Luis Gasco

Luis Gasco

NLP Research Engineer

Barcelona Supercomputing Center

Biography

Luis Gasco is currently a Senior Machine Learning Engineer at Avature, where he leverages language technologies and artificial intelligence to enhance recruitment processes. Formerly, he was a Research Engineer at the NLP4BIA Research Group from Barcelona Supercomputing Center. His research interests encompass a multidisciplinary approach, where he explores Natural Language Processing (NLP) techniques, Entity Linking, and Large Language Models (LLMs) applied to the fields of human resources, healthcare, environmental studies, and urban management. He received the Outstanding Doctoral Thesis Award from UPM, was recognized as the Best Young Researcher at Internoise 2019, and delivered the best doctoral presentation at the “Tell Your Thesis in 4 minutes” symposium. He was one of the ten doctoral students selected to join the EIT Digital Doctoral School in Spain’s 2020 cohort, where he received training in innovation management and technology transfer. Additionally, he conducted research visits at Telecom Paris and the renowned Nokia Bell Labs in Cambridge (UK). He was been involved in several large-scale research projects including the DataTools4Heart Horizon Europe project, AI4HF, biomatdb, TeresIA, and PlanTL. He has also co-organized multiple tasks in community evaluation efforts, including SSM4H (SocialDisNER, ProfNER), BioASQ (Mesinesp, Distemist, and Medprocner), and BioCreative (Drugprot and Symptemist).

Interests
  • Natural Language Processing
  • Data Science
  • Artificial Intelligence
  • Information Retrieval
  • Large Language Models
Education
  • PhD Certification in Innovation and Entrepreneurship, 2020

    European Institute of Innovation and Technology

  • PhD in Engineering, 2019

    Universidad Politécnica de Madrid

  • Master in Business Intelligence and Big Data, 2016

    Escuela de Organización Industrial

  • MSc in Acoustic Engineering in Industry and Transport, 2014

    Universidad Politécnica de Madrid

  • BSc in Sound and Image (Telecom) Engineering, 2013

    Universidad Politécnica de Madrid

Projects

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TalentCLEF

TalentCLEF

TalentCLEF is an initiative to advance Natural Language Processing (NLP) in Human Capital Management (HCM). It aims to create a public benchmark for model evaluation and promote collaboration to develop fair, multilingual, and flexible systems that improve Human Resources (HR) practices across different industries.

Deepspanorm

Deepspanorm

A framework with resources for the normalization of clinical entities to controlled terminologies developed for use in Spanish but adaptable to other languages.

SciLinker

SciLinker

An app to assist the creation of entity linking corpora .

REECapi

REECapi

This package provides a list of functions to facilitate access to the data offered by Registro Español de Estudios Clínicos in its REST API.

Open Noise Monitoring Network

Open Noise Monitoring Network

An innitiative to unify the collection of noise monitoring data

OpenSkyR

OpenSkyR

A R package that provides a list of functions to facilitate access to the data offered by OpenSky-Network..

Noytext

Noytext

An applitation to facilitate annotation of short texts

Experience

 
 
 
 
 
Avature
Senior Machine Learning Engineer
February 2024 – Present Spain

Working in the Machine Learning department at Avature, with a primary focus on developing multilingual Natural Language Processing (NLP) systems applied to Human Capital Management (HCM). Key contributions and responsibilities include:

  • Researching and developing advanced contextual entity linking (EL) systems to improve the extraction of key information from job descriptions, resumes, and HCM data. This research area focuses on exploring novel algorithms and methodologies to enhance the accuracy and efficiency of entity linking in multilingual and cross-industry contexts.
  • Collaborating in the deployment of models into production environments, ensuring their scalability and performance within Avature’s platform.
  • Developing methodologies for terminology enrichment, focused on expanding and refining controlled vocabularies to improve the accuracy and relevance of multilingual skill and competency representations.
  • Actively organizing and presenting results in shared-task challenges, conferences, and industry events, collaborating with experts and showcasing our innovations within the NLP field to researchers and students.
 
