High-Performance Computational Strategies

Thanks to our research in theoretical, algorithmic, and applied aspects of computational electromagnetics, the complexity of standard modelling approaches can be substantially reduced resulting in orders of magnitude savings of solution time. These research axes impact several application scenarios including biomedical systems, antenna design and high power electromagnetics. Are you interested in high performance computing, numerical analysis, advanced algorithmics, or computational physics and would like to do research with us? Then contact us for learning about our currently available positions!

Modelling and Computations for Biomedical Imaging and Brain-Computer Interfaces

Computational Electromagnetics (CEM) can be used to accurately reconstruct the brain’s electrical activity via non-invasive techniques like electroencephalography to help in medical diagnosis for pathologies such as focal epilepsy, Parkinson Disease and Alzheimer. Electroencephalography, or EEG, is a well-established modality for functional brain imaging via source localization, and is utilized in a wide range of applications, such as epilepsy planning and treatment, transcranial brain stimulation, electrical impedance tomography and brain-computer interfaces. Our work focuses on finding increasingly innovative computational solutions to push the boundaries related to the brain’s studies. This is of the utmost importance today for what it concernes neurosciences. By reconstrunting the brain’s electrical activity it is possible to diagnose the occurrence of neurological disorders and neurodegenerative diseases and without the need of skull’s trepanation, with a consequential high impact on society, releted to the social cost of such diseases and, above all, to the needs of all those patients who can not tolerate an invasive treatment.

Computationally Enhanced Reality

The fast modeling capabilities offered by novel computational electromagnetic technologies enable a wide array of real-time applications. Neurosurfing combines this real-time capabilities with high resolution brain models to allow for real-time, VR-augmented intracranial navigation of a patient into his own brain activity, for assisting in psychotherapy treatments or to help with presurgical assessments. Our VR framework in Unity3D can stimulate a neurofeedback to create a real-time display of neuroactivity to teach patients to self-regulate their own brain functions. This technology can provide a substantial contribution in the field of neurotherapy that is considered today a crucial part of therapeutic strategies for psychological diseases such as anxiety, depression, and obsessive-compulsive disorders.

IEEE AP-S Elections 2025

01 January 2026

IEEE Fellow elevation

01 January 2023

Five Honorable Mentions at the 2022 IEEE AP-S International Symposium

05 July 2022

2021 ICEAA IEEE-APWC Best Paper Award

11 August 2021

Honorable Mention at IEEE-AP-S Symposium 2020

01 April 2020

The new Editor-in-Chief of the IEEE AP-S Magazine

01 July 2019

Third Prize at 2018 IEEE AP-S International Symposium SPC

20 July 2018

Consolidator Grant by the European Research Council

17 November 2016

First Prize in the best paper competition of the 2016 URSI International Symposium

15 August 2016

2015 ICEAA IEEE-APWC Award

15 September 2015

Third Prize at 2015 IEEE AP-S International Symposium

01 August 2015

EurAAP Leopold B. Felsen Award for Excellence in Electrodynamics.

15 April 2015

Best young scientist paper award at URSI

02 October 2014

Second prize at the URSI General Assembly 2014

20 August 2014

2014-2016 URSI Issac Koga Gold Medal.

20 August 2014

Best poster award during the IEEE EMBS international summer school

27 June 2014

IEEE AP-S Donald G. Dudley Jr. Undergraduate Teaching Award

25 May 2014

Journal Papers

Conference Proceedings