Vanessa Lopez Garcia


Vanessa Lopez Garcia


Senior Research Scientist and Manager, AI for Health and Social Care


IBM Research Europe - Ireland Dublin, Ireland


Vanessa Lopez is a senior researcher scientist at IBM Research Ireland since 2012 and manager of the AI for Health and Social Care team.

My research interests are to investigate how technology can be made “smarter” to better understand human needs, and support us, as a society, to target complex problems. My research looks at semantics and knowledge graph representations to enhance NLP and learning technologies, applied to assist human experts, from protecting healthcare programs integrity, reducing disparities and improving the delivery of care for the most vulnerable , to most recently, using knowledge to enhance accelerated scientific discovery, to help experts reduce the search space of possible candidate solutions.

Research Experience

We look at technologies that can leverage existing, background knowledge from diverse and multimodal sources, and create computable knowledge representations that can be used in various downstream tasks, for example, to build predictive and generative models for candidate solution generation. This research can be applied, for example, for drug discovery, to use existent rich multimodal knowledge to enhanced learned protein and molecule knowledge representations ; or to find relevant features to accelerate clinical trials, for example to improve cohort diversity and engagement.

Our previous research has been applied to envision and develop applications in the Social and Health care domain, to support care professionals to take better informed decisions, and received various awards, including the 2017 US-Ireland Innovation from the American Chamber of Commerce Ireland and the Royal Irish Academy. Past projects include:

  • Team lead of a project for Program Integrity that uses healthcare policies to accelerate the creation of human and machine consumable healthcare policies, to support detecting fraud, waste and abuse on healthcare claim data.
  • Cognitive analytics for patient-centric care: to support care professionals in capturing and interpreting the right information about an individual to take better informed decisions, based on structured and unstructured health records, as well as external open data and knowledge graphs. The system could capture highlights extracted from patients' case notes, identify missing information and / or actionable insights to ultimately obtain better outcomes for citizens (Projects: Notes Highlights for WCM, Cognitive Care Mentor)
  • QA over knowledge graphs: to support users in querying and exploring information, in particular by answering user queries pose in natural language, which required aggregating data across heterogeneous knowledge records and Web of Data sources and/or patient (Projects: BlueLENS, QuerioDALI, Link2Outcome)
  • Urban data management: a platform for harnessing urban and web data as knowledge, through a combination of semantic lifting and integration of tabular data and metadata coming from cities into knowledge graphs, as well as providing novel contextual & retrieval services on top for: spatial and semantic search, thematic exploration and linking data into multiple views, by making semantic connections across entities in different data sources explicit, in response to user needs (Projects: DALI, QuerioCity).

Before IBM, I was a research associate and a part-time PhD at KMi, Open University (2003-2011), where I got my doctorate. I was the project champion and main developer of AquaLog and PowerAqua, pioneering prototypes for Natural Language interfaces for the Semantic Web / Linked Data, published in in major international journals and conferences, and participated in various EU projects on the topics of IR, query disambiguation, ontology augmentation and semantic search. Prior to that I worked at the European Space Agency (ESA) (2002-2003) and graduated in 2002 (M.Sc) at the Technical University of Madrid (UPM) (1996-2002), where I carried out an internship as part of the AI department.

Google Scholar publications
Research Gate publications
Previous publications @KMi LinkedIn




Accelerating clinical trials.png

Accelerating clinical trials

Developing AI and analytics to understand the drivers of study or clinical trial efficiency.
  • Natural Language Processing
  • Machine Learning
  • Knowledge and Reasoning
  • Healthcare
  • Accelerated Discovery
  • Foundation Models

Knowledge enhanced accelerated discovery

Enhance scientific discovery with multimmodal knowledge
  • Accelerated Discovery

Top collaborators

Lam Hoang

Lam Hoang

Research Staff Member, data mining