September 2026
New Position at 
Principled Intelligence!
Rome, Italy
Started a new position as Senior AI Engineer at Principled Intelligence.
# Scroll to show info. def get_info(ro: RiccardoOrlando) -> str: return ro.basic_info() print(get_info(riccardo))
// Scroll to show info. public String getInfo(RiccardoOrlando ro) { return ro.basicInfo(); } System.out.println(getInfo(riccardo));
$ Riccardo Orlando Senior AI Engineer @ Principled Intelligence, Rome → github scholar cv
Computer Scientist
/ AI Researcher.
About
Hi, I'm Riccardo Orlando, Computer Scientist and AI Researcher. I build language technology that works at scale: from multilingual semantic pipelines to large language models trained from scratch.
Currently
Senior AI Engineer at Principled Intelligence, in Rome.
01 / WorkNow.
Sep. 2026 – Now
Senior AI Engineer · Principled Intelligence
Rome, Italy
02 / UpdatesNews.
New Position at
March 2025
New Position at 
DIME AI!
World Bank Group, Rome, Italy
Started a new position as AI Researcher at DIME AI.
December 2024
Minerva 7B Released!
Sapienza University of Rome, Italy
Public release of the Minerva 7B (base and instruct) model.
August 2024
ReLiK Code and Models Released!
Sapienza University of Rome, Italy
Public release of the code and models for ReLiK, our system for Entity Linking and Relation Extraction.
May 2024
ReLiK Paper Accepted at ACL 2024!
Sapienza University of Rome, Italy
Our paper "ReLiK: Retrieve and LinK, Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget" has been accepted at ACL 2024.
May 2024
Minerva LLM Family Released!
Sapienza University of Rome, Italy
Public release of the Minerva models (350M, 1B, 3B), the first family of Large Language Models (LLMs) trained from scratch on Italian (and English) data.
03 / ResearchPublications.
May 2026
Predicting Causal Effects from Natural Language Queries using Structured Representations
arXiv preprint, 2026
November 2025
RAED: Retrieval-Augmented Entity Description Generation for Emerging Entity Linking and Disambiguation
In Proceedings of EMNLP, 2025
November 2024
ZEBRA: Zero-Shot Example-Based Retrieval Augmentation for Commonsense Question Answering
In Proceedings of EMNLP, 2024
September 2024
Minerva LLMs: The First Family of Large Language Models Trained from Scratch on Italian Data
In CLiC-it, 2024
August 2024
ReLiK: Retrieve and LinK, Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget
In Findings of ACL, 2024
June 2024
MOSAICo: a Multilingual Open-text Semantically Annotated Interlinked Corpus
In Proceedings of NAACL, 2024
July 2023
Exploring Non-Verbal Predicates in Semantic Role Labeling: Challenges and Opportunities
In Findings of ACL, 2023
November 2022
Universal Semantic Annotator
In European Language Grid. Springer, Cham, 2023
June 2022
Universal Semantic Annotator: the First Unified API for WSD, SRL and Semantic Parsing
In Proceedings of LREC, 2022
November 2021
AMuSE-WSD: An All-in-one Multilingual System for Easy Word Sense Disambiguation
In Proceedings of EMNLP, 2021
November 2021
InVeRo-XL: Making Cross-Lingual Semantic Role Labeling Accessible with Intelligible Verbs and Roles
In Proceedings of EMNLP, 2021
04 / Experience & EducationPast.
Mar. 2025 – Aug. 2026
Researcher · World Bank Group
Rome, Italy
Built ZeroHungerAI's LLM extraction system from the ground up: training data, models, evaluation benchmark, and the inference setup that runs it across 150 million news articles. Also built the retrieval and agentic parts of ImpactAI's meta-analysis pipeline, plus the RCT benchmark used to evaluate retrieval, and got it into production.
Nov. 2021 – Jan. 2025
PhD · Sapienza NLP Group
Sapienza University of Rome, Italy
PhD in Natural Language Processing and Deep Learning at the Sapienza NLP group of Sapienza University of Rome.
Feb. 2021 – Dec. 2021
2018 – 2020
Master of Science in Engineering in Computer Science
Sapienza University of Rome, Italy
Thesis title: An automatic approach to produce multilingual training data for Semantic Role Labelling.
Grade: 110/110 with honours
Mar. 2018 – Sep. 2018
Software Engineer · Capgemini
Rome, Italy
Included in a team that worked to re-platform a series of internal applications of an insurance company. Worked as a software engineer mainly on the backend but also contributed to the frontend.
2015 – 2018
Bachelor of Computer Science
Sapienza University of Rome, Italy
Thesis title: Densest subgraph in Fork/Join.
05 / Open SourcePersonal projects.
llama-trainer
A "just few lines of code" utility for fine-tuning (not only) Llama models.
transformers-embedder
A Word Level Transformer layer based on PyTorch and 🤗 Transformers.
nlp-template
A template to initialize PyTorch projects that use PyTorch Lightning as a backbone framework.
ner-serve
Simple multilingual NER model serving using Docker, FastAPI, ONNX and Multilingual Mini-LM.
transformer-srl
Reimplementation of a BERT based model (Shi et al, 2019), currently the state-of-the-art for English SRL. Also implements predicate disambiguation.
chinese-word-segmentation
Chinese Word Segmentation based on BERT, implemented in PyTorch for state-of-the-art Chinese word segmentation.
ml-malware-classifier
Three classifiers trained to distinguish malware applications from non-malware ones and recognize the family they belong to.
densest-subgraph-fork-join
Bachelor's thesis. A Fork/Join parallel algorithm for the densest subgraph problem.
fork-join-sudoku-solver
Solver that uses the Fork/Join framework to solve Sudoku in parallel, made during a multi-core programming course.