The program of this event has two parts and you may participate in one or both of them. Please save the date, for this is a discussion you don’t want to miss!
PART ONE 9.00–12.00 Data Science for Social Good
Follow the morning programme in Unitube
You will learn about how the research in data science tackle real world problems and improve public services.
• What is MyData and how does it affect your life?
• How is the modern data research methodologies applied to detect social media deviations?
• What are the possibilities of data science to be used for the social good?
• What else are you interested in finding out about the topics of the presentations?
Please join the event and ask! The program will be consisting of real-life application examples of data science.
9.00 Opening Speech
Sasu Tarkoma, Director of HiDATA, University of Helsinki
9.15 Key Note: Data Science for Social Good - An Industry Perspective
Dipanjan Saha, Associate Vice President, Cognizant
10.00 Elements of AI
Janina Fagerlund, Reaktor
10.30 What Is MyDATA and How Does It Affect Your Life?
Karolina Mackiewicz & Ansku Tuomainen, MyData Global
11.00 Investigating Illegal Wildlife Trade from Social Media and Other Digital Platforms
Enrico di Minin, Helsinki Lab of Interdisciplinary Conservation Science, Department of Geosciences and Geography, University of Helsinki.
11.30 The Internet of Fake Things
Antti Ukkonen, Academy Research Fellow at the Department of Computer Science, University of Helsinki
Moderator: Patrik Floréen, Vice-Director of HiDATA
12.00–13.00 LUNCH BREAK
PART TWO 13.00–15.00 Introduction of new HiDATA professors
Follow the afternoon programme in Unitube
• You will learn about current HiDATA activities.
• What are the newly appointed professors going to focus on?
• What is their research about and how they are going to contribute on data science research?
The presentations are open for discussion. Come and find out more and please contribute to the discussion.
13.00 Exploratory search and interactive information retrieval
Dorota Glowacka, Assistant Professor, Data Science - Machine Learning and AI
13.30 How do we know if AI is right? Challenges in the testing of AI systems
Jukka K. Nurminen, Professor, Data-Intensive Computing in Natural Sciences
14.00 Getting Your Genome Together: Algorithmic Genomics Research in Helsinki
Simon Puglisi, Associate professor
14.30 Pervasive Data Science: Sensing for Science
Petteri Nurmi, Associate professor, Distributed Systems and Internet of Things
Moderator: Keijo Heljanko, Professor, Vice-Director of HiDATA
The program is in two sessions and you may participate in one or both of them. The event is in English.
There is no entrance fee, but but we have only 200 seats available, so please register as soon as possible!
Please register by 21 May here.
If you cannot join the event, you will find live streaming and recording at Unitube.
Helsinki Centre for Data Science (HiDATA) is a world-class hub of Data Science in Helsinki and it builds on the pioneering scientific results of the community and paves way for new breakthrough results across disciplines. The overarching goal of HiDATA is to leverage the synergies of the network in solving significant societal and industrial challenges related to data analysis. HiDATA is a joint hub of the two participating universities, the University of Helsinki and Aalto University, and it is supported by the Academy of Finland.
Sasu Tarkoma is a 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.
Dipanjan Saha, currently Associate Vice President at Cognizant, has more than two decades of rich experience in strategy and operations with global consulting majors. He has deep expertise in high performance enterprise solutions, value architectures and large, complex digital transformations. He has played Enterprise Architect role in platform development, business workflow, process and cognitive automation, data analytics and On-Demand Service Utility models. He is a frequent speaker at top engineering, business schools and at NASSCOM and IEEE. He holds a Bachelor of Technology Degree and an MBA from the renowned Indian Institute of Technology.
Anna “Ansku” Tuomainen is the communications lead for the non-profit MyData Global and the MyData 2019 conference. She is passionate about conveying and spreading the vision of a fairer future of personal data management. Her mission is to advance the personal data literacy and further the MyData concept education. Ansku is fascinated about finding ways to help people understand complex ideas by means of storification.
