Hi, I'm Tuğçe 👋🏻

C++ Software Engineer (Working Student)

• Design and implement operator-facing desktop applications using Qt in C++17/20 on Windows, including both GUI and backend components.
• Define and maintain software architecture for complex desktop applications; ensure scalability, maintainability, and clean separation of concerns.
• Implement RabbitMQ-based messaging for inter-application communication; containerise and deploy services using Docker.
• Own Windows deployment end to end: package Qt applications into release-ready exe/DLL bundles with windeployqt; run always-on background services via Windows services and Task Scheduler; automate WSL2-based Docker environments and startup scripts for reliable unattended operation.
• Maintain CI/CD pipelines via Jenkins and GitHub Actions; write automated unit and integration tests with GoogleTest; enforce quality gates with SonarQube.
• Participate in Agile/Scrum ceremonies; gather and refine requirements with stakeholders; take end-to-end ownership of features from specification through delivery.

R&D Intern – Medical Imaging AI

• Owned a full ML pipeline end-to-end within an international cross-functional team: synthetic dataset generation, preprocessing, augmentation, model training (PyTorch), hyperparameter optimisation, and offline evaluation.
• Designed a denoising autoencoder to post-process 3D U-Net segmentation outputs for cardiac 3D-CTA images; developed post-processing algorithms to reduce surface artifacts and vessel misconnections.
• Adapted quickly to an unfamiliar codebase and domain; delivered results in a medical device development context within the internship window.

Software Engineering Intern

• Developed frontend (GUI) and backend components using the Qt framework on Windows; performed system testing, error analysis, debugging, and peer code reviews. Converted to Working Student role on graduation track.

Research Intern – AI Applications

• Developed CNN, LSTM, and CLSTM deep learning models for audio-based mental health classification using TensorFlow; designed MFCC, mel-spectrogram, and spectrogram feature extraction pipelines with latency constraints.
• Built and shipped a Node.js data collection platform from backend to integrated deployment independently; integrated trained models into web applications for real-world testing.
• Applied systematic data augmentation and preprocessing strategies to improve model robustness and generalisation across diverse audio datasets.

AI R&D Intern

• Developed CNN and ResNet-18/50 models for speaker identification and age/gender prediction from audio signals; engineered MFCC and spectrogram feature extraction pipelines.

Engineering Intern

• Completed Engineering Development Program (MGP) at Turkey's leading aerospace and defence manufacturer; received certified CATIA training and designed 3D mechanical parts.
• Gained foundational experience in aerospace engineering design processes and cross-disciplinary collaboration within a defence and aviation environment.