This work has spun out of academical research performed at Uppsala University:
Kristiaan Pelckmans (email@example.com) is Associate Professor in Applied Mathematics at Uppsala University, department of Information Technology, division of Systems and Control. He specialises in fundamental research on automatic control, machine learning and different applications of those. This emerged from working at different places, including Leuven (KUL, BE), Fraunhofer (Darmstadt, DE), London (UCL, UK) and shorter term visits (see cv2018). Recently, he is working on a research endeavour in astronomy (called VASCO) combining astrophysics, IT and ML and citizen science. Curiously enough, this effort shares many similarities with the FaDO project.
Dragos Dancila (firstname.lastname@example.org) is Associate Professor at Uppsala University, department of Engineering Sciences, division of Solid State Electronics. He received also a Complementary Master in Management, from the Solvay Business School in Brussels. He holds several patents in the fields of medical diagnostics and energy efficiency. He was project leader in several projects related to antennas, sensors, microwaves and terahertz technology. He is presently the Principal Investigator of a H2020 Eurostars project on energy efficiency in radio frequency amplifiers for cyclotron technology. Recently, he started working on applications of ML and AI for ‘Predictive maintenance’, which is the continuous surveillance of industrial equipment for pre-emptive maintenance, i.e. to act before things actually break down. He has strong interests in entrepreneurship, strategy and innovation in high-tech companies.
Erik Gudmundson (email@example.com, Ph.D.) is a scientist at FOI, Swedish Defence Research Agency. His work focuses on statistical signal processing for underwater applications. Examples of such applications are direction-of-arrival and range estimation for sonar systems, general estimation theory, and non-linear filtering and tracking. Recently, he has also started working on applications of ML and AI for identification of underwater sound sources. Erik Gudmundson has a Ph.D. in statistical signal processing from Uppsala University under supervision of prof. Peter Stoica. Before joining FOI, he held a post-doc positions at both Lund University and KTH Royal Institute of Technology, Stockholm.