Published papers such as 'A Muscle Pennation Angle Estimation Framework From Raw Ultrasound Data for Wearable Biomedical Instrumentation' and 'Reducing False Alarms in Wearable Seizure Monitoring'.
Research Experience
Involved in the High-Precision Control and Localization for Robotic Billiard Shots project, which combines the fields of view of two cameras (an overhead camera pointing down on the table and a cue-mounted camera) to allow a robotic arm to achieve the excellent cueing accuracy observed in human players.
Education
Ph.D. in Electrical Engineering and Information Technology, ETH Zurich, supervised by Prof. Dr. Luca Benini; M.Sc. in Electrical Engineering and Information Technology, 2020, ETH Zurich; B.Sc. in Electrical and Computer Engineering, 2018, University of Iceland.
Background
Research interests include applying robust and practical machine learning approaches, particularly in bio-signal analysis, taking into account the characteristics and constraints of wearable edge devices and IoT units. Currently researching the use case of using bio-signals to detect and forecast seizures.
Miscellany
Interests include Artificial Intelligence, Neural Architecture Search, and Bio-signal Classification.