Learn
Learn involves how to extract information from data that makes systems smart and adaptive or even autonomous. Since the generation and storage of data will often be distributed, there is a strong need for efficient distributed data analytics. A fundamental understanding of how machine learning algorithms extract information from data is still missing, and the impact of the data on the learning process and the resulting bias is hardly understood. This gives rise to questions concerning legal safeguards and the rule of law.
If you are interested in joining the working group, please feel free to contact the chair.
Aristides Gionis
Professor, Division of Theoretical Computer Science at KTH, Member of the Strategic Research Committee, Chair working group Learn, Main Supervisor: Dragons - Data-Driven Algorithms and Governance for Networked Societies, Digital Futures Faculty
argioni@kth.se
Martina Scolamiero
Assistant Professor, Department of Mathematics at KTH, Vice Chair Working group Learn, Digital Futures Faculty
+46 8 790 81 19scola@kth.se
Stefan Bauer
Assistant Professor at KTH EECS, Working group Learn, Co-PI: Data-driven cardiovascular assist devices, Former Co-PI: Seed funding for large grant proposals, Digital Futures Faculty
baue@kth.se
Jonas Beskow
Professor and Dep. Head of Division at Division of Speech, Music and Hearing at KTH, Working group Learn, Co-PI of research project Advanced Adaptive Intelligent Systems (AAIS), Digital Futures fellow, Digital Futures Faculty
+46 8 790 89 65beskow@kth.se
Henrik Boström
Professor, Division of Software and computer Systems at KTH, Working group Learn, Digital Futures fellow, Digital Futures Faculty
+46 8 790 43 06bostromh@kth.se
Pawel Herman
Associate Professor, Computer Science, Division of Computational Science and Technology at KTH EECS, Co-PI: Humanizing the Sustainable Smart City (HiSS), Former Co-supervisor: Intelligence through reasoning, Digital Futures Faculty
+46 8 790 65 13paherman@kth.se
Jaakko Hollmén
Senior lecturer, Department of Computer and Systems Sciences at Stockholm University, Working group Learn, Digital Futures Faculty
+46 8 16 16 91jaakko.hollmen@dsv.su.se
Anders Holst
Senior Research Scientist, Swedish Institute of Computer Science at RISE, Adjunct professor at KTH Royal Institute of Technology, Working group Learn, Digital Futures Faculty
+46 10 228 43 13anders.holst@ri.se
Iolanda Leite
Associate Professor, Department of Robotics, Perception and Learning at KTH, Working group Learn, PI: Advanced Adaptive Intelligent Systems (AAIS), Former Main supervisor: On The Feminist Design of Social Robots and Designing Robots For Young People, With Young People, Former Main supervisor: Designing Gamified Robot-Enhanced Interventions for Children with Neurodevelopmental Disorders, Digital Futures Faculty
iolanda@kth.se
Alexandre Proutiere
Professor, Division of Decision and Control Systems at KTH, Working group Learn, Co-PI of research project Data-Limited Learning of Complex Dynamical Systems, Digital Futures fellow, Digital Futures Faculty
+46 8 790 63 51alepro@kth.se
Kevin Smith
Associate Professor, Division of Computational Science and Technology at KTH, Working group Learn, Digital Futures Faculty
+46 8 790 64 37ksmith@kth.se
Liam Solus
Assistant Professor at KTH SCI, Working group Learn, Co-PI of project cAIMBER: Causal Artificial Intelligence for Human Mobility Behavior Analysis Using Trajectory Data, Digital Futures Faculty
+46 8 790 65 85solus@kth.se
Ming Xiao
Associate Professor, Division of ISE at KTH EECS, Working group Learn, Co-supervisor: SMART – Smart Predictive Maintenance for the Pharmaceutical Industry, Co-supervisor: Fast Distributed Learning based on Adaptive Gradient Coding with Convergence Guarantees, Former Main supervisor: Intelligent wireless communications and high-accuracy positioning systems, Digital Futures Faculty
+46 8 790 65 77mingx@kth.se
Ozan Öktem
Associate Professor at KTH, Co-PI of project Spatiotemporal reconstruction with learned deformations for earlier cancer detection via PET imaging
ozan@kth.se