Hi! I’m Ful Belin Korukoglu, a Master’s student in Bioinformatics at Saarland University and a Research Assistant at the Interdisciplinary Institute for Societal Computing (I2SC). I am doing my thesis jointly at Computational Pathology & Machine Learning at Schüffler Lab and Chair of Computational Biology at Saarland University.

Research Interests

I’m interested in developing AI systems that accelerate scientific discovery through robust, reproducible, and uncertainty-aware reasoning. My research interests include reliable machine learning, evidence-based decision-making, and autonomous scientific agents.

What I’m Working On

Geospatial Data Infrastructure @ I2SC, Saarland University

I develop scalable geospatial data infrastructure for large-scale societal research, integrating Google Maps data with complementary geographic sources. My work involves building distributed data collection and processing pipelines, optimizing asynchronous workflows, and enabling analyses of hundreds of thousands of places of interest across different regions.

Graph-Based Deep Learning for Computational Pathology — Saarland University & Technical University of Munich

For my Master’s thesis, I investigate topology-aware graph-based multiple instance learning for predicting molecular characteristics from histopathology images. I develop and evaluate graph neural network architectures using pathology foundation-model representations, with an emphasis on robustness and generalization.

Selected Previous Work

Medical Imaging Reconstruction @ Harvard Medical School

Implemented and evaluated deep learning pipelines for MRI reconstruction across multiple imaging datasets and undersampling conditions, automating model inference and reconstruction-quality evaluation.

Sepsis Mortality Prediction @ University of Southern California

Benchmarked classical and deep learning models for sepsis mortality prediction across 16 independent transcriptomic cohorts, investigating cross-cohort generalization, feature importance, and reproducibility of predictive biological signals.

Global AI Ethics Atlas @ Emory University

Developed a full-stack healthcare AI governance platform for organizing and comparing international regulatory frameworks and ethical guidelines. This research contributed to my first-author publication, Mapping Ethical Guidelines for AI in Healthcare: A Global Perspective (2025).

Genomic Reproducibility Benchmark @ ETH Zürich

Investigated the reproducibility of genomic read alignment tools and developed automated bioinformatics workflows using Snakemake for systematic benchmarking and reproducible analysis.

Other Interests

Alongside my technical research, I’m interested in the reliability, transparency, and societal implications of increasingly capable AI systems.

I previously led Marketing and Outreach at AI Safety Saarland (AISS), a student-led initiative promoting safe, fair, and beneficial AI development.

Previously, I also worked as a Marketing Specialist at Thread In Motion, where I managed data-driven digital campaigns, integrated marketing automation workflows, and developed analytics pipelines to support user acquisition and retention.