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Claudio Altafini

Professor

My research interests are broadly in the area of modeling and control of nonlinear dynamical systems.

Presentation

Background

I received a Laurea degree in Electrical Engineering from the University of Padova, Italy, in 1996 and a PhD in Optimization and Systems Theory from the Royal Institute of Technology, Stockholm, in 2001. I then moved to SISSA (International School for Advanced Studies) in Trieste, Italy, where I stayed until 2013. Since 2014 I am a Professor in Automatic Control in the Department of Electrical Engineering, Linkoping University.

Research

My research interests are broadly in the area of modeling and control of nonlinear dynamical systems. Over the years I have been involved with very different applications, ranging from robotics to quantum mechanics, from biological systems to complex networks. In the last few years the focus of my research has been almost exclusively on Modeling and Control of Complex Networks, for applications in Engineering and Technology, Systems Biology and Social Networks.

Selected Publications

Complex Networks:

  • G. Shi, C. Altafini and J. Baras. Dynamics over Signed Networks. SIAM Review, 61(2):229-257, 2019.
  • C Altafini. Consensus problems on networks with antagonistic interactions. IEEE Trans. on Automatic Control, 58 (4), 935-946, 2013.
  • G Facchetti, G Iacono, C Altafini. Computing global structural balance in large-scale signed social networks. Proceedings of the National Academy of Sciences 108 (52), 20953-20958, 2011.

Systems Biology:

  • G De Palo, G Facchetti, M Mazzolini, A Menini, V Torre, C Altafini. Common dynamical features of sensory adaptation in photoreceptors and olfactory sensory neurons. Scientific reports 3:1251, 2013.
  • G Facchetti, M Zampieri, C Altafini Predicting and characterizing selective multiple drug treatments for metabolic diseases and cancer. BMC systems biology 6 (1), 115, 2013.
  • N. Soranzo, F. Ramezani, G. Iacono and C. Altafini. Decompositions of large-scale biological systems based on dynamical properties. Bioinformatics, 28(1):76-83, 2012.

Quantum Control:

  • C. Altafini and F. Ticozzi. Modeling and Control of Quantum Systems: An Introduction, (tutorial paper) Special Issue on Quantum Control of the IEEE Trans. on Automatic Control, 57(8):1898-1917, 2012.

See my Google scholar page for a complete list.

Teaching

From 2020 I am teaching the TSRT09 Control Theory course.
In 2014-19 I was teaching the TSRT62 Modeling and Simulation course.

I am also responsible for the PhD course Nonlinear Control, normally given every second year. In 2015 I taught two other PhD courses: Networked Dynamical Systems and Systems Biology: nonlinear mechanistic models.

Master Thesis proposals

I have several topics for Master thesis for Engineering students. Contact me if interested.

Latest Publications

2024

Angela Fontan, Marco Ratta, Claudio Altafini (2024) From populations to networks: Relating diversity indices and frustration in signed graphs PNAS NEXUS, Vol. 3, Article pgae046 Continue to DOI
Carmela Bernardo, Claudio Altafini, Anton Proskurnikov, Francesco Vasca (2024) Bounded confidence opinion dynamics: A survey Automatica, Vol. 159, Article 111302 Continue to DOI

2023

Muhammad Ahsan Razaq, Claudio Altafini (2023) Propagation of Stubborn Opinions on Signed Graphs 2023 62ND IEEE CONFERENCE ON DECISION AND CONTROL, CDC, p. 491-496 Continue to DOI
Angela Fontan, Claudio Altafini (2023) PSEUDOINVERSES OF SIGNED LAPLACIAN MATRICES SIAM Journal on Matrix Analysis and Applications, Vol. 44, p. 622-647 Continue to DOI
Julia Åkesson, Sara Hojjati, Sandra Hellberg, Johanna Raffetseder, Mohsen Khademi, Robert Rynkowski, Ingrid Kockum, Claudio Altafini, Zelmina Lubovac-Pilav, Johan Mellergård, Maria Jenmalm, Fredrik Piehl, Tomas Olsson, Jan Ernerudh, Mika Gustafsson (2023) Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis Nature Communications, Data for: Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis, Vol. 14, Article 6903 Continue to DOI

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