I have 3+ years of professional experience in research, development, and integration of deep learning based computer vision solutions. I have worked on object recognition, semantic segmentation, and image classification projects. My aim is to create valuable solutions and make contributions to field of machine learning and deep learning.
Senior Computer Vision Engineer • August 2022 - Present
- Designing and implementing solutions for computer vision problems.
Computer Vision Engineer • July 2021 - July 2022
- Analysis of AI research papers for healthcare.
- Development of disease diagnosis systems with deep learning models such as RetinaNet, YOLO, Faster R-CNN.
- Deployment of the models via Amazon Web Services with Docker Images.
R&D Engineer • October 2019 - July 2021
- Have been working on an deep learning based OCR project for Cal Lab Solutions, Inc who is the project partner of Spark Calibration Service . It detects and recognizes measurement value on the measurement devices. YOLOv3, Tesseract, OpenCV, Numpy, PySide2 and Flask are utilized for the project.
- Responsible for the development of the SparkS script language in a research team consisting of electronics and computer engineers. It is used to create test procedures for calibrating RF and Microwave devices. Cooperating with the National Measurement Institute of The Scientific and Technological Research Council of Turkey for the project. .NET, Python, SCPI and ANTLR are used for the project.
- Developed a data processing program to be used in-house. It basically take big excel files as input and output a Excel and CSV files after specific processes. Numpy, Pandas, Numpy and PyQt5 were utilized for the project.
Machine Learning Engineer Intern • November 2018 - March 2019
- AI-SOLT supported the final project that is mini autonomous car prototype of my team. We redesigned a RC Car electronic circuits and used Raspberry Pi 3 B+ to drive it. Was responsible to development of E2E CNN model. OpenCV, Tensorflow, Keras, Numpy were used for the project.
- Have worked on ingredient recognition task. In this task, scientific articles were analyzed and developed machine learning models. BagOfTextons, SIFT, unsupervised learning and supervised learning techniques were utilized for the project. Numpy, openCV, scikit-learn, pandas and matplotlib libraries were used for the project.
Full Stack Developer Intern • July 2017 - September 2017
- Have developed a new website for the Tetraport Technology. I designed the front-end and developed the back-end of the new site, set-up the server and database. I used HTML, CSS, JS, bootstrap, ASP.NET and MSSQL for the project.
Master in Computer Engineering • July 2019 - January 2023
Master thesis: Segmentation of Fetal Brain Tissues Using Deep Learning
BSc Degree in Computer Engineering • September 2014 - June 2019
The final project of my team was on deep learning based autonomous car.
BSc Degree in Computer Engineering • February 2018 - June 2018
I have visited TBU as an Erasmus exchange student.