Adj/Prof Hanna Suominen, with over 15 years’ experience in longitudinal, multimodal data analytics for saving, structuring, and summarising data, is bridging the gap between Computer Science (CS) and health/social sciences. Her MSc was awarded in applied mathematics, PhD in CS, and Adj/Prof in CS in the University of Turku, Finland in 2005, 2009, and 2013, respectively. She joined The Australian National University as a Senior Lecturer and Data61 as the Team Leader of TAMPA, Theory and Applications of Multimodal Pattern Analysis within the Machine Learning (ML) Group after working in Data61/NICTA as a Team Leader of Natural Language Processing (NLP) and Senior Researcher in ML. Hanna has over 100 publications with 60 co-authors from 10 countries, including Harvard, Karolinska Institutet, and Max Planck. Her work has been published in the most prestigious journals, cited over 1,000 times, and awarded for best papers, ML/NLP-methods, business-plans, and teaching-units. She has scored competitive grants with a total value of over $11 million.
Adj/Prof Hanna J Suominen develops and evaluates Statistical Machine Learning methods for Text Analytics and Health. Please do not hesitate to contact her for research collaboration or summer/long/honours/masters/doctors projects.
Hanna has 100+ 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).
Hanna has been shortlisted to the top 15 per cent in the 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. 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.