Sevda Öğüt
Visiting Researcher at Wellcome Sanger Institute
Switzerland
Summary
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Rockstar🎓
Top SchoolSevda Öğüt is a PhD candidate in Computer Science at EPFL's LTS4 lab, focused on applying graph deep learning and whole-slide image analysis to advance personalized oncology while prioritizing interpretability and reliable foundation models for computational biology. With prior research on molecular communication and multi-armed bandits, she combines strong theoretical grounding from Bilkent (BSc 3.91/4.00) with practical experience in ML inference benchmarking from industry internships. Her work bridges algorithmic rigor and clinical relevance, aiming to make AI-driven decisions transparent for clinicians. Based in Switzerland, she brings two years of focused research experience and a consistent academic excellence streak dating back to top scores in secondary education.
2 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS Electrical and Electronics Engineering, Bachelor of Science - BS Electrical and Electronics Engineering at Bilkent UniversityFirst and Middle School Diploma, First and Middle School Diploma at Private Bilkent First and Middle SchoolVisiting Researcher, Visiting Researcher at University of CambridgeDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at EPFLHigh School Diploma, High School Diploma at Private Bilkent High School
English, French, Turkish
Github Skills (6)
machine-learning7
medical-image-analysis3
histopathology2
digital-pathology2
graph1
image-analysis1
Programming languages (3)
Github contributions (5)
ogutsevda/ogutsevda.github.io
Nov 2023 - Jul 2026
Contributions:37 pushes, 1 branch in 2 years 7 months
ogutsevda/HIGT
Jul 2024 - Aug 2024
[MICCAI'23] HIGT: Hierarchical Interaction Graph-Transformer for Whole Slide Image Analysis
Contributions:6 pushes in 8 days
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