Biography:

Daniel Sbarbaro got a degree in electrical engineering from the Universidad de Concepción, Concepción, Chile, in 1984, and a Ph.D. from Glasgow University, Glasgow, U.K., in 1993. He was an Alexander von Humbolt Fellow at the Control Engineering Laboratory, Ruhr University, Bochum, Germany, in 1998. He also held visiting research positions at the Daimler-Benz research institute, Berlin and at Stuttgart University in 1993 and 2009 respectively. Together with Prof. Rene del Villar from Laval University, Canada, he edited a book on “Advanced Control and Supervision of Mineral Processing Plants” published by Springer in 2010. He has co-authored more than 50 papers in international Journals and 90 papers in International Conferences.  He has graduated one PhD, ten masters and more than eighty undergraduate students. He has developed projects with the industry in the areas of technological benchmarking, economical assessment of control improvements, development of training programs, advanced control and data processing. He has also led several projects funded by Fondecyt and Innova in the areas of nonlinear control and sensor developments. He has been member of Fondecyt Engineering Committee and Engineering Committee of the Chilean Accreditation Board (CNA). He is IEEE senior member and member of ISA. He has been awarded the Concepción City Council applied research award and the Universidad de Concepcion academic excellence award.

He is currently a professor in the Department of Electrical Engineering, Universidad de Concepción. His current research interest includes design of observers for nonlinear systems and the development of technologies for improving people’s quality of life and the productivity of the main Chilean productive sectors.

Degrees: Ing. Civil Eléctrico, Universidad de Concepción, 1984.  Ph.D. Universidad de Glasgow, Escocia, 1992.

Telephone: +56 41 2204981

Office: Office 234, Edificio Central de Ingeniería

Web page: http://www.udec.cl/~dsbarbar

email: dsbarbar@udec.cl

Areas of Interest: 

• Control Automático.
• Identificación No-Lineal de Sistemas.
• Redes Neuronales.