LAURA
ASTOLFI
ING-INF/06
1021985 - Modelli di Sistemi Biologici (a.a. 2022/23)
Per informazioni aggiornate fare riferimento alla pagina web del corso: https://sites.google.com/a/uniroma1.it/mdsb/home
1044422 - Neuroscienze Industriali (a.a. 2022/23)
Per informazioni aggiornate fare riferimento alla pagina web del corso: https://sites.google.com/uniroma1.it/neuroscienzeindustriali/home
10592834 - Neuroengineering (a.y. 2022/23)
Instructions and links to join the online classes are available in the Piazza Class of the course. Check also the updated course website: https://sites.google.com/uniroma1.it/neuroengineering/home
Course | Code | Year | Course - Attendance | Bulletin board |
---|---|---|---|---|
Modelli di sistemi biologici | 1021985 | 2023/2024 | ||
NEUROENGINEERING | 10592834 | 2023/2024 | ||
NEUROSCIENZE INDUSTRIALI | 1044422 | 2023/2024 | ||
NEUROENGINEERING | 10592834 | 2023/2024 | ||
Modelli di sistemi biologici | 1021985 | 2022/2023 | ||
NEUROENGINEERING | 10592834 | 2022/2023 | ||
NEUROSCIENZE INDUSTRIALI | 1044422 | 2022/2023 | ||
NEUROENGINEERING | 10592834 | 2022/2023 | ||
NEUROSCIENZE INDUSTRIALI | 1044422 | 2021/2022 | ||
NEUROENGINEERING | 10592834 | 2021/2022 | ||
Modelli di sistemi biologici | 1021985 | 2021/2022 | ||
NEUROENGINEERING | 10592834 | 2021/2022 | ||
NEUROENGINEERING | 10592834 | 2020/2021 | ||
Modelli di sistemi biologici | 1021985 | 2020/2021 | ||
NEUROSCIENZE INDUSTRIALI | 1044422 | 2020/2021 | ||
NEUROENGINEERING | 10592834 | 2020/2021 | ||
NEUROSCIENZE INDUSTRIALI | 1044422 | 2019/2020 | ||
NEUROENGINEERING | 10592834 | 2019/2020 | ||
Modelli di sistemi biologici | 1021985 | 2019/2020 | ||
NEUROENGINEERING | 10592834 | 2019/2020 | ||
NEUROSCIENZE INDUSTRIALI | 1044422 | 2018/2019 | ||
Modelli di sistemi biologici | 1021985 | 2018/2019 | ||
MODELLI DI SISTEMI BIOLOGICI | 1021985 | 2018/2019 | ||
Modelli di sistemi biologici | 1021985 | 2017/2018 | ||
NEUROSCIENZE INDUSTRIALI | 1044422 | 2017/2018 | ||
Modelli di sistemi biologici | 1021985 | 2016/2017 | ||
NEUROSCIENZE INDUSTRIALI | 1044422 | 2016/2017 |
Da concordare inviando messaggio email alla docente.
Laura Astolfi received her Master Degree in Electronic Engineering from University of Rome Sapienza and her PhD in Biomedical Engineering from University of Bologna Alma Mater Studiorum. Currently, she is an Associate Professor at the Department of Computer, Control, and Management Engineering at Sapienza University of Rome and a Researcher at Fondazione Santa Lucia Hospital, Rome, Italy.
She is Associate Editor of Medical & Biological Engineering & Computing and Brain Topography.
She is Fellow of the European Alliance for Medical and Biological Engineering Sciences (EAMBES) and Member of the Scientific Board of the International Society for Brain Electromagenetic Topography (ISBET).
She is Head of the Bioengineering and Bioinformatics Laboratory at DIAG and Junior Fellow of the Sapienza School for Advanced Studies (SSAS).
She participated and/or was PI in several national (Ministry of Health, Ministry of University, Private Foundations) European (7th FPs, Horizon2020) and US (NSF and NIH) funded research projects. She has been National Representative to 2 EU COST Actions.
She received several national and international awards for her scientific activity, among which the Best Under-40 Researcher Award at Sapienza University in 2010, the Trainee Travel Award by the Human Brain Mapping Society in 2011, the Young Investigator Competition by the ISBET Society in 2009, the Best PhD Thesis Award by the Italian Society for Biomedical Engineering in 2008, the Young Investigator Award by the Brain Connectivity Society in 2006, the Young Investigator Award by the International Society for Functional Source Imaging in 2005.
She authored 170 papers, with 4806 citations and a total Impact Factor of 241.247 and her H-index is 46.
She is listed among the Top Italian Scientists in Engineering (http://www.topitalianscientists.org/TIS_HTML/Top_Italian_Scientists_Engi...)
Her research activity include brain connectivity, high resolution EEG source reconstruction, EEG applications to neurorehabilitation, simultaneous recordings from multiple subjects (hyperscanning), consciousness, cognition and social Neuroscience.