About Christina Igasto
Research Interests
The research fields that Christina has found most interesting over the years are image analysis and computerised decision support systems for Real-Life applications. Image analysis is an interdisciplinary subject, involving areas such as signal processing, sensor physics, multi variate statistics, mathematics, numerical analysis, intelligent computing and cognitive science. Add to this the dimension of the application area within which the image analysis is to be performed -- medicine, process industry, robotics, surveying, security, military to mention only a few -- and the complexity of the subject becomes apparent.
Christina started her Master's thesis "Automatic Determination of Mammogram Adequacy" in 2002 at the Department of Computing Science Umeå University, and her research was, during that period, oriented towards medical image analysis and problems and challenges involved in developing methods for medical decision making applications. Christina’s Ph.D.-student research project resulted in a Licentiate thesis "Automatic Assessment of Mammogram Adequacy" 2005, followed by a PhD thesis "Towards Automatic Image Analysis for Computerised Mammography" in 2008. Over the years, Christina’s research interests have turned from more application specific issues to rather general problems for decision support and real-life applications.
During the last couple of years Christina has found additional work areas such as research management and research projects responsibilities very interesting. Christina is structured, organized and finds it appealing to develop activities and people in their work. Therefore part of her post doc position involves project coordination and she is also part of the rather large research group Cloud and Grid Computing. Through Christina’s involvement in Cloud and Grid Computing questions her involvement in UMIT Research Lab becomes natural.
Teaching
Since 2004 Christina has been responsible for mainly two courses Artificial Intelligence and Image Analysis and involved in several courses from basic to advanced level at the Department of Computing Science at Umeå University. She has also been student advisor on a number of courses, such as for instance Pattern Classification. For details see Teaching. To strengthen the education-research connection, Christina has used many of her research problems in her teaching. This becomes natural since Christina’s research interests involve artificial intelligence, image analysis and pattern classification methods. In addition, Christina’s has also supervised several theses at the Master's level from both Physics and Computing Science, all which were associated to her research.
