Contact information
Name: Barbara Cannas
Address: Dept. of Electrical and Electronic Engineering, Faculty of Engineering, University of Cagliari
Telephone +39 070 6755858
Email barbara.cannas@unica.it

Personal information
Date of Birth: December 24, 1971
Place of Birth: Cagliari, Italy
Citizenship: Italian
Sex: female
Marital Status: married
Children 2

Current position
Since March 2022 full professor in the SSD IIET/01-A sector “Elettrotecnica”, at the Engineering Faculty of the University of Cagliari.

Since October 2026 Coordinator of the Phd program on Electronic Engineering and Computer Science, University of Cagliari.

Education
1996 Master degree on in Electric Engineering, University of Cagliari, with rank 110/110 cum laude. Title of the dissertation: "Metrology and quality," supervised by Prof. Alessandra Fanni.
1996-1999 PhD in Electronic Engineering and Computer Science, Univ. of Cagliari. Title of the dissertation: "Development of circuital and neural techniques for the processing of chaotic signals and systems."
2000-2002 Research grant on "Analysis and synthesis of complex systems with neural networks" sector ING-IND/31, supervisor Prof. M. Marchesi, Dept. of Electrical and Electronic Engineering, Faculty of Engineering, University of Cagliari.
2002-2015 Researcher at the Dept. of Electric and Electronic Engineering, Faculty of Engineering, University of Cagliari (ING-IND/31).
2014  National scientific qualification to function as associate  professor in Italian Universities (sector ING-IND/31).
2017 National scientific qualification to function as full professor in Italian Universities (sector ING-IND/31).

2015-2022 Associate professor at the Dept. of Electric and Electronic Engineering, Faculty of Engineering, University of Cagliari (ING-IND/31).

Teaching Activities
• 2001/2002, Principles of Electrical Engineering 2, 6 credits, Master degree in Electrical and Electronic Engineering).
• 2002/2003, 2003/2004, 2004/2005, 2005/2006, 2006/2007, 2007/2008, 2008/2009, 2009/2010: Advanced Circuit theory (6 credits, Bachelor’s Degree in Electrical and Electronic Engineering).
• 2003/2004, 2004/2005, 2006/2007, 2007/2008: Dynamics of nonlinear circuits and chaos (6 credits, Master degree in in Electrical and Electronic Engineering).
• 2004/2005, 2005/2006, Circuit theory 1 (6 credits, Master degree in in Electrical and Electronic Engineering).
• 2006/2007, 2007/2008, 2009/2010 Circuit theory 2 (3 credits, Bachelor’s Degree in Electrical and Electronic Engineering). 

• 2011/2012 Digital and analog filters (6 credits, Master degree in in Electrical Engineering).
• 2012/2013, 2013/2014, 2014/2015, 2015/16, 2016/17, 2017/2018, 2018/2019  Nonlinear Systems and chaos  (6 credits, Master degree in in Electrical Engineering)

• 2019/2020, 2020/2021, 2021/2022, 2022/2023, 2023/2024  Circuit's design for signal processing (6 credits, Master degree in in Electrical Engineering)
• 2015/2016, 2016/2017, 2017/2018, 2018/2019, 2019/2020, 2020/2021, 2021/2022 2022/2023, 2023/2024 Circuit theory (6 credits, Bachelor’s Degree in Mechanical and Chemical Engineering).

Other educational activities
• 2003/2004, 2006/2007, 2007/2008, 2011/2012, 2015/2016, 2018/2019, 2020/2021: course of Dynamics of non-linear systems and chaos at the PhD School in Industrial Engineering, University of Cagliari (10 hours).
• 2003/2004, 2004-2005, 2006/2007: course of Electrical Engineering Education (Circuit Theory), University of Cagliari, School of Specialization for Secondary School Teachers (30 hours).
• 2005/2006, course of Circuit analysis under sinusoidal regime, University of Cagliari, School of Specialization for Teachers of Secondary School, Course for Technical and practical teachers (40 hours).

Research subjects

She is the scientific responsible of the agreement between  ENEA and University of Cagliari in the framework of FP9 program for the EUROfusion work program on nuclear fusion.
-Analysis and synthesis of nonlinear dynamic systems
-Soft computing techniques
-Nuclear fusion: disruption prediction and classification for tokamak; heat load monitoring in stellarators
-Biomedical data processing with machine learning techniques (COVID 19, multiple sclerosis risk)

2026, April 10th