Speakers

Johanna Laiho-Kauranne 

Dr Johanna Laiho-Kauranne is a Data Governance Lead at CSC - IT Center for Science Ltd Finland, and doctoral researcher at Social Data Sciences Center, University of Helsinki. She promotes new solutions on data strategies, promotion of Open Science and FAIR principles, digitalization and sustainability powered with data analytics and AI, sustainability and advances in survey methodologies.

Johanna’s previous work experience entails developing AI and data analytics solutions at DAIN Studios, and leadership of the official statistical system as Deputy Director General at Statistics Finland 2020-2022 responsible for unifying and modernizing production of official statistics and promoting the use of experimental statistics. Prior to that Johanna worked as Director of Statistics and Vice President for the Natural Resources Institute Finland (Luke) 2015-2020, bridging between statistics and research. She acted as Director of Agricultural statistics 2009-2014 modernizing agricultural statistics, and as Senior Advisor of Statistical Methods and Quality at Statistics Finland 2001-2008 and Senior Researcher at National Centre for Social research (NatCen, UK) 1999-2000 and as Senior Statistician for Social surveys at Statistics Finland 1996-1999.

Johanna has Master’s degree in Statistics from the University of Helsinki 1996; and Ph.D. in Social statistics from the University of Southampton 2007. 

She is a member of the Scientific Advisory Board of Statistics Sweden, elected member of the ISI and a member of Research Data Alliance.

Li-Chun Zhang

Li-Chun Zhang is Professor of Social Statistics at the University of Southampton and Senior Researcher at Statistics Norway. He has worked and published on topics such as machine learning, graph sampling, population size estimation, finite population sampling and coordination, sample survey estimation, nonresponse and missing data, measurement errors, small area estimation, index number calculations, editing and imputation, register-based statistics, statistical matching, record linkage, analysis of integrated data. He has been involved in the EU framework projects EURAREA, DACSEIS, RISQ and BLUE-ETS, the ESSnet projects Small Area Estimation, Data Integration and Quality of Multisource Statistics, Mobile Network Operator Methods for Integrating New Data Sources, the H2020-project InGRID-2, the ESRC-projects ADRCE and NCRM-SAE.   

Gustaf Strandell

Methodologist at Statistics Sweden with a keen interest for natural language processing and machine learning.

Jacob Kasche

Methodologist at the Department of Data and member of Statistics Sweden’s Machine Learning Group.

Krista Lagus 

Prof., Dr(Tech). Krista Lagus is a distinguished academic and researcher in artificial intelligence (AI), natural language processing (NLP), and machine learning. She currently serves as a Professor of Digital Social Science at the University of Helsinki, where she integrates AI and digital methods with social sciences to analyze complex social behaviors.

Lagus obtained her MSc in Computer Science in 1996 and a Ph.D. in Computer and Information Sciences in 2000 from Helsinki University of Technology (now Aalto University). She continued as a Researcher and Lecturing Researcher to 2006, followed by appointment as an Academy Research Fellow at the Finnish Academy of Sciences from 2006 to 2012, and as a Senior Researcher to 2014. In 2015, she joined the University of Helsinki as a Researcher and was appointed as a Professor at the Faculty of Social Sciences in 2017. In 2019, she co-founded the Center for Social Data Science (CSDS) and became its first director. She was involved with establishing EIT ICT Labs as its Helsinki Education Coordinator in 2011 and Schools and Camps Lead in 2012. She is a frequent reviewer in publications, grants and academic appointments related to AI and NLP. In particular, in 2021 she served as a reviewer for grants at the ERC Cog SH3 panel. 

Lagus has led and contributed to several key projects, including WEBSOM, a method for visualizing large text collections using self-organizing maps; Citizen Mindscapes, which examines digital communication to gauge public opinion and societal trends; and Morfessor, an algorithm for unsupervised morphological analysis, utilized nowadays widely in NLP and also for modeling linguistic processes in the brain. Her publications have appeared in leading journals such as Neural Networks, Information Retrieval Journal, and IEEE Transactions on Neural Networks and Learning Systems. Her extensive and well-cited publication record makes her one of the key figures in the field. 

In addition to her research, Lagus teaches and guides students and early-career researchers in AI and digital social science e.g. in the Contemporary Societies Master's Programme. Her current work emphasizes advancing interdisciplinary research, national infrastructure development, and education that leverages AI for societal benefit.

Maria Valaste 

Dr Maria Valaste is a senior university lecturer in the Centre for social data science at the University of Helsinki. Her main scientific research is in microsimulation, survey methodology and the analysis of complex survey data. Previously she worked as a senior researcher at the Social Insurance Institution of Finland (KELA), focusing on register based research and data analysis, survey methodology and microsimulation.

Maria has Master’s degree in Statistics from the University of Helsinki 2004 and Ph.D. in Social statistics from the University of Helsinki 2015. She holds a docent in applied statistics (2017, University of Helsinki, Faculty of Social Sciences).

Currently she is a member of the research projects "Dariah-FI - Network for Data-Intensive Social Science and Humanities Research" and "Datalit - Data literacy for responsible decision-making", funded by the Academy of Finland. She and is a member of the Steering Committee of the BNU - Baltic-Nordic-Ukrainian network on Survey Statistics and elected member of the ISI.

Adeline Clarke

Adeline Clarke is a Project Planner at the Centre for Social Data Science at the University of Helsinki. Since 2023 she has worked on building finnsurveytext which is an R package used for analysing responses to open-ended survey questions. The finnsurveytext project is part of DARIAH-FI which is a research infrastructure project for Social Sciences and Humanities (SSH) in Finland.

Prior to living in Finland, Adeline worked as a Data Scientist for the Aged Care Quality and Safety Commission which is the agency in charge of the regulation of aged care in Australia. Adeline has Bachelor degrees in Political Science, Economics, and Mathematics, and a Master of Data Science. Adeline is motivated by how Data Science and computational methods can be meaningfully applied in the Social Sciences to enable research, and in policy to improve social outcomes.