Hello, I'm Yagmur
Full Stack Development | Data Enthusiast
Full-stack developer and data engineer with experience building cloud-native pipelines, containerized applications, and applied machine learning models. Skilled in AWS serverless architectures, Terraform, and computer vision (YOLO-based detection). Passionate about making complex technical topics accessible—regular contributor to Towards Data Science, where I publish tutorials on data engineering and ML workflows.
Download my CVProjects
Serverless Job Queue for SQL-Based Label Statistics and Dataset Partitioning
Designed and deployed a serverless data-processing pipeline for object detection dataset analytics (Pascal VOC). Use case: Balanced dataset generation for computer vision models.
End-to-End Geospatial Climate Data Visualization with Spring Boot, PostgreSQL, and Deck.gl
This project is a comprehensive end-to-end geospatial climate data visualization application. It utilizes Spring Boot for the backend to serve GeoJSON data, PostgreSQL for the database, and Deck.gl for the frontend visualization. The project is designed to handle large datasets efficiently and provides an interactive user interface for exploring climate data.
Next.js Portfolio With Continuous Delivery using GitHub Actions
This portfolio is built with Next.js and deployed with GitHub Pages. The deployment is automated with GitHub Actions.
Publications
Clustering Eating Behaviors in Time: A Machine Learning Approach to Preventive Health
May 8, 2025
Towards Data Science
An article exploring temporal dietary patterns using Modified Dynamic Time Warping and unsupervised clustering.
End-to-End AWS RDS Setup with Bastion Host Using Terraform
Jul 28, 2025
Towards Data Science
An article detailing the setup of AWS RDS with a Bastion host using Terraform.
How to Import Pre-Annotated Data into Label Studio and Run the Full Stack with Docker
August 29, 2025
Towards Data Science
An article detailing the process of importing pre-annotated data into Label Studio and running the full stack with Docker.
Job Experience
Machine Learning Developer Intern
M2M
May 2025 – July 2025
- Implementing data augmentation techniques for a large-scale dataset of images to improve the performance of a deep learning model for Yolo Object DetectionPythonDeep LearningPyTorchData Augmentation
Software Developer Intern
Riipen Level UP and Beyond the Cloud
March 2024 – March 2025
- Automation of provisioning a Jenkins server running on an EC2 instance with TerraformAWS EC2Bash ScriptNgnixTerraformJenkinsInfrastructure as Code (IaC)
- Developed a full-stack interactive dashboard for analysis of prediction market data and deployed on AWS LambdaAWS LambdaPythonData analysisAPI GatewayPandasPlotlyDashDockerServerless
- Redesigned a MySQL database schema for a voluntary board management database to reduce redundancy and improve performanceSQLDockerEntity Relation DiagramCollaboration
- Developed a full-stack application to automate the trimming of long Youtube video clips according to the subtitle analysis using OpenAI APIFastAPIDockerJavaScriptBootstrapOpenAI API
P.h.D. Researcher in Mechanical Engineering
University of Sherbrooke, Quebec
February 2019 – September 2021
- Successfully automated large-scale simulations on **High-Performance Computing (HPC) clusters, optimized computational workflows by writing Bash scripts to manage job scheduling, data preprocessing, and result extractionBash scriptingLinux
- Implemented a sub-model into an open-source computational fluid dynamics package (OpenFOAM) to simulate a single vapor bubble dynamics in a liquid poolC++Object oriented programmingOpenFOAM
- Developed a Java Plugin to automate image processing to measure bubble sizes for ImageJJavaImage ProcessingImageJ
Teaching Assistant in Mechanical Engineering
Izmir Institute of Technology, Turkey
February 2015 – January 2019
- Conducted recitations and laboratory experiments for Fluid Dynamics and Numerical Methods courses.
- Assisted the professor in evaluating exams, assignments, and experimental reports.
- Provided academic support to undergraduate students, clarifying concepts and solving problems related to fluid mechanics and numerical modeling.
- Facilitated hands-on experiments, ensuring students understood data collection, analysis, and report writing.Fluid DynamicsNumerical MethodsTeachingAcademic Support