AI Researcher

Applied AI for efficient LLMs.

Hi, I’m Elia — an Applied AI Researcher and fourth-year PhD candidate at the University of Trento, with experience across academia and industry.

My research focuses on model compression, pruning, sparsity, data curation, and post-training for large language models.

Elia Cunegatti smiling

01 Model compression

02 Efficient LLMs

03 Post-training

Presented at EMNLP 2026

Latest work

All publications
EMNLP 2026 · Findings 01

From Layers to Submodules: Rethinking Granularity in Replacement-Based LLM Compression

Submodule-level compression with lightweight fitted residual bypasses.

EMNLP 2026 · Main 02

Frequency Matters: Fast Model-Agnostic Data Curation for Pruning and Quantization

Fast, Zipf-inspired calibration data selection for model compression.

Now · Turin, Italy

Amazon

Post-training at Alexa AI.

I am currently an Applied Scientist Intern at Amazon in Turin, working with Alexa AI on post-training.

Apr–Jun 2026 · Seville, Spain

Bristol Myers Squibb

From papers to biomedical discovery.

Between April and June 2026, I joined Bristol Myers Squibb (CITRE) in Seville as a Visiting Scientist. I worked with Dr. Santiago Egea Gomez and Dr. Hannah Pliner on generating gene regulatory networks from scientific literature using large language models.

Since 2022 · Trento, Italy

Università di Trento

PhD student at the University of Trento.

I have been a PhD student in Computer Science at the University of Trento since 2022, researching efficient deep learning, model compression, pruning, and sparsity.