HiDATA Event on 4 March 2020: From Complex Data to Well-being

March 4 2020
Tiedekulma - Think Corner (Yliopistonkatu 4)

Helsinki Centre for Data Science HiDATA and Helsinki Insititute of Life Science HiLIFE organise a joint event together with Finnish Centre for Artificial Intelligence FCAI about data and wellbeing. Come and find out the many ways we can use data science for wellbeing.



9:00 Programme starts @stage:


10:45 Time for your questions. Please notice that we take all questions after all the presentations.

11:00 End of programme. Time to mingle.

About the speakers:

Sasu Tarkoma is Professor of Computer Science at the University of Helsinki and Head of the Department of Computer Science. He is also Director of the Helsinki Center for Data Science and affiliated with the Helsinki Institute for Information Technology HIIT and the Finnish Center for AI (FCAI).  He is chairman of the Finnish Scientific Advisory Board for Defence (MATINE). He has authored 4 textbooks and has published over 200 scientific articles.  He has seven granted US Patents. His research has received a number of Best Paper awards and mentions, for example at IEEE PerCom, ACM CCR, and ACM OSR. As an example flagship research project, he is leading the MegaSense project, which aims at deploying a wide array of low-cost urban air-monitoring stations and employing the data in prediction models.

Nadia Tamminen is working as Senior Advisor in Pharma Industry Finland. The possibility to use data is bringing new possibilities to the life science and pharmaceutical industry. In my work I have been following how the Finnish environment has developed and opened the data for scientific research. With the data we can understand more how diseases act and how new innovations are benefitting our society. With increasing competitiveness we expect to see more investments and more research to Finland.



Professor Ville Mustonen, University of Helsinki:  "I work at the Organismal and Evolutionary Biology Research Programme, Department of Computer Science, Institute of Biotechnology and Helsinki Institute for Information Technology (HIIT).  After completing a doctorate in statistical physics, (DPhil 2005, University of Oxford, UK) I started to explore biological data. I first worked at the University of Cologne, Germany, for five years and then lead my own research group at the Wellcome Sanger Institute, Cambridge, UK, for seven years. I develop evolutionary theory and its applications to solve problems such as drug resistance. In particular, I try to understand how predictable evolution is and how and to what extent evolving populations can be controlled. We also develop bioinformatic algorithms needed to analyse big biological data sets. Our work is basic science that can lead to applications relevant to human health, for example, in the context of cancer and infectious disease and evolution of drug resistance. My group works collaboratively and across different scientific disciplines. We have a record of successful research collaborations working together with clinicians and experimentalists."

Antti Honkela is an Associate Professor of Data Science at the University of Helsinki. He is the coordinating professor for the Finnish Center for AI (FCAI) research programme in privacy-preserving and secure AI. Prior to his current position he was an Assistant Professor of Statistics with joint appointment between the Faculty of Science and Faculty of Medicine, University of Helsinki. Antti is an expert in privacy and data anonymisation. He servers as an expert in the steering group of Findata, the recently established Finnish Health and Social Data Permit Authority. His research interests include privacy-preserving machine learning, differential privacy and probabilistic inference as well as their applications in computational biology and health.


Jarno Vanhatalo is an assistant professor of statistics working both in the Department of Mathematics and Statistics (Faculty of Science) and Organismal and Evolutionary Biology Research Program (Faculty of Biological and Environmental Sciences). He leads Environmental and Ecological Statistics group and is one of the PIs in the Research Center for Ecological Change. His research interests span from Bayesian statistics and machine learning to environmental and ecological sciences.


Petteri Nurmi is an Associate Professor in Distributed Systems and Internet of Things in the Department of Computer Science at University of Helsinki since September 2018. At the University of Helsinki, he currently leads the Pervasive Data Science research group. He received his MSc in Computer Science in 2006 from University of Helsinki and his Doctor of Philosophy in 2009 from University of Helsinki, Finland. Prior to his current position, he worked as Lecturer in Foundations of Pervasive Data Science at Lancaster University, UK.