cinematic Corpus and extending the analysis to model expressiveness.
Research Focus
Current systems achieve accurate lip synchronization but limited emotional expressiveness, likely due to the neutral bias of training data.
Methods
Outputs
2026
Research Internship ProjectA two-stage framework for generating audience-adapted scientific narratives
EURECOM · Politecnico di Torino — Andrea Sillano, Pasquale Lisena, Raphaël Troncy, Tommaso Calò, Luigi De Russis
Lead developer — dataset construction, framework design, model fine-tuning, evaluation, and web application
SciTeller is a two-stage framework that transforms scientific papers into audience-adapted narratives by separating content planning (Splitter) from generation (Storyteller).
Research Focus
Existing systems generate generic summaries with limited control over audience adaptation and weak guarantees of faithfulness.
Methods
Outputs
Next
These projects connect the technical work behind the publications with broader experimentation in AI-generated storytelling, evaluation, and expressive media.