Birgül Akolpoglu 4 minute read

InternViews #4: Evie Stergiopoulou

InternViews is our weekly series where RIGI interns share their experiences, insights, and stories from their time in Stuttgart.

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Evie Stergiopoulou is a master's student in Environmental Data Science & Machine Learning at Imperial College London.
This week, we meet Evie Stergiopoulou, a master's student in Environmental Data Science & Machine Learning at Imperial College London. Evie has worked on developing a system for contact prediction in Cutaneous Electrohydraulic (CUTE) Wearable Devices under the supervision of Natalia Sanchez-Tamayo and Dr. Katherine J. Kuchenbecker during her internship. This involved building a data acquisition setup to record signals (voltage, current, and force), preprocessing the data, and training an LSTM-based machine learning model that estimates contact force in real time from voltage and capacitance. The goal is to bring us closer to creating full-body wearable arrays of haptic actuators, enabling users to feel realistic sensations for applications ranging from remote sensing to immersive VR experiences. One of Evie's favourite robots is Icefin, a hybrid remotely operated or AI-assisted autonomous underwater vehicle. It explores the melting beneath Antarctic ice shelves, such as the Thwaites Glacier (aka the Doomsday Glacier), which helps us improve sea level rise projections.