The Chinese University of Hong Kong
Kernel-based approaches in system identification
Tianshi Chen: Tianshi Chen was born on November 17, 1978, in Heilongjiang, China. He received his Ph.D. degree in Automation and Computer-Aided Engineering from The Chinese University of Hong Kong in December 2008. From April 2009 to December 2015, he was working in the Division of Automatic Control, Department of Electrical Engineering, Linköping University, Linköping, Sweden, first as a Postdoc (April 2009–March 2011) and then as an Assistant Professor (April 2011–December 2015). In December 2015, he returned to China and joined the Chinese University of Hong Kong, Shenzhen, as an Associate Professor.
His research interests are in the field of system identification, machine learning, and automatic control. In the past decade, he has been mainly working in the area of kernel-based regularized system identification and has published in this area over 20 journal papers in peer reviewed international journals. He is/was an Associate Editor for Automatica (2017–present), System & Control Letters (2017–2020), and IEEE Control System Society Conference Editorial Board (2016–2019). In May 2015, he received the Youth Talents Award of the Thousand Talents Plan of China.
Uppsala University, Sweden
Machine learning and dynamic models
Thomas B. Schön is the Beijer Professor Artificial Intelligence in the Department of Information Technology at Uppsala University. He received the PhD degree in Automatic Control in Feb. 2006, the MSc degree in Applied Physics and Electrical Engineering in Sep. 2001, the BSc degree in Business Administration and Economics in Jan. 2001, all from Linköping University. He has held visiting positions with the University of Cambridge (UK), the University of Newcastle (Australia) and Universidad Técnica Federico Santa María (Valparaíso, Chile). In 2018, he was elected to The Royal Swedish Academy of Engineering Sciences (IVA) and The Royal Society of Sciences at Uppsala. He received the Tage Erlander prize for natural sciences and technology in 2017 and the Arnberg prize in 2016, both awarded by the Royal Swedish Academy of Sciences (KVA). He was awarded the Automatica Best Paper Prize in 2014, and in 2013 he received the best PhD thesis award by The European Association for Signal Processing. He received the best teacher award at the Institute of Technology, Linköping University in 2009. He is a Senior member of the IEEE and a fellow of the ELLIS society.
ABB Corporate Research Västerås, Sweden
An industrial perspective on learning models for decision and control
Alf Isaksson received an MSc in Computer Engineering and a PhD in Automatic Control, in 1983 and 1988 respectively, both from Linköping University, Sweden. After graduating he stayed at Linköping University until 1991 as an Assistant Professor. From 1991 to 1992 he spent one year as a Research Associate at The University of Newcastle, Australia. Returning to Sweden in 1992 Isaksson moved to the Royal Institute of Technology (KTH) in Stockholm, where eventually in 1999 he was promoted to full Professor.
In 2001 he made the shift from academic to industrial research and joined ABB Corporate Research in Västerås, Sweden. After a specialist career culminating in an appointment to Corporate Research Fellow in 2009, he from 2012 – July 2020 had multiple positions responsible for managing research inside ABB. For example from 2014-2019 he was funding and coordinating all Control research globally in ABB. He is now since August 2020 Corporate Research Fellow for Automation and Control.
University of Cambridge, UK
University of California, USA
Applications of machine learning of dynamic systems
Mihaela van der Schaar is the John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge, a Fellow at The Alan Turing Institute in London, and a Chancellor’s Professor at UCLA.
Mihaela was elected IEEE Fellow in 2009. She has received numerous awards, including the Oon Prize on Preventative Medicine from the University of Cambridge (2018), a National Science Foundation CAREER Award (2004), 3 IBM Faculty Awards, the IBM Exploratory Stream Analytics Innovation Award, the Philips Make a Difference Award and several best paper awards, including the IEEE Darlington Award.
Mihaela’s work has also led to 35 USA patents (many widely cited and adopted in standards) and 45+ contributions to international standards for which she received 3 International ISO (International Organization for Standardization) Awards.
In 2019, she was identified by National Endowment for Science, Technology and the Arts as the most-cited female AI researcher in the UK. She was also elected as a 2019 “Star in Computer Networking and Communications” by N²Women. Her research expertise spans signal and image processing, communication networks, network science, multimedia, game theory, distributed systems, machine learning and AI.
Mihaela’s research focus is on machine learning, AI and operations research for healthcare and medicine.