Computer Engineer
From visual data to intelligent systems.
Computer engineering graduate working across machine learning, computer vision, and embedded software.
I am a computer engineer and recent graduate of Middle East Technical University Northern Cyprus Campus. I am especially interested in machine learning, deep learning, computer vision, and the software systems that make intelligent applications practical.
Through individual projects, internships, and teaching experience, I have worked with object detection, neural networks, PID-based tracking, ROS integration, and embedded software. I am looking for a junior engineering role where I can contribute to real products while continuing to strengthen my technical skills.
March 2026 - June 2026
Middle East Technical University Northern Cyprus Campus
September 2025
VISEA
July 2025 - August 2025
HAVELSAN
August 2024 - September 2024
Desird Ar-Ge A.S.
Work in computer vision, neural networks, machine learning, and autonomous systems. Explore the problem, approach, and engineering decisions behind each project.
A real-time video-analysis system that detects and tracks pedestrians and vehicles, evaluates their position against a user-defined region, and counts passing vehicles.
The system combines YOLOv8 detection with ByteTrack tracking so objects retain consistent identities across video frames. Users define a four-corner region of interest, allowing the application to distinguish pedestrians inside and outside the area and count vehicles without repeated detections.
It supports webcam, single-video, and batch processing, with configurable model settings, color-coded overlays, tracking IDs, vehicle counts, and FPS monitoring.
Converted a MobileNetV4 image classifier into a Leaky Integrate-and-Fire spiking neural network for ship detection in satellite imagery.
ReLU activations were replaced with calibrated LIF neurons, BatchNorm parameters were folded into convolution layers, and classification was performed through accumulated output spikes. Channel-wise thresholds helped account for different activation ranges across the network.
The ANN baseline reached 95.88% accuracy. The converted SNN reached 95.00% at 128 timesteps and 95.75% at 256 timesteps. The project also exports model artifacts for hardware-oriented implementation.
Built a complete machine-learning pipeline and custom support vector machine for next-day energy-consumption and air-pollution classification.
The project transforms hourly measurements into daily time-series features and implements the SVM dual optimization problem with a quadratic-programming solver. It compares linear, RBF, polynomial, and custom trend-aware kernels using cross-validation.
The work reinforced an important modeling lesson: accuracy alone was misleading for the imbalanced pollution dataset, so recall and F1 were necessary to compare models responsibly.
Built a compact vision-language model that matches images of concatenated MNIST digits with English text descriptions.
Three digit images are combined and paired with captions such as “one hundred twenty-three.” A pretrained ViT-Tiny image encoder and DistilBERT text encoder project both modalities into a shared embedding space trained with SigLIP contrastive loss.
The project covers multimodal dataset generation, frozen pretrained encoders, trainable projection heads, contrastive training, and Top-1/Top-5 retrieval evaluation.
PID-based target tracking, ROS communication, and computer vision integration for an unmanned aerial vehicle system.
Designed and implemented a PID-based tracking algorithm to follow target UAVs in real time, synchronizing motion dynamics with sensor feedback.
Built modular communication between onboard subsystems using ROS and integrated target detection with the flight control stack for real-time edge processing during combat simulations.
2021 - 2026
Middle East Technical University Northern Cyprus Campus
GPA: 3.722024 - 2026
Middle East Technical University Northern Cyprus Campus
GPA: 3.68I am interested in junior opportunities in machine learning, computer vision, software engineering, and embedded software. If my background fits your team or project, feel free to contact me.