Dr. Bartosz Krawczyk
Bio: Bartosz Krawczyk is an assistant professor in the Department of Computer Science, Virginia Commonwealth University, USA, where he heads the Machine Learning and Stream Mining Lab. His research is focused on machine learning, ensemble learning, data streams, class imbalance, one-class classifiers, and interdisciplinary applications of these methods. He has authored 35+ international journal papers and 80+ contributions to conferences. Dr Krawczyk was awarded with numerous prestigious awards for his scientific achievements like IEEE Richard E. Merwin Scholarship and IEEE Outstanding Leadership among others. He served as a Guest Editor in four journal special issues and as a chair of ten special session and workshops. He is a member of Program Committee for over 40 international conferences and a reviewer for 30 journals.
Title: Learning from imbalanced data: current trends and future directions
Abstract: Despite more than two decades of continuous development learning from imbalanced data is still a focus of intense research. Starting as a problem of skewed distributions of binary problems, this topic evolved way beyond this conception. With the expansion of machine learning and data mining, combined with the arrival of big data era, we have gained a deeper insight into the nature of imbalanced learning, while at the same time facing new emerging challenges. This talk will discuss contemporary achievements in learning from imbalanced data, mainly in the context of classification problems. The nature of class imbalance will be analyzed, focusing on analyzing not only the disproportion among classes, but also other difficulties embedded in the nature of data. Special focus will be given to two challenging areas: multi-class imbalanced data and imbalanced data streams. The talk will also provide a discussion and suggestions concerning lines of future research in this field.
Dr. Dario Izzo
Bio: Dario Izzo is the scientific coordinator of the Advanced Concepts Team in the European Space Agency. Dario Izzo graduated as a Doctor of Aeronautical Engineering from the University Sapienza of Rome in 1999. He later took a second master in “Satellite Platforms” at the University of Cranfield in the UK and completed his Ph.D. in Mathematical Modelling in 2003 at the University Sapienza of Rome where he also taught classical mechanics and space flight mechanics in 2002-2003. In 2004, Dario Izzo moved to ESTEC in the Netherlands where he started a research fellowship in Mission Analysis during which he performed several studies on asteroid deflection, including the first design option of an interplanetary trajectory leading to the successfull deflection of MN2004 (later called Apophis) by means of the kinetic impactor concept. In 2008, he became the scientific coordinator of the Advanced Concepts team where he led studies in interplanetary trajectory design and artificial intelligence. He started the Global Trajectory Optimization Competitions (http://sophia.estec.esa.int/gtoc_portal/) events. He published more than 140 papers in journals and conferences. In 2013, Dario Izzo received the Humies Gold Medal (http://www.genetic-programming.org/combined.php) for his work on grand tours of the galilean moons and on 2014 he won the 8th edition of the Global Trajectory Optimization Competition, organized by NASA/JPL, leading a mixed team of ESA/JAXA scientists. In 2015 he started, with Joerg Muller, the ESA/ACT Kelvins platform (https://kelvins.esa.int/) where machine learning and algoritmic competitions are hosted on space specific problems and data.
Title: Machine Learning methods for Trajectory Design