Get REAL, AI!

"I work on probabilistic machine learning, meaning probabilistic modelling and Bayesian inference, applied to difficult problems that are interesting and societally important. At the moment I work on the inter-related topics of analysis of multiple data sources, human-in-the-loop machine learning, simulator-based inference (likelihood-free inference with ABC), and privacy-preserving learning. I have had the chance to collaborate with amazing people in interdisciplinary research projects on applications in biology and medicine, brain signal analysis and user interaction (see list of publications), and in the Aalto Probabilistic Machine Learning Group which I lead with Prof. Aki Vehtari, and the Finnish Center of Excellence in Computational Inference Research which I lead until end of 2017.

To further boost the already strong artificial intelligence research and its impact, we are setting up a new Finnish Artificial Intelligence Center FCAI, which I will lead 2018-. It is a partnership of Aalto University, University of Helsinki, and a number of company members, networking further to key international and national partners. We aim to solve three bottleneck questions in AI research: data scarcity, dependability of AI, and ability of AI to understand its users (more details here). The research will be done with company partners, including new startups and spin-offs, which will take the results directly to use. We will also pay special attention to AI education."

Teemu Roos is the leader of the Information, Complexity and Learning (ICL) research group. He is also affiliated with the Academy of Finland funded Centre of Excellence COIN.

Topics of his interest include the theory and applications of machine learning and big data, probabilistic graphical models, information theory and digital humanities.

Dr. Nidhi Singh is Director of Research at Elisa Corporation in Helsinki. Prior to joining Elisa, she worked with Fortune 500 as well as mid-sized companies for over 16 years in various R&D and leadership roles. Her focus has been on applying AI and machine learning for solving complex, large-scale IT problems in domains like intelligent automation of customer services, online fraud detection in e-commerce, and energy optimisation for data centres. She received her Ph.D in computer science, and has been a reviewer for a number of premier AI conferences and journals.

Dr. Milica Todorović runs the machine learning research projects of the Computational Electronic Structure Theory (CEST) group at Aalto University. The group, led. by Prof. Patrick Rinke, interfaces machine learning algorithms with quantum mechanical simulations of materials with the aim to optimise material functionality.

Dr. Todorović moved from Serbia to the UK to study physics at University College London, then she took a DPhil in Materials Science from Merton College at the University of Oxford in 2008. She went on to specialise in development and HPC applications of large-scale first principles calculations at the National Institute for Materials Science (Japan) and Universidad Autonoma de Madrid (Spain). She joined the CEST group at Aalto University in 2015.