Program
The conference will be moderated by Anna Pihl and Johannes Tralla.
The conference will be in Estonian with simultaneous translation into English.
The programme and list of speakers are to be updated
Program | 9. march
Ivo Fridolin is a Professor at the Department of Health Technologies, Tallinn University of Technology (TalTech), Coordinator of the Estonian IT Centre of Excellence EXCITE and CTO at Optofluid Technologies OÜ. He holds a PhD since 2003 from Linköping University in Sweden. His main research interests are in the field of bio-optical sensors for monitoring and early diagnosis of chronic disease. Prof. Fridolin has published more than 100 scientific papers and abstracts, has been an invited speaker at international events, and is the author of several patents and patent applications.
Linnar Viik is Chairman of the EIT Digital Cluster at the European Institute of Innovation and Technology, and has been advising governments on digital innovation since 1995, as well as being an active entrepreneur and investor. Linnar's presentation will touch upon the EU's pursuit of digital sovereignty and its implications for Estonia's digital development.
Yuri Belikov is a tenured professor of control systems modelling and head of the Nonlinear Systems Group at TalTech. His research focuses on various control problems in the energy sector.
Meelis Kull is an Associate Professor of Machine Learning at the Institute of Computer Science, University of Tartu. He leads the Machine Learning Research Group, which develops artificial intelligence's ability to know the limits of its knowledge and to express uncertainty when necessary, thereby making it a trusted partner. He is also a highly respected lecturer in machine learning and data science, and his courses have benefited over a thousand students.
Liina Kamm is a Senior Researcher at Cybernetica AS. For over a decade she has been researching ways to analyse data in a way that protects people's privacy. She was one of the first to show that secure collaborative computing can be used in supra-genomic association studies to ensure privacy, and is exploring how to make secure collaborative computing faster, more powerful and user-friendly.