Dr. Georgiana Ifrim is an Assistant Professor in the School of Computer Science, University College Dublin, and an SFI Funded Investigator with the Insight Centre for Data Analytics, Ireland. She holds a PhD (2009) and MSc (2005) in Computer Science (research area: Machine Learning), from Max-Planck Institute for Informatics, Germany and a BSc (2003) in Computer Science from University of Bucharest, Romania. Until 2014, Dr. Ifrim held a senior research fellow position with the Insight Centre for Data Analytics, University College Dublin, Ireland. Prior to that, she held postdoctoral positions with the Cork Constraint Computation Centre (2013), Ireland, and the Bioinformatics Research Centre (2010), Denmark.
Dr. Ifrim's research focuses on scalable machine learning and data mining, in particular, large scale sequence learning, time series forecasting and information extraction/retrieval. She has worked in application domains ranging from Web mining, news and social media, energy and biology. Her current research interests include scalable sequence learning and real-time prediction for streaming data.
Learning from Massive News and Social Streams for Digital Journalism
Connecting news and Twitter conversations (TKDE17, WWW16, ECML16, ECML14)
Twitter-Topics: Twitter Event Detection (SNOW@WWW14 Data Challenge, twitter-topics)
SEQL: Sequence Learner (KDD11, seql-v2.0.tar.gz). General learning framework for discriminative sequence/string classification. Includes regularized SLR and linear SVM.
SLR: Structured Logistic Regression (KDD08, please use SEQL, it extends SLR and is better maintained). Fast Logistic Regression for Text Categorization: learning phrase-classifiers (ngram-classifiers) with variable-length phrases (ngrams).