-Led the development of an AI-based performance measurement tool by using Machine Learning and Deep Learning libraries in Python.-Managed data processing, established data pipelines, and crafted AI models within the Microsoft Azure environment.-Delivered valuable business insights by extracting complex relationships within data.-Achieved the successful completion of a project within a defined timeline, focusing on details such as requirements/specifications definition, model development, and thorough testing.-Developed and executed optimization strategies for "scheduling" and "training recommendation" tools , leading to improved accuracy and performance.

-Designed and evaluated deep-learning-based spoofer detection classifiers with PyTorch, Pandas and Numpy in Python,-Developed both a baseline model and a Neural Network to detect wireless spoofers,-Led the Physical Layer Security part of a National Leader Researchers Program of TUBITAK,-Performed an extensive literature search on deep learning and machine learning models with a focus on anti-jamming, anti-spoofing, and anti-eavesdropping applications, resulting in the publication of a comprehensive survey

-Contributed to the design and development of data-driven anti-jamming military communication systems,,-Played a key role in the project "Index Modulation based Anti-jamming and Anti-spoofing System Design",-Led the comprehensive literature search on various anti-jamming techniques,-Designed and developed Index Modulation (IM) based anti-jamming communication models,-Used MATLAB to perform data-driven simulations and evaluate the jamming detection performance of the proposed models.