more informationMore information: Notes Highlights in WCM | Benchmarking QA over Linked Data (QALD) | Research: semantic systems | DubLinked: Dublin Open Data Platform
Vanessa Lopez is a research scientist and manager - AI for Health and Social Care at IBM's Dublin Research Laboratory in Ireland.
My research interests are to investigate and envision technologies to better understand human needs and support us, as a society, to target complex problems in the health and social care domain. In particular using a combination of knowledge representation and semantics, natural language and learning technologies to capture, integrate, search and query diverse data, and apply it to solve real challenges, like for Integrated Care, to support the care of the most vulnerable citizens and to ultimately obtain better outcomes.
I am a research scientist at IBM's Dublin Research Laboratory in Ireland since 2012. Currently I am the team lead on a project for Program Integrity that uses healthcare policies to support detecting fraud, waste and abuse on claim data. Our previous research has been applied to envistion 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. We have delivered technology demostrators and cognitive capabilities for care management and urban data platforms, in particular:
- AI system to extract actionable knowledge for healthcare text policies to support Fraud, Waste and Abuse investigations on healthcare claims
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. By continuosly learning from the actual practise of care professionals based on this holistic semantic-picture, the system can present ranked 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)
Contextual search and QA: combine semantics and business rules to model the needs of individuals across the clinical and social care dimensions (e.g, conditions, symptoms, activities of daily living, care providers, safety net, etc.) and supporting users in querying and exploring information. In particular by answering user queries pose in natural language that require aggregating data across heterogeneous knowledge records and Web of Data sources (Projects: BlueLENS, QuerioDALI, Link2Outcome)
Urban data management: a platform for harnessing urban and web data as knowledge, thorugh 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, where 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. EU projects I was working on include Dot.Kom, AKT, OpenKnowledge, X-Media, SmartProducts and RADAR, on the topics of IR, query disambiguation, ontology augmentation and semantic search. Prior to that I worked at the European Space Agency (ESA) and graduated in 2002 at the Technical University of Madrid (UPM), with an intership in the AI department.
Google Scholar publications
Research Gate publications
Previous publications @KMi