Area |
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Data Science / Knowledge Discovery from Databases Artificial Intelligence and Intelligent Systems |
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Domain of specialization |
Research interests |
Application Domains |
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Sequential pattern mining Temporal data mining |
Feature Engineering Ethical Concerns Data Science Engineering |
Temporal data Healthcare Energy Education |
Cláudia Antunes has concluded her PhD in the data science domain, known as machine learning and data mining at the time. She proposed new methods and methodologies for dealing with temporal data, in particular for mining event sequential patterns. In her thesis, she argued that “It is possible to efficiently use constrained sequential pattern mining algorithms over nominal temporal data to discover unknown information, keeping the process centered on the user.” For proving her claim, she introduced the concept of constraint relaxation and proposed methods for mining frequent patterns in the presence of domain knowledge, represented as a context-free language.
Along time, Cláudia has kept her focus on two major directions: dealing with temporal
data and incorporating domain knowledge into the discovery process. These interests materialized
on the exploration of feature engineering as a natural way to explore both of them in the
classification process.
The continuous challenges faced by data science industry led Cláudia to address the field
from an engineering perspective, in particular from a computer science and engineering one.
On top of all, data science plays one of the most important roles in digital transformation, and
consequently its responsabilities are huge. Ethical concerns and efficient but clear ways to deal
with them are mandatory.
| 2019-2022 | VizBig
Project funded by FCT, under the grant PTDC/CCI-CIF/28939/2017 Consortium between IST-ID, INESC-ID and WEBDETAILS - CONSULTING, led by Prof. Daniel Gonçalves (INESC-ID) |
| 2019-2022 | GameCourse -
Project funded by FCT, under the grant PTDC/CCI-CIF/30754/2017 Consortium between IST-ID, INESC-ID and INSTITUTO DE EDUCAÇÃO DA UNIVERSIDADE DE LISBOA, led by Prof. Daniel Gonçalves (INESC-ID) |
| 2011-2014 | D2PM - Domain Driven Pattern Mining
Scientific coordinator Project funded by FCT, under the grant PTDC/EIA-EIA/110074/2009 |
| 2011-2014 | educare - visualization and mining of behavior models in education
Scientific coordinator Project funded by FCT, under the grant PTDC/EIA-EIA/110058/2009 Consortium between IST-ID and INESC-ID |
| 2010-2012 | EuDML - The European Digital Mathematics Library Project funded by the European Commission (CIP-ICT-PSP.2009.2.4) led by Prof. José Borbinha |
| 2008-2009 | TELplus Project funded by the European Commission under the eContentplus Program (ECP-2006-DILI-510003) led by Prof. José Borbinha |