Matteo Iervasi

Stipendiat

Matteo Iervasi

Kontakt

E-post: matteo.iervasi@uis.no

Rom: KE E-401

Organisasjonsenhet

Det teknisk- naturvitenskapelige fakultet

Institutt for data- og elektroteknologi

Kort om meg

I’m a Ph.D. student at the University of Stavanger with a strong background in embedded systems, firmware development, and low-level programming. I graduated in Computer Science and Engineering from the University of Verona in 2020, where I grew a passion for developing software on microcontrollers and real-time systems.

Before starting my Ph.D., I worked for the IoT consultancy industry, where I contributed to various R&D projects in the IoT and automation domains. I enjoy working close to the hardware, especially with C and C++, and I like exploring how systems behave under the hood.

For more information visit my website https://matteoiervasi.it

Dette forsker jeg på

My research explores how Wireless Sensor Networks (WSNs) and wearable devices can be used to support Active and Assisted Living (AAL). I’m currently working on a system that uses smart glasses, wearable sensors, and environmental data (like BLE beacons and Wi-Fi signals) to recognize symptoms and daily activities in people with Parkinson’s disease. By running AI algorithms directly on the devices, the system can detect issues like Freezing of Gait in real-time and provide timely, personalized feedback to the user.

Ultimately, my goal is to create adaptive, context-aware tools that help people manage their conditions more independently, while also easing the load on healthcare systems.

Publikasjoner

Vitenskapelige publikasjoner

Matteo Iervasi; Jodi Maple Grødem; Luigi Borzì; Guido Werner Alves; Trygve Christian Eftestøl; Florenc Demrozi (2025) Cueing Technologies in Parkinson’s Disease: A Systematic Review. I: IEEE Access. Online ISSN 2169-3536. Volum 13. s.216408-216427. DOI: 10.1109/ACCESS.2025.3647133

Formidling

Geir Halnes; Anam Javaid; Michael Solvang; Stefano Nichele; Michael Riegler; Bjørn-Jostein Singstad; Baltasar Beferull-Lozano; Emilio Ruiz Moreno; Luis M. Lopez-Ramos; Mehrzad Abdi Khalife; Ola Huse Ramstad; Hamze Issa; Arina Surko; Axel Sandvig; Hasan Ogul; Daniele Fantin; Ioanna Sandvig; Christopher Vibe; Kushtrim Visoka; Mehdi HoushmandSarkhoosh; Aaron de Leyos; Sinan Ugur Umu; Klaus Johannsen; Kjetil Indrehus; Malcom McMillan; Julia Kropiunig; Ryan Anthony Marinelli; Fadi Al Machot; Xue-Cheng Tai; Andrea Alessandro Gasparini; David Parkes; Semra Oztemel Sari; Gro Fonnes; Cise Midoglu; Anton Tkachenko; Maria Bashir; Kari-Anne Kallerud Lyng; Florenc Demrozi; Kate Briggs; Junyong You; Signe Riemer-Sørensen; Benjamin Daniel Adolphi; Martin Thomas Horsch; Arangan Subramaniam; Ibrahim Riza Hallac; Lina Plataniti; Hao Liu; Mikkel Elle Lepperød; Changkyu Choi; Preben Castberg; Abdelaziz Qassi; Raymond H. Chan; Anja Stein; Heinz Adolf Preisig; Alexander Johannes Stasik; Saeed Shafiee Sabet; Nils Olav Handegard; Robert Jenssen; Solve Sæbø; Synnøve Rubach; Waldir Leoncio Netto; Pankaj Pandey; Jan Wuite; Arezo Shakeri; Shailendra Singh; Ali Ramezani-Kebrya; Pål Halvorsen; David S. Leslie; Matteo Iervasi; Mathis Korseberg Stokke; Tomas Kupka; Lingfeng Li; Helge Fredriksen; Shakiba Sadat Mirbagheri; Ali Ramezanikebrya; Jacob Alexander Hay; Aslak Djupskås; Mina FNorwayarmanbar; Claudio Sartori; Felix Simon Reimers; Thomas Nagler; Amber Leeson (2025) Proceedings of NORA’s annual conference 2025. I: Nordic Machine Intelligence (NMI). Online ISSN 2703-9196. Volum 5. s.1-14. DOI: 10.5617/nmi.12551

Kilde: Nasjonalt vitenarkiv