Karolina Mackiewicz works as the Events Lead and Project Manager for MyData 2019 Conference at MyData Global - an international non-profit, which advocates for equal data sharing, based in Helsinki. Her professional mission is to bring people together to network and collaborate for creating actionable solutions for MyData materialization and implementation. Simply speaking, she wants to make the world a better place by contributing to building the more just and sustainable society.
Dr. Enrico Di Minin is a researcher at the Department of Geosciences and Geography, University of Helsinki, where he leads the Helsinki Lab of Interdisciplinary Conservation Science (https://www.helsinki.fi/en/researchgroups/helsinki-lab-of-interdisciplin...). He recently received a European Research Council Starting Grant to investigate illegal wildlife trade from digital platforms. His research background and expertise are relevant to investigate the interactions among biosphere, society and economy, which affect sustainability. He has specific interests in land use planning; spatio-temporal modelling; environmental economics, and how to apply machine learning methods in conservation science. He addresses these topics by using cross-disciplinary research and big data.
Antti Ukkonen is an Academy Research Fellow at the Department of Computer Science, University of Helsinki. He leads two research projects funded by Academy of Finland about data science and AI. Antti’s current research interests mainly concern applications of machine learning in the context of natural language processing and understanding. Prior to joining University of Helsinki, Antti has worked at Yahoo! Research, Helsinki Institute for Information Technology HIIT, and Finnish Institute for Occupational health. He obtained his doctoral degree in the field of Computer Science from Aalto University in 2008.
Patrik Floréen, PhD, is University Lecturer in Computer Science at University of Helsinki. His research interests are in intelligent information retrieval and context-aware computing. He is Vice-Director of Helsinki Institute for Information Technology HIIT, Vice-Director of Helsinki Centre for Data Science HiDATA, and member of the management team of the Finnish Center for Artificial Intelligence FCAI. He has previously been a director at the Academy of Finland (1995-97) and a Scientific Officer at the European Commission in Brussels (1997-2001).
Dorota Glowacka is Assistant Professor of Artificial Intelligence and Machine Learning in the Department of Computer Science, University of Helsinki. She obtained a PhD in Machine Learning from University College London, UK, after which she spent 6 years as a researcher in the Helsinki Institute for Information Technology and one year as an Assistant Professor in the School of Informatics, University of Edinburgh. Her research interests are in interactive information retrieval, user modelling, and applied machine learning.
Jukka K. Nurminen started as a professor of computer science at the University of Helsinki in spring 2019. He has worked extensively on software research in industry at Nokia Research Center, in academia at Aalto University, and in applied research at VTT. His key research contributions are on energy-efficient software as well as mobile peer-to-peer and cloud solutions but his experience ranges widely from applied optimization to AI, from network planning tools to mobile apps, and from software project management to tens of patented inventions. He received his MSc degree in 1986 and PhD degree in 2003 from Helsinki University of Technology (now Aalto University). Currently his main interests are tools and techniques for developing data-intensive software systems including testing of AI solutions, computational moral, and software development for quantum computers.
Simon J. Puglisi is an Associate Professor and Academy Research Fellow in the Department of Computer Science at the University of Helsinki. Prior to arriving in Helsinki he spent two years as a Newton International Fellow at King's College London, and earlier still held an Australian Postdoctoral Fellowship in the Search Engine Group at the Royal Melbourne Institute of Technology. His research focuses on Algorithms and Data Structures for efficiently storing, searching, and manipulating large quantities of data, and applications of these tools to problems in Bioinformatics, Search Engines, and Database Systems. Outside of research, he likes May, June, July, and August. September can be okay.
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.
Keijo Heljanko is a Professor of Parallel and Distributed Data Science at University of Helsinki and Vice-Director of Helsinki Centre for Data Science (HiDATA), a world-class hub of Data Science in Helsinki. His research topics include Big Data, Parallel and Distributed Computing, Distributed Systems, and Verification Methods for Parallel Software.