The aspect of interdisciplinarity was also an important aspect for Jonas Schulz (shown above) when he decided to take up a doctoral position at SECAI. His research involves understanding human hand movements to accurately predict potential human intentions, such as interacting with a specific object. "Given that many applications, such as human-robot interaction or virtual world exploration, involve data communication over networks, this prediction can be used to compensate for certain latencies in the communication process." At the annual meeting of the DAAD Konrad Zuse Schools of Excellence in AI, Jonas Schulz presented a demonstration alongside other doctoral students.

The DAAD Zuse School event was the opportunity for many new doctoral students to familiarise themselves with the broad spectrum of AI research in SECAI and Germany in general and discuss current developments. "The Konrad Zuse Schools annual meeting was an interesting networking event. I got to know many young researchers and other Zuse Schools' work. It was inspiring and motivating," says Susu Hu. She has already received a SECAI scholarship for her master's thesis in the National Center for Tumor Disease (NCT) research group and joins SECAI as part of its PhD Fast Track Programme. Her research focuses on geometric deep learning for predicting surgical outcomes. The objective of the research is to help surgeons to better plan operations and, ideally, discover biomarkers for tumour diseases through the systematic analysis and interpretation of complex and multimodal medical data.

© DAAD/Nathan Dreessen

SECAI PhD Candidate Susu Hu showcasing the NCT demo during the DAAD Zuse School Event

In view of the rapid developments in AI research, Haadia Amjad's research topic is becoming increasingly relevant. She is working on Explainable Artificial Intelligence. "My research at SECAI is in collaboration with different experts and institutes, aiming to create explanations for computer-aided surgery systems“, explains Haadia Amjad. Her objective is to give the users of an AI system an understanding of the decisions made by this system. For areas in which an AI system makes or supports decisions that have an impact on human life, explainable AI is crucial. "The idea of being dedicated enough to a passion that you uncover the details to develop something new with your own research is what has always fascinated me. Even among researchers, the opportunity to tap into a field that directly affects human life is rare. Fortunately, this is exactly what SECAI has given me the opportunity for", reflects Haadia Amjad.

SECAI welcomes its new PhD students and wishes them all the best on their research journey.