Barış Güleç Email & Phone Number

Kütahya, Türkiye

I am the team captain of our project team for TEKNOFEST, TÜBİTAK, and international competitions.

Kütahya, Türkiye

Barselona, Katalonya, İspanya

During my internship at Dpointgroup as an AI Engineer, I worked on several key tasks: Cleaned and pre-processed the data provided by the company, transforming it into a suitable format for further use. Fine-tuned a language model to develop a custom chatbot for the company. Additionally, I created an automation tool using JavaScript, which automated tasks that were previously done manually, significantly improving efficiency.

1. Computer Vision Section: In the computer vision project, precise bounding box calculations were performed using YOLOv10 for mass and calcification detection, and the data was prepared for training. A high-accuracy object detection model was developed using YOLOv10 after two weeks of extensive training, specifically for mass and calcification identification. A CNN-based classification model was designed to predict BI-RADS categories, with accuracy improved through prolonged training. The object detection and classification models were integrated into a threaded system, enabling real-time predictions. The integrated system automatically detects lesions and performs classification on new incoming data, providing real-time inference.2. Natural Language Processing (NLP) Section: Data Preparation and Cleaning: BI-RADS reports were categorized (1-5), with DICOM images converted to PNG. Using Llama 3, text errors were corrected, and additional BI-RADS 1 reports were generated to balance the dataset, followed by Mixtral validation to confirm data quality. Model Development: Logistic Regression and Random Forest models were trained using TF-IDF for vectorization, with GridSearchCV optimizing Random Forest’s hyperparameters. The final model was selected based on accuracy and F1 scores. NER for Medical Entities: With Llama 3 for final text refinement, an NER model was developed using Spacy, achieving high accuracy in identifying anatomical and clinical terms. Evaluation: The optimized Random Forest model reached an F1 score of 0.92, indicating high precision across models.

Bursa, Türkiye

I worked as a freelancer and managed the setup and maintenance of three different websites on WordPress. My curiosity that started in high school helped me gain experience in this field.

Engineer'S Degree, Computer Engineering, Ösym Puanımı Kullanarak Yatay Geçiş Yaptım (Myp)

Lisans Derecesi, Preparatory School

I have completed the English preparatory school of the European University of Lefke.