Summary
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.
2 years of coding experience
2 years of employment as a software developer
First and Middle School Diploma, First and Middle School Diploma at Private Bilkent First and Middle School
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Ecole polytechnique fédérale de Lausanne
Bachelor 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
High School Diploma, 99.39/100, High School Diploma, 99.39/100 at Private Bilkent High School
English, French, Turkish