Sevda Öğüt

Doctoral Student at École polytechnique fédérale de Lausanne

Switzerland
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Summary

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Sevda 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.
code2 years of coding experience
job2 years of employment as a software developer
bookFirst and Middle School Diploma, First and Middle School Diploma at Private Bilkent First and Middle School
bookDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Ecole polytechnique fédérale de Lausanne
bookBachelor of Science - BS, Electrical and Electronics Engineering, 3.91/4.00, Bachelor of Science - BS, Electrical and Electronics Engineering, 3.91/4.00 at Bilkent University
bookHigh School Diploma, 99.39/100, High School Diploma, 99.39/100 at Private Bilkent High School
languagesEnglish, French, Turkish
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Github Skills (5)

machine-learning6
data-science5
digital-pathology1
medical-image-analysis1
histopathology1

Programming languages (1)

Jupyter Notebook

Github contributions (5)

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Contributions:17 pushes, 1 branch in 1 year 3 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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Sevda Öğüt - Doctoral Student at École polytechnique fédérale de Lausanne