This image shows Andrea Iannelli

Andrea Iannelli

Prof. Dr.

Trustworthy Autonomy for Smart Adaptive Systems
Institute for Systems Theory and Automatic Control

Contact

+49 711 685 67730
+4971168557730

Pfaffenwaldring 9
70569 Stuttgart
Germany
Room: 2.244

Office Hours

to be announced

                               

Subject

My research interests are on principled techniques for modelling, analysis, and control of uncertain linear and nonlinear dynamical systems. I do research on both model- and data-based approaches, and I believe that reconciling these two viewpoints and leveraging the respective strengths is key to achieve safety and reduce conservatism for trustworthy autonomous operation of complex systems. My research has impact on the development of intelligent systems for a sustainable society, especially in the fields of energy and transportation systems and industry 4.0: e.g. industrial automation, robotics, automotive, manufacturing, energy management. Research keywords: data-driven control theory; uncertainty quantification; optimization; robust control; system identification; dynamical systems theory.

Andrea Iannelli is from October 2022 a Tenure-Track Junior Professor in the Institute for Systems
Theory and Automatic Control at the University of Stuttgart. His basic research interests include:
data-driven control theory; uncertainty quantification; optimization; robust control; system
identification; dynamical systems theory.
He completed his Bachelor and Master degrees in Aerospace Engineering at the University of Pisa
(Italy). In April 2019 he got his PhD at the University of Bristol (UK), supported by the H2020 project
FLEXOP. During his PhD, Andrea worked on the reconciliation between robust control theory (Linear
Fractional Transformation, structured singular value, Integral Quadratic Constraints, Dissipativity)
and dynamical systems approaches (bifurcation theory, numerical continuation), with application to
the study of dynamic instabilities in uncertain aerospace systems. He was a postdoctoral researcher
in the Automatic Control Laboratory at ETH Zürich from May 2019 to September 2022. During his
PostDoc he has developed and demonstrated theoretical and practical advances in the broad field at
the intersection between control theory and learning, with particular emphasis on the use of data to
make robust predictions and take reliable decisions. He has been involved in the supervision and co-
supervision of several Master thesis and PhD projects on the topics above and has been invited to
present the outcome of his research in Workshops and Seminars organized nationally and
internationally. He has a solid network of international collaborators and is looking forward to
strengthen it in the future.
For more information, please refer to his personal webpage 
and research profiles: Google Scholar, Scopus, Research Gate

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