Valentina Casadei, Eng, earned her PhD in Electrical Engineering and Electronics from the University of Liverpool, UK. Her interdisciplinary research, conducted in collaboration with the Psychology Department and Alder Hey Children's Hospital, focuses on enhancing the accuracy of biomedical measurements from wearable devices through advanced uncertainty analysis and model development. 

Currently, she is a postdoctoral researcher at the Centre for Elderly and Nursing Home Medicine (SEFAS) at the University of Bergen, Norway, involved in the DARK.DEM project. Her research focuses on developing models to identify Digital Phenotyping of dementia and quantifying the associated uncertainties. This research aims to evaluate the feasibility of wearable devices for clinical applications.

She is IEEE member since 2018 (Engineering in Medicine and Biology society since 2019 and Instrumentation and Measurement since 2020). She is currently Vice-Chair of the IEEE EMBS Norway Section Chapter.

Invited Speaker

• 2025 - Neuro-SysMed Seminars "Tech-care: wearable sensor technologies to enhance understanding of symptoms, behavior and response to treatment"

• Demonstrator (teaching assistant) for Signals and Systems, Robotics, and MATLAB in the Electrical and Electronics Engineering Department at the University of Liverpool
• Currently, she is co-supervising one PhD student within the DARK.DEM project

• (2020) Ferracuti Francesco, Casadei Valentina, Marcantoni Ilaria, Iarlori Sabrina, Burattini Laura, Monteriu Andrea, Porcaro Camillo, ”A functional source separation algorithm to enhance error-related potentials monitoring in the noninvasive brain-computer interface”
   
• (2020) V. Casadei, R. Ferrero, and C. Brown, "Model-Based Filtering of EEG Alpha Waves for Enhanced Accuracy in Dynamic Conditions and Artifact Detection," 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Dubrovnik, Croatia.
   
• (2022) - V. Casadei and R. Ferrero, "Online Skin-Electrode Contact
  Quality Monitoring in Wearable Devices: An EEG Application," 2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Ottawa, ON, Canada.
   
• (2023) - V. Casadei and R. Ferrero, "Model-Based Fitting of EEG Signals With Uncertainty Quantification for Robust Alpha Wave Identification," in IEEE Transactions on Instrumentation and Measurement.

• University of Liverpool - Programming of an accelerometer using Arduino for confidential biomedical application. Funded project.
• University of Liverpool - Development of a proof-of-concept prototype for automated measurement of thin liquid film drying rates using weight difference during evaporation. Founded project
• University of Liverpool - Development of  an interface for students using LabVIEW  for the Signal and Systems module at the Department of Electrical Engineering and Electronics