Imperial News

DoC PhD Researcher Mélanie Roschewitz Receives Prestigious Award

by Mr Ahmed Idle

Mélanie Roschewitz receives the British Federation of Women Graduates award for disease detection research.  

The Department of Computing at Imperial is pleased to announce that Mélanie Roschewitz has been awarded the Margaret and Martin Gotheridge Award by the British Federation of Women Graduates (BFWG). This prestigious award is given to female doctoral students who demonstrate outstanding academic achievements and the ability to communicate complex research to a non-specialist audience.

Roschewitz's research is focused on enhancing the reliability, fairness, and robustness of disease detection models. Her work involves developing advanced computational techniques to improve the performance and ethical considerations of these models, which are crucial in medical diagnostics. By addressing biases and ensuring consistent accuracy, her research aims to make disease detection models more reliable and equitable.

The BFWG recognized Roschewitz for her significant contributions to the field of medical computing and the potential impact of her work on healthcare outcomes. Her ability to present her research in an accessible manner to non-specialists was also a key factor in her receiving the award.

Roschewitz expressed her gratitude for the recognition, stating, “I am delighted to receive this award. It’s a wonderful recognition of the importance of our research. I’d like to thank my supervisor Prof Ben Glocker for his valuable guidance, as well as all my colleagues for their support and contributions. I’m also grateful for the support of Imperial President’s PhD Scholarship.”

Professor Ben Glocker, Roschewitz's supervisor, praised her dedication and innovation in her research. "Mélanie's work is a testament to her commitment to advancing the field of medical image computing. Her contributions are paving the way for more reliable and fair disease detection models, which is a significant step forward in using AI technology for medical diagnostics."