I grow seeing machines — embedded systems that watch fields for pests, follow targets across rough ground, and learn the shape of the world from a Raspberry Pi.
I am a final-year Electrical & Electronics Engineering student at İzmir Democracy University, working at the soft seam between embedded hardware and computer vision. I find the richest problems on the boundary — where a sensor meets a model, where a model meets the dirt of a real field.
For three years I have been building seeing machines: ground control stations for autonomous vehicles, real-time perception for UAVs, and edge-deployed YOLO pipelines that watch crops for pests. I lead student teams, ship to deadlines, and prefer prototypes over promises.
ekenturkueylul@gmail.com · +90 539 588 2267
A herbarium of working prototypes — autonomous vehicles, edge-deployed perception, wearable safety devices. Pressed and labelled.
A camera-based detection system that flags pest activity early — reducing pesticide use and field-scouting labour. Built the full image-acquisition pipeline and trained a YOLO model on 56,000+ annotated samples, currently achieving 92% mAP on the validation set. Targeting deployment on edge hardware (Raspberry Pi 5).
A 500 kg, tracked, 2×1.5 kW BLDC autonomous platform. I own the computer-vision stack — perception with YOLOv26, OpenCV trackers for frame-to-frame target/sign following — running at 60 FPS, 1080p, on the Pi 5 onboard. Also contributing to the Ground Control Station: live video, GPS telemetry, vehicle status, manual override over a redundant WiFi + GSM link.
Co-developing an 8 kg autonomous combat UAV with a variable-sweep wing — back-swept for high-speed dashes (210 km/h target dive), forward for slow-speed loiter; T/W 1.34. I own the YOLO training pipeline, post-detection tracking algorithms, and the GCS interface of the CV stack. All tested first in a ROS 2 + Gazebo simulation.
Co-designed a mobile app delivering location-based recommendations and personalised itinerary planning across Northern Cyprus. Owned the UI/UX and integrated Maps API for geolocated points of interest.
A wearable drowsiness-detection device. Prototyped on the Pi Pico W with IR sensors that trigger audio alerts on prolonged eye-closure. Wrote firmware in C++ and a configuration utility in Python; designed and assembled the supporting circuit by hand.
An OpenCV pipeline — pre-processing, contour detection, polygon approximation — to classify hand-drawn shapes from a webcam feed in real time. Tuned thresholding and noise-reduction parameters to keep classification stable under variable lighting.
İzmir Democracy University
Signals & Systems · Microprocessors · Control Systems · Digital Image Processing · Data Analysis · Machine Learning.
Bahçeşehir College, İzmir South Campus
Engineering Project Development Community · İzmir Democracy University
Led a student team developing applied engineering projects. Organised technical workshops, mentoring sessions, and project reviews. Grew active membership from zero to 400+ and shipped 7 internal projects across the academic year.
I am open to R&D and embedded-engineering opportunities — especially where computer vision meets the physical world. Reach out, and I will reply with the same care I bring to