Silvia Seidlitz

Silvia is a PhD student in Computer Science, focusing her research on reliable, bias-aware deep learning-based spectral image analysis for perioperative applications, such as surgical scene segmentation and automated sepsis diagnosis. She completed her BSc in physics in 2017 and her MSc in 2019, both at Heidelberg University. Since 2021, she has taken on a leadership role in the Spectral Imaging subgroup within the department. Silvia has a keen interest in open science, actively contributing to open source repositories and sharing her spectral imaging datasets with the broader research community. Additionally, she holds the position of sustainability officer within the department, seeking opportunities to enhance the environmental impact of their research.

Beyond her academic pursuits, Silvia enjoys climbing and volunteers at the Federal Agency of Technical Relief. She also has a passion for traveling the world, especially for bikepacking and hiking.

Expertise

• (Bio)Photonics, especially Hyperspectral Imaging and Superresolution Microscopy
• Data Science & Deep Learning, with a focus on generalizability and bias-awareness
• Scientific visualizations

Links

• Github
• Google Scholar
• Linkedin