Experience
Education
Bio
Adj/Prof Hanna J Suominen received her PhD in Computer Science and MSc in Applied Mathematics (includes BS) in the University of Turku in Turku, Finland in 2009 and 2005, respectively. Her PhD dissertation was approved with honours of belonging to the ten percent elite of the field internationally. Her MSc dissertation was commissioned by the national Turku PET Centre. She develops and evaluates Statistical Machine Learning methods for Text Analytics and Health. She works as a Senior Researcher in the NICTA Machine Learning Research Group in Canberra, Australia and is an Adjunct Professor of Computer Science in the University of Turku at the Department of Information Technology. She also holds an Adjunct Research Fellowship (Level C) in the Australian National University at the College of Engineering and Computer Science and is a Professional Associate in the University of Canberra at the Faculty of Health. She joined NICTA as a Researcher after working as a Turku Centre for Computer Science (TUCS) Graduate Research Assistant, Coordinator, and Lecturer in the University of Turku. Her most important research visits include the Microsoft Research Cambridge in the UK, Austrian Institute of Technology (AIT), and University of California, San Diego, USA. Hanna has about seventy peer-reviewed papers with over sixty co-authors from ten countries, including, for example, the US Harvard University, Swedish Karolinska Institutet University, and German Max Planck Institute. She considers the following co-authored papers as her three most important publications: Benchmarking clinical speech recognition and information extraction: New data, methods and evaluations (JMIR Medical Informatics 2015, Impact Factor 4.669), Capturing patient information at nursing shift changes: Methodological evaluation of speech recognition and information extraction (Journal of the American Medical Informatics Association 2014, Impact Factor 3.932), and Overview of the ShARe/CLEF eHealth EvaluationLab 2013 (Lecture Notes in Computer Science 2013). She has been shortlisted to the top 15 per cent in the L’Oréal AU&NZ Women in Science in 2013, belonged within the top teams in two health language technology challenges in 2007-2011, and won two best paper awards in 2006 and 2007. Her research interests are developing and evaluating methods and applications of Machine Learning, Mathematical Modelling, and Natural Language Processing. Adj/Prof Suominen is or has been a member of the Australasian Language Technology Association (ALTA), Health Informatics Society of Australia (HISA), Health text Analysis network in the Nordic and Baltic countries (HEXAnord), and Information and Language Technology for Health Information and Communication consortium (IKITIK). She is a Co-Chair/Task-Leader of the ShARe/CLEF eHealth Evaluation Labs and Assistant/Guest Editor for the Artificial Intelligence in Medicine and Journal of Pattern Recognition Research. She is a Reviewer for the Journal of American Medical Informatics Association, Journal of Biomedical Informatics, International Journal of Medical Informatics, and many other top journals and conferences of her field. She has won a best business-plan award and several competitive research and commercialisation grants for both herself and her team. Her teaching has been rated as excellent by both students and staff in 2012 and 2013.