基本信息
views: 25
![](https://originalfileserver.aminer.cn/sys/aminer/icon/show-trajectory.png)
Bio
Marco Spruit is Full Professor of Advanced Data Science in Population Health at the department of Public Health & Primary Care (PHEG) of the Faculty of Medicine (LUMC) and the Leiden Institute of Advanced Computer Science (LIACS) at the Faculty of Science (FWN) of Leiden University in the Netherlands. He is interested both in translating new algorithms to novel health applications as in implementing new insights from these novel applications into daily practices.
Marco’s strategic research objective is to establish an authoritative national infrastructure for Dutch Natural Language Processing and Machine Learning to democratise Data Science. He focuses in particular on the Population Health and Wellbeing domain in his Translational Data Science Lab.
Marco leads the research line Translational Data Science in Population Health at the Health Campus The Hague. This research line has three themes. First, in Data Engineering he investigates the further consolidation, standardisation and enrichment of the Extramural LUMC Academic Network (ELAN) data infrastructure, in line with national initiatives and in collaboration with his PHEG colleagues. Second, in Data Analytics he investigates Natural Language Processing and Machine Learning techniques for their suitability to answer current and novel types of translational research questions, especially from a democratising Data Science perspective, in collaboration with his LIACS colleagues. Third, in e-Health Implementation Marco designs and implements Data Science interventions through e-Health software solutions within the region in close collaboration with the Campus partners.
Until 2020 Marco worked as associate professor in the Natural Language Processing research group at the department of Information and Computing Sciences at Utrecht University, where he notably conducted numerous European-funded studies (OPERAM, SAF21, SMESEC, GEIGER, OPTICA) and nationally funded research projects (STRIMP, COVIDA). He participated in various leadership programmes and obtained academic qualifications such the Senior Research Qualification, Senior Teaching Qualification, and Ius Promovendi. From 2007-2018 he was an assistant professor Information Science, acting as the Information Science and Applied Data Science programmes manager for several years, among others.
From 2003-2007 Marco worked as a Ph.D. researcher in the Language Variation group of the Meertens Institute at the intersection of syntactic variation and dialectometry as a linguistic data scientist. In 2005 he notably received an Association for Literary and Linguistic Computing bursary award for his scientific work. Before 2003 he was active in industry for ten years as a Natural Language Processing and Big Data engineer at ZyLAB Europe B.V. and the Royal Dutch Navy, among others. In 1995 he graduated in Computational Linguistics at the University of Amsterdam.
Research Interests
Papers共 221 篇Author StatisticsCo-AuthorSimilar Experts
By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
Patternspp.100990, (2024)
SOCIO-ECONOMIC PLANNING SCIENCES (2024): 101837
Natural Language Processing Journalpp.100082, (2024)
BMC Health Services Researchno. 1 (2024): 1-1
Katharina Tabea Jungo,Michael J. Deml, Fabian Schalbetter,Jeanne Moor,Martin Feller, Renata Vidonscky Luethold,Corlina Johanna Alida Huibers,Bastiaan Theodoor Gerard Marie Sallevelt,Michiel C. Meulendijk,Marco Spruit,Matthias Schwenkglenks,Nicolas Rodondi,
BMC HEALTH SERVICES RESEARCHno. 1 (2024)
Rebecca Ferguson,Hassan Khosravi,Vitomir Kovanović,Olga Viberg,Ashish Aggarwal,Matthieu Brinkhuis,Simon Buckingham Shum, Lujie Karen Chen,Hendrik Drachsler, Valerie A. Guerrero, Michael Hanses,Caitlin Hayward,
Journal of learning Analyticsno. 2 (2023): 14-50
CoRR (2023): 352-363
Cited0Views0EIBibtex
0
0
Load More
Author Statistics
Co-Author
Co-Institution
D-Core
- 合作者
- 学生
- 导师
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn