Junior Computer Engineer skilled in full-stack development and robotics, delivering integrated hardware-software solutions. Proficient in programming, algorithms, and web technologies, with a focus on quality, collaboration, and timely results

October 2024 - Ongoing

AI Training Specialist

As an AI Training Specialist at Outlier.ai, I train AI models using Reinforced Learning with Human Feedback (RLHF) to enhance decision-making and accuracy. My role involves reviewing, optimizing, and improving code in Python, C, C++, Java, Javascript, and SQL, with a focus on efficiency, error-free implementation, and maintainability.

February 2024 - December 2024

SMARTAGE

Sensor-Based Monitoring and Adaptation for Geriatric Environments in real time.
By integrating IoT devices and machine learning models, it collects, analyzes, and responds to data, ensuring personalized and adaptive solutions that enhance the safety and well-being of elderly individuals.
The system leverages advanced positioning algorithms and intuitive dashboards to provide seamless visualization and actionable insights, making it a robust tool for improving quality of life in geriatric settings.

February 2023 - January 2024

Turkish Text Summarizer

Full-stack project that uses NLP techniques, including cosine similarity and PageRank, to generate concise summaries of Turkish texts. It features a scalable back-end for efficient processing and an interactive front-end for user-friendly input and visualization, delivering accurate and intuitive summarization results.

February 2023 - January 2024

Image Processing

The project involved creating a tailored dataset for training machine learning models to detect and classify images. It included developing an automated sorting algorithm, enabling real-time object detection and tracking in videos, and building a comprehensive end-to-end analysis pipeline optimized for accuracy and efficiency across diverse scenarios.

February 2022 - June 2022

Robotics

The Robotics project focused on developing a robotic hand controlled via computer vision, integrating machine learning and image processing. A novel approach was proposed to improve the efficiency of vision-based finger motion control. The work has been submitted for a patent and is set for publication as a research article.