Marco Ponza

Marco Ponza

PhD, Senior AI Research Engineer

Bloomberg LP

Biography

Opinions are my own.

I am a senior AI research engineer at Bloomberg LP, working on their financial search engine where I build software systems based on machine learning (ML).

I have experience in designing and developing ML systems for the classification and ranking of news stories. This involves the ML system in its whole lifecycle - data analysis, collection, annotation, model training and evaluation, as well as its deployment (and maintainance) in an existing production infrastructure which serves millions of requests per day.

I worked on automating our ML development pipeline through different and reusable software components that are currently used by different teams.

I also have experience in documenting, debugging, fixing, and migrating legacy systems into modern software services/libraries.

Prior to joining Bloomberg I was a PhD student at the University of Pisa. During my PhD studies I worked in the domain of information retrieval and I published different research works on entity relatedness, entity salience, fact salience, and expert finding.

I am a former member of the A³ Lab at the University of Pisa, and an ex-research intern at Max Planck Institute for Informatics.

During my spare time I enjoy traveling, taking photos, watching movies, cooking, and reading.

Publications

(2021). Contextualizing Trending Entities in News Stories. In the Proceedings of the 14th International Conference on Web Search and Data Mining (WSDM 2021). Full paper, acceptance rate 18.6%.

PDF Dataset Poster Slides Video DOI

(2019). SWAT: A System for Detecting Salient Wikipedia Entities in Texts. Computational Intelligence, Wiley-Blackwell Publishing. Journal paper, impact factor 0.77.

PDF Project DOI

(2018). Facts That Matter. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018). Short paper, acceptance rate 23.2%.

PDF Code Poster DOI

(2018). Algorithms for Knowledge and Information Extraction in Text with Wikipedia. PhD Dissertation, University of Pisa. Defended on 08/03/2019.

PDF Slides

(2017). A Two-Stage Framework for Computing Entity Relatedness in Wikipedia. Proceedings of the Conference on Information and Knowledge Managements (CIKM 2017). Full paper, acceptance rate 20%.

PDF Code Dataset Poster Slides DOI

(2017). Document Aboutness via Sophisticated Syntactic and Semantic Features. International Conference on Applications of Natural Language to Information Systems (NLDB 2017). Full paper, acceptance rate 17%.

PDF Project Slides DOI

Education

 
 
 
 
 

PhD in Computer Science

Department of Computer Science, University of Pisa

Oct 2015 – Oct 2018 Pisa, Italy
 
 
 
 
 

MSc in Computer Science

Department of Computer Science, University of Pisa

Oct 2011 – Jul 2015 Pisa, Italy
 
 
 
 
 

BSc in Computer Science

Department of Computer Science, University of Pisa

Sep 2008 – Dec 2011 Pisa, Italy

Experience

 
 
 
 
 

Senior AI Research Engineer

Bloomberg LP

Mar 2023 – Present London, United Kingdoom
 
 
 
 
 

AI Research Engineer

Bloomberg LP

May 2020 – Feb 2023 London, United Kingdoom
 
 
 
 
 

Research Intern

Bloomberg LP

Sep 2019 – Apr 2020 London, United Kingdoom
 
 
 
 
 

Postdoctoral Researcher

Department of Computer Science, University of Pisa

Dec 2018 – Sep 2019 Pisa, Italy
 
 
 
 
 

Teaching Assistant

Master in Big Data Analytics & Social Mining, University of Pisa

Jan 2018 – Aug 2018 Pisa, Italy
 
 
 
 
 

Research Intern

Max Planck Institute for Informatics

Aug 2017 – Feb 2018 Saarbrücken, Germany
 
 
 
 
 

Teaching Assistant

Department of Physics, University of Pisa

Oct 2015 – Jun 2017 Pisa, Italy

Awards

SIGIR Student Travel Grant

Student travel grant for CIKM 2017.

Pegaso Doctorate Scholarship

Three-years funding and stipend awarded for young researchers.

Activities

Talks