Agata Mosinska
About Agata Mosinska
Agata Mosinska is a Senior Machine Learning Scientist at RetinAI, where she prepares documentation for regulatory submissions and designs validation study plans. She holds a Ph.D. in Computer and Communication Science from École polytechnique fédérale de Lausanne and has extensive experience in machine learning applications in healthcare.
Work at RetinAI
Agata Mosinska currently serves as a Senior Machine Learning Scientist at RetinAI, a position she has held since 2021. In this role, she is responsible for preparing documentation for regulatory submissions and designing validation study plans. She collaborates with various teams within a highly interdisciplinary healthcare environment to ensure the successful delivery and integration of machine learning algorithms. Mosinska also shares her expertise with young machine learning adepts and is involved in publishing research advances, as well as representing the company at technical and clinical conferences.
Education and Expertise
Agata Mosinska earned her Doctor of Philosophy (Ph.D.) in Computer and Communication Science from École polytechnique fédérale de Lausanne (EPFL), where she studied from 2014 to 2018. Prior to this, she completed a Master of Engineering in Biomedical Engineering at Imperial College London from 2010 to 2014. Her educational background is complemented by her experience in various research and engineering roles, enhancing her expertise in machine learning applications within healthcare.
Background
Before joining RetinAI, Agata Mosinska worked as a Research Scientist at the same organization from 2019 to 2021. Her earlier roles include serving as an Image Processing Research Engineer at Skin Analytics in 2014 and as an Interim Engineering Intern at Qualcomm Cambridge in 2013. She also gained experience as a Summer R&D Intern at Sony in 2012 and as an Undergraduate Researcher at Imperial College London in 2011. Her diverse background spans several years in research and engineering, contributing to her current role.
Research Contributions
Agata Mosinska has contributed to several significant research projects in the field of machine learning and ophthalmology. She participated in research focused on expert-level automated biomarker identification in OCT scans and AI-based fluid quantification in neovascular age-related macular degeneration. Additionally, she worked on developing GLAMpoints, a CNN-based feature point detector, and was involved in studies on fully-automated atrophy segmentation and personalized atrophy risk mapping in age-related macular degeneration.
Publications and Presentations
Agata Mosinska has authored publications on various topics, including automated foveal location detection in geographic atrophy patients and the comparison of drusen volume assessed by different OCT devices. She actively participates in presenting her research at technical and clinical conferences, contributing to the dissemination of knowledge in the field of machine learning applications in healthcare.