 
 
 
 
Universidad Complutense de Madrid
Lecturer
Universidad Complutense de Madrid
September 2020 – Present Madrid, Spain
  • Lecturer of the Text Mining and Social Networks modules in the Master Big Data and Business Analytics and the Master Data Science and Big Data of the Universidad Complutense de Madrid.
  • More than 600 students have been taught the basics of NLP techniques including data preprocessing, document representation and, text classification and topic modeling strategies.
 
 
 
 
 
Barcelona Supercomputing Center
Research Engineer
October 2020 – February 2024 Barcelona, Spain

Worked within Martin Krallinger’s research group with a primary focus on advancing the field of clinical Natural Language Processing (NLP) in the Spanish language. My work revolved around harnessing NLP systems to extract valuable biomedical insights from Electronic Health Records (EHRs) and emerging data sources, including online social networks. Key contributions and responsibilities included:

  • Development of neural entity linking systems for the Spanish language. These systems were designed to link biomedical mentions extracted from NERs to ontologies such as SNOMED-CT, ICD-10 or HPO, among others.
  • Played a key part in making Gold Standard datasets and creating clear rules for Named Entity Recognition (NER) and Entity Linking. This work helped make evaluation standards consistent in the field.
  • Actively participated in organizing and publishing results in shared-task challenges conducted within esteemed international conferences and workshops such as COLING, NAACL, CLEF, SEPLN, BioASQ, SMM4H, and IberLEF. These platforms served as valuable venues for showcasing our advancements and collaborating with fellow experts in the field.
  • Actively engaged in seeking research funding, which involved finding partners and writing grant proposals. This included applying for funding from European Union’s Horizon Program and the Spanish government’s PERTE initiative.
 
 
 
 
 
Atos Research and Development
Data Scientist
Atos Research and Development
November 2019 – May 2020 Madrid, Spain
  • Developed and integrated a suite of open-source data analysis tools to manage the machine learning lifecycle within the company’s IoT solution, the Urban Data Platform.
  • Utilized TensorFlow for training time series prediction models using sensor data from Mallorca airport and deployed these models on the platform.
  • Collaborated on business consulting tasks, including creating business models for technology transfer from European projects in Computer Vision and Edge Computing.
 
 
 
 
 
Nokia Bell Labs
Visiting Research Engineer
Nokia Bell Labs
July 2018 – October 2018 Cambridge, UK
  • Research stay at the Bell Labs, with 9 Nobel prizes, under the supervision of Daniele Quercia (Social Dynamics Department director), working withing one of the projects of the initiative goodcitylife.org, which seeks to solve urban problems using open data and AI.
  • I was involved in research activities focused on data mining of geographic social media and open data, and on the impact of noise on health in the city of London
 
 
 
 
 
Télécom Paris
Visiting Research Engineer
Télécom Paris
September 2017 – December 2017 Paris, France
  • Research stay in the S2A Team (Image, Data and Signal Department) under the supervision of Prof. Chloé Clavel working on topics related to opinion mining and NLP appied to detect attitudes to environmental noise written in Online Social Networks
  • Research activities focused on pre-processing twitter texts, feature extraction (part-of-speech, statistical features, sentiment features, and word embeddings), short-text classification models, and noise taxonomy creation (using WordNet and DBPedia)
 
 
 
 
 
Universidad Politécnica de Madrid
Researcher
Universidad Politécnica de Madrid
May 2013 – October 2019 Madrid, Spain
  • Developed text mining models for complaint detection and classification related to urban noise.
  • Analyzed urban data to create prediction models.
  • Designed open data-based platforms for visualizing environmental noise data.
  • Conducted statistical analysis of noise levels from smart city sensors and attitude surveys.
  • Researched noise data reporting methods in major cities and international airports (Europe, USA, Australia).
  • Implemented pattern recognition algorithms for aircraft identification software.
  • Collaborated on consultancy projects and various research initiatives.

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