SARA C. MADEIRA is an Associate Professor with tenure at Department of Informatics of Faculdade de Ciências, Universidade de Lisboa, since February 2017, where she teaches courses on Data Mining, Machine Learning, Foundations of Data Science, and Introduction to Research in Data Science. She is also a Senior Researcher at FCiencias-ID/LASIGE, where she coordinates the Data and Systems Intelligence and is a member of Health and Biomedical Informatics Research Line of Excellence. From May 2018 to January 2022 she further coordinated the Data Science graduation at FCUL. She was awarded the Scientific Prize Universidade de Lisboa/Caixa Geral de Depósitos 2021 in the area of Computer Science and Engineering, and was awarded the Best Runner-Up Outreach Initiative 2020 by LASIGE. She received her PhD degree in Computer Science and Engineering at Instituto Superior Técnico, Universidade Técnica de Lisboa (Técnico) in December 2008, her MSc degree in Computer Science and Engineering at Técnico in 2002, and graduated in Matemática-Informática at Universidade da Beira Interior, in 2000. She was a Lecturer at the Informatics Department of UBI, from November 2002-December 2008, while being a PhD student at Técnico, and hired as an Assistant Professor after finishing her PhD in December 2008. From June 2009-February 2017 she was an Assistant Professor at the Computer Science and Engineering department at Técnico, where she taught undergraduation courses on algorithms and data structures and programming, and graduation courses on computational biology and integrative bioinformatics. She was also a senior researcher at INESC-ID, Lisbon, where she received the INESC-ID Young Research Award in 2013. From March 2015 to July 2016, she was on sabbatical leave at the Biocomputing group - University of Bologna and an EURIAS Junior Fellow at the Istituti di Studi Avanzate in Bologna from September 2015-June 2016. She co-chaired the 14th and 15th International Workshops on Data Mining in Bioinformatics (BIOKDD'15 and BIOKDD'16), held in conjunction with ACM SIGKDD '15 and SIGKDD'16. Her research interests are in the broad area of data science and include machine learning, bioinformatics and health informatics. In this context, she was the PI of NEUROCLINOMICS - Understanding NEUROdegenerative diseases through CLINical and OMICS data (PTDC/EIA-EIA/111239/2009), and NEUROCLINOMICS2 - Unravelling Prognostic Markers in NEUROdegenerative diseases through CLINical and OMICS data integration (PTDC/EEI-SII/1937/2014). Following these projects, she is now the PI of AIpALS - Advanced learnIng models using Patient profiles and disease progression patterns for prognostic prediction in ALS (PTDC/CCI-CIF/4613/2020). She further participated and participates in several other national research projects in bioinformatics and data science topics and is now leading FCiencias-ID/LASIGE team in H2020 Project CIRCLES - Controlling mIcRobiomes CircuLations for bEtter food Systems (Grant agreement ID: 818290) and H2020 Project BRAINTEASER - BRinging Artificial INTelligencE home for a better cAre of amyotrophic lateral sclerosis and multiple SclERosis (Grant agreement ID: 101017598). Her 2004 paper "Biclustering Algorithms for Biological Data Analysis: a Survey" on ACM/IEEE TCBB, considered an ESI Hot Paper in Computer Science in 11/2006, has now more than 2500 citations. Biclustering and triclustering algorithms together with their applications in biomedical data analysis are still her main research topics. She proposed state of the art biclustering algorithms based on efficient string processing and mining techniques, in the case of biclustering temporal data, and pattern mining algorithms, in the general case of biclustering tabular and network data, and co-authored the paper "Triclustering Algorithms for Three-Dimensional Data Analysis: A Comprehensive survey" published in the end of 2018 in ACM Computing Surveys. She further made relevant contributions in the area of prognostic prediction using machine learning in neurodegenerative diseases, in particular Amyotrophic Lateral Sclerosis (ALS) and Alzheimer’s Disease (AD).

Machine Learning. Data Science. Bioinformatics. Biomedical Informatics, Health Informatics.

Machine Learning. Data Science. Bioinformatics. Biomedical Informatics, Health Informatics.

2021-12-31 - Prémios Científicos Universidade de Lisboa/Caixa Geral de Depósitos (Caixa Geral de Depósitos)

2020-12-31 - Best Runner-up Outreach Initiative (LASIGE)

2020-12-31 - Menções honrosas dos Prémios Científicos Universidade de Lisboa/Caixa Geral de Depósitos (Caixa Geral de Depósitos)

2016-12-31 - Menções honrosas dos Prémios Científicos Universidade de Lisboa/Caixa Geral de Depósitos (Caixa Geral de Depósitos)

2013-12-31 - Best Young Researcher (Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento em Lisboa (INESC-ID))

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