Zeynep

GÜRİŞ Technology Inc.

• Developed industrial Artificial Intelligence and Computer Vision solutions for the renewable energy sector.
• Built YOLO-based defect detection, classification, and measurement systems for wind turbine blade inspection.
• Designed image processing, similarity analysis, and automated reporting pipelines using OpenCV.
• Developed and deployed scalable Python microservices using Docker and Azure Container Apps.
• Managed CI/CD pipelines with GitHub Actions and implemented cloud-native deployment workflows.
• Designed real-time data synchronization and Change Data Capture (CDC) architectures using Apache Kafka and Debezium.
• Developed OCR-based document processing services and production-ready APIs for extracting structured information from PDFs and images.
• Contributed to the development and maintenance of production systems built on Azure App Service, Azure Blob Storage, and PostgreSQL.

GÜRİŞ Technology Inc.

• Developed time-series analysis and machine learning models for renewable energy forecasting.
• Contributed to computer vision projects involving image processing and automated defect detection.
• Built Python-based data processing and analytics pipelines for large-scale datasets.
• Developed data-driven applications using PostgreSQL.
• Contributed to the development and deployment of cloud applications on Microsoft Azure.
• Built internal web applications and engineering tools for technical teams.
• Worked on industrial data analytics, automation, and reporting solutions.

TOBB University of Economics and Technology

• Developed Python, TCL, MATLAB, and VBA codes for creating initial 3D atomistic structures, running computational calculations sequentially, and performing numerical analysis and visualization of outputs.
• Developed Bash scripts on Linux to create workflows for molecular simulations.
• Created batch scripts for high-performance computer systems (TRUBA supercomputers provided by TÜBİTAK).
• Conducted in-depth data analysis for COVID-19 datasets sourced from GISAID and PDB, using Python and Bash scripting for extraction, statistical calculations, and analysis.
• Managed and recorded the grading process for homework, experimental reports, and exams. Courses: Numerical Methods in Biomedical Engineering / Materials Science, Materials Science 101 Laboratory, Biomaterials Laboratory.

Coderspace - TRENDYOL

• Used Google BigQuery, SQL, Kafka Connect, ETL/ELT, batch data pipelines, and Airflow.

Coursera - UC San Diego

• Developed bioinformatics algorithms: finding frequent words with mismatches, pattern analysis, Hamming distance, greedy motif search, and Gibbs sampling. Coded all algorithms in Python.

Coursera - UC San Diego

• Developed bioinformatics algorithms. Coded all algorithms in Python.