Personal information

Biography

Natalia Mordvanyuk is currently a PhD candidate at the University of Girona, Girona, Spain, where she also works as a researcher. Her research interests include sequential pattern mining, time interval related pattern mining and machine learning fields.

Activities

Employment (1)

University of Girona: Girona, ES

2014 to present
Employment
Source: Self-asserted source
Natalia Mordvanyuk

Education and qualifications (4)

Universitat de Girona: Girona, Catalunya, ES

2016 to 2021 | Doctoral Programme in Technology
Education
Source: Self-asserted source
Natalia Mordvanyuk

Universitat Oberta de Catalunya: Barcelona, Catalunya, ES

2014 to 2016 | Master's degree in security of information and communication technologies
Education
Source: Self-asserted source
Natalia Mordvanyuk

Universitat de Girona: Girona, Catalunya, ES

2012 to 2014 | Computer Engineering
Education
Source: Self-asserted source
Natalia Mordvanyuk

Universitat de Girona: Girona, Catalunya, ES

2009 to 2012 | Technical Engineering in Management Computing
Education
Source: Self-asserted source
Natalia Mordvanyuk

Works (13)

TA4L: Efficient temporal abstraction of multivariate time series

Knowledge-Based Systems
2022 | Journal article
EID:

2-s2.0-85126578168

Part of ISSN: 09507051
Contributors: Mordvanyuk, N.; López, B.; Bifet, A.
Source: Self-asserted source
Natalia Mordvanyuk via Scopus - Elsevier

VEPRECO: Vertical databases with pre-pruning strategies and common candidate selection policies to fasten sequential pattern mining

Expert Systems with Applications
2022-10 | Journal article
Contributors: Natalia Mordvanyuk; Albert Bifet; Beatriz López
Source: check_circle
Crossref
grade
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vertTIRP: Robust and efficient vertical frequent time interval-related pattern mining

Expert Systems with Applications
2021 | Journal article
Part of ISSN: 0957-4174
Source: Self-asserted source
Natalia Mordvanyuk
grade
Preferred source (of 5)‎

Understanding affective behaviour from physiological signals: Feature learning versus pattern mining

2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS)
2021-06 | Conference paper
Source: Self-asserted source
Natalia Mordvanyuk
grade
Preferred source (of 2)‎

NOAH: SUPPORTING PREMATURE BABIES CARE WITH MOBILE PHONES

Unpublished
2019 | Conference poster
Source: Self-asserted source
Natalia Mordvanyuk

eXiT Research Group at the University of Girona: Artificial Intelligence and Machine Learning Applied to Medicine and Healthcare

̧opyright Herrera, F. et al.(eds.)(2018). XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018): 23-26 de octubre de 2018: Granada, España, p. 1273-1278
2018 | Conference paper
Source: Self-asserted source
Natalia Mordvanyuk

Knowledge representation and machine learning on wearable sensor data: a study on gait monitoring

Proceedings of the First International Conference on Data Science, E-learning and Information Systems
2018 | Conference paper
Source: Self-asserted source
Natalia Mordvanyuk

Knowledge representation and machine learning on wearable sensor data: A study on gait monitoring

ACM International Conference Proceeding Series
2018 | Conference paper
EID:

2-s2.0-85058174525

Contributors: López, B.; Pla, A.; Mordvanyuk, N.; Gay, P.
Source: Self-asserted source
Natalia Mordvanyuk via Scopus - Elsevier

PREDICTION OF HYPERGLYCAEMIA AND HYPOGLYCAEMIA EVENTS USING LONGITUDINAL DATA

DIABETES TECHNOLOGY & THERAPEUTICS
2018 | Conference paper
Source: Self-asserted source
Natalia Mordvanyuk

Bag-of-steps: Predicting lower-limb fracture rehabilitation length by weight loading analysis

Neurocomputing
2017 | Journal article
Source: Self-asserted source
Natalia Mordvanyuk
grade
Preferred source (of 3)‎

MATCHuP: An mhealth tool for children and young people health promotion

HEALTHINF 2017 - 10th International Conference on Health Informatics, Proceedings; Part of 10th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2017
2017 | Conference paper
EID:

2-s2.0-85051741066

Contributors: López, B.; Soung, S.; Mordvanyuk, N.; Pla, A.; Gay, P.; López-Bermejo, A.
Source: Self-asserted source
Natalia Mordvanyuk via Scopus - Elsevier

Negative results for the prediction of postprandial hypoglycemias from insulin intakes and carbohydrates: analysis and comparison with simulated data.

Artificial Intelligence for Diabetes (AID)
2017 | Conference paper
Source: Self-asserted source
Natalia Mordvanyuk

Prediction of Glucose Level Conditions from Sequential Data

Frontiers in Artificial Intelligence and Applications
2017 | Conference paper
Source: Self-asserted source
Natalia Mordvanyuk
grade
Preferred source (of 2)‎