Uğurcan Akyüz

Master's in Computer Engineering

2019 - 2023

Erciyes University, Kayseri, Türkiye

Thesis Title: Fetal Brain Tissue Segmentation Using Deep Learning

Context: To segment fetal brain tissues precisely and efficiently, state-of-the-art 3D segmentation models and patch-based training approaches have been researched. A new 3D U-Net model based on dilated convolutions has been developed. GitHub link of the project

Bachelor's in Computer Engineering

02 - 06/2018

Thomas Bata University, Zlin, Czech Republic

Program: Erasmus+ Student Exchange Program Student

Bachelor's in Computer Engineering

2014 - 2019

Erciyes University, Kayseri, Türkiye

Final Project: Mini Self-Driving Car Prototype

Task: Development of perception module for self-driving.

Computer Vision Engineer

08/2022 - Present

ICterra, Ankara, Türkiye

• Working on image classification task. Developing a computer vision solution using more than 100,000 images with deep learning models.
• Achieved an average PR-AUC score of 0.88 across different datasets. Currently addressing the domain shift problem.

Computer Vision Engineer

07/2021 - 07/2022

Akgun Technology, Ankara, Türkiye

• Worked on a real-time medical object detection project. Developed and packaged a deep learning system that reached a score of 0.86 mAP running at 22 FPS on the GPU.
• Contributed to the migration of on-premise machine learning solutions to AWS, leveraging cloud capabilities for enhanced efficiency and performance.

Research and Development Engineer

10/2019 - 06/2021

Spark Calibration Services Inc., Ankara, Türkiye

• Development and deployment of automatic measurement recognition software using deep learning. RESTful service has been implemented to be integrated with Metrology.NET.
• Developed a data processing program, reducing the processing time for large Excel files from 45 minutes to just a few minutes.
• Development of the SparkS script language (DSL) that is used to calibrating RF and Microwave devices.