About

I am an AI Engineering director supervising various AI initiative at Algolia, starting with our flagship product AI Search. Before that, I led the engineering work behind the Algolia Recommend product and I oversaw our discovery initiatives. I joined Algolia because I wanted to address AI challenges at the root (inside the search or recommendation engines) while before that, I used to work on top of providers like Elasticsearch or Solr. The broad variety of customers and their use cases is what drive me most currently, as they are fantastic challenges to be solved with AI.

Past TL;DR
Lead Machine Learning Engineer at Doctrine, Paris, a blooming French Legaltech startup. I focused on search and recommendation to always propose users the most relevant documents. I loved tackling the challenges of dealing with Legalese and fulfilling user needs in such a specific domain.

Postdoctoral Visiting Fellow in Zhiyong Lu‘s Biomedical Text Mining group at the National Center for Biotechnology Information of the National Institutes of Health, Bethesda, USA. I was privileged to be able to work on PubMed and PubMed Labs search engines — the latter became the new PubMed since then. My work there focused on improving the systems by providing more accurate query answers through a better understanding of queries, documents and relevance. This work has impacted the experience of the millions of users PubMed welcomes every day.

Collaboration during my free time with Moreno Mitrović on topics related to computational linguistics.

PhD student in the LGI2P lab of IMT Mines Alès, France. I happened to work with the MAB team of the LIRMM at Montpellier, on phylogenetics and evolution. On these topics, I also worked with the Ensembl team of the European Bioinformatics Institute on genomic alignments.

Research interests

  • machine learning
  • information retrieval
  • recommender systems
  • deep learning
  • text mining
  • natural language processing

Academia

talk
2020.
Chavallard, P., Fiorini, N.. Searching the Law: a Doctrine case study. ECIR 2020, Springer.
conference talk talk
2019.
Fiorini, N.. Find Relevant Cases in All Cases: Your Journey at Doctrine. Proceedings of the 42nd International ACM SIGIR, ACM.
conference
2019.
Sayers, E., Agarwala, R., Bolton, E., Brister, J. et al.. Database Resources of the National Center for Biotechnology Information. Nucleic Acid Research.
journal
2018.
Fiorini, N., Leaman, R., Lipman, D.J., Lu, Z. How user intelligence is improving PubMed. Nature Biotechnology.
journal
2018.
Fiorini, N., Canese, K., Bryzgunov, R., Radetska, I. et al. PubMed Labs: An experimental system for improving biomedical literature search. Database (Oxford).
journal
2018.
Fiorini, N., Canese, K., Starchenko, G., Kireev, E. et al. Best Match: new relevance search for PubMed. PLoS Biology.
journal talk
2018.
Fiorini, N., Lu, Z. Personalized neural language models for real-world query auto completion. Proceedings of the 2018 conference of NAACL-HLT, ACL.
conference
2018.
AI & IR. Doctrine.
talk
2018.
PubMed search and PubMed Labs. Elsevier.
talk
2018.
Mohan, S., Fiorini, N., Kim, S., Lu, Z. A Fast Deep Learning Model for Textual Relevance in Biomedical Information Retrieval. Proceedings of the 27th WWW conference.
conference award
2017.
Anekalla, K.R., Courneya, J.P., Fiorini, N., Lever, J. et al. PubRunner: A light-weight framework for updating text mining results. F1000 research, Hackathon collection.
journal
2017.
Fiorini, N., Lipman, D.J., Lu, Z. Towards PubMed 2.0. eLife.
journal
2017.
Special Act or Service Group Award for the development of PubMed Labs. NLM.
award
2017.
Kim, S., Fiorini, N., Wilbur, W.J, Lu, Z. Bridging the gap: incorporating a semantic similarity measure for effectively mapping PubMed queries to documents. Journal of Biomedical Informatics, Elsevier.
journal
2017.
Mohan, S., Fiorini, N., Kim, S., Lu, Z. Deep Learning for Biomedical Information Retrieval: Learning Textual Relevance from Limited Click Logs. Proceedings of the 2017 ACL Workshop on BioNLP.
conference
2017.
PubMed Labs: A Sandbox Toward PubMed 2.0. Pi Day, NIH.
talk
2016.
Fiorini, N., Harispe, S., Ranwez, S., Montmain, J. et al. Fast and reliable inference of semantic clusters. Knowledge-Based Systems, Elsevier.
journal
2016.
Medjkoune, M., Harispe, S., Montmain, J., Cariou, S., Fanlo, J.-L., Fiorini, N. Towards a Non-oriented Approach for the Evaluation of Odor Quality. Proceedings of IPMU 2016, Springer.
conference
2015.
Intelligent machines that help humans face huge data. University of Graz.
talk
2015.
Fiorini, N., Ranwez, S., Harispe, S., Montmain, J., and Ranwez, V. USI at BioASQ 2015: a Semantic Similarity-Based Approach for Semantic Indexing. CLEF, CEUR Workshop Proceedings.
conference
2015.
Fiorini, N., Ranwez, S. Montmain, J., Ranwez, V. USI: a fast and accurate approach for conceptual document annotation. BMC Bioinformatics.
journal
2015.
Fiorini, N., Harispe, S., Ranwez, S. Montmain, J., Ranwez, V. Annotation sémantique de clusters. Proceedings of ROADEF.
conference
2014.
Fiorini, N., Lefort, V., Chevenet, F., Berry, V. et al. CompPhy: a web-based Collaborative Platform for Comparing Phylogenies. BMC Evolutionary Biology.
journal
2014.
Fiorini, N., Ranwez, S., Ranwez, V. and Montmain, J. Indexation conceptuelle par propagation. Application à un corpus d’articles scientifiques liés au cancer. Proceedings of CORIA.
conference
2014.
Fiorini, N., Ranwez, S., Montmain, J. and Ranwez, V. Coping with imprecision during a semi-automatic conceptual indexing process. Proceedings of IPMU 2014, Springer.
conference

Resume

April 2024 - Present

Senior Engineering Director
Algolia
Project: Algolia AI Search

Sept 2022 - March 2024

Engineering Director
Algolia
Project: Algolia Discovery

Sept 2021 - Sept 2022

Engineering Manager
Algolia
Project: Algolia Recommend

May 2021 - Aug 2021

Lead Machine Learning Engineer
Algolia
Project: recommendation & search

Jan 2021 - Apr 2021

Senior Machine Learning Engineer
Algolia
Project: recommendation & search

I joined Algolia

Bringing AI in search.
Then pivoted to Recommender systems.
Then again to AI search.

April 2019 - Dec 2020

Lead Machine Learning Engineer
Doctrine
Project: recommendation & search

January 2019 - March 2019

Senior Machine Learning Engineer
Doctrine
Project: search relevance

I joined Doctrine

Working on French legal information
retrieval and recommendation

January 2016 - January 2019

Postdoctoral Visiting Fellow
NCBI - NLM - NIH
Project: improvement of PubMed search

October 2012 - November 2015

PhD Student researcher
IMT Mines Alès
Project: semantic indexing and clustering

November 2015

PhD in Computer Science
University of Montpellier, France

March 2008 - September 2012

Self-Employee
Freelancer in web technologies and data-mining

September 2012

MSc in Bioinformatics
University of Montpellier, France

March 2012 - August 2012

Research Intern
EBI
Project: genome fragment phylogenies

July 2010

BSc in Biology
University of Marseille, France