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). My work lies at the intersection of artificial intelligence, large-scale systems, and computational biology where I design intelligent, scalable pipelines that bridge scientific discovery with real-world impact.

With hands-on experience in Python, R, SQL, C++, and JavaScript, and a strong foundation in machine learning, high-performance computing, and data architecture, I specialize in building end-to-end systems that are both computationally efficient and ethically grounded. My broader goal is to engineer technologies that not only advance biomedical and societal research but also reinforce fairness, reproducibility, and transparency in AI.

What I’m Working On

At the Interdisciplinary Institute for Societal Computing, I am developing a scalable geo-intelligence platform that integrates Google Maps data with complementary geospatial sources for large-scale regional analysis. The system enables dynamic insights such as live traffic trends, population movement, and user behavior across geographic boundaries. This is achieved by combining PostgreSQL/PostGIS, Redis, and asynchronous microservices for high-throughput data ingestion and analysis.

Selected Previous Work

Medical Imaging Reconstruction (Harvard Medical School) Designed and optimized convolutional neural networks (CNNs) for parallel imaging reconstruction, improving signal-to-noise ratio and reconstruction speed.

Sepsis Mortality Prediction (University of Southern California) Developed ensemble models using Random Forests, Gradient Boosting, and k-Nearest Neighbors to predict sepsis outcomes from clinical time-series data.

Global AI Ethics Atlas (Emory University) Built an interactive global visualization platform that maps medical AI ethics guidelines across countries, integrating NLP and geospatial data visualization in React.

Genomic Reproducibility Benchmark (ETH Zürich) Automated genomic workflows with Snakemake on HPC clusters to assess reproducibility of read alignment tools, improving consistency and transparency in bioinformatics analysis.

AI Safety & Community

Alongside my research, I lead Marketing and Outreach at AI Safety Saarland (AISS), a student-led initiative promoting safe, fair, and beneficial AI development. I coordinate cross-channel campaigns, oversee event communications, and collaborate with researchers and mentors worldwide to grow an interdisciplinary community around AI safety.

Before that, I worked as a Marketing Specialist at Thread In Motion, where I led data-driven campaigns across Google Ads, LinkedIn, and Meta, integrated HubSpot automations, and deployed machine learning analytics pipelines to improve user acquisition and retention.

In Short

I care deeply about building systems that matter aka scalable infrastructures that accelerate research, advance healthcare, and make technology more responsible. My goal is creating tools that empower both researchers and society at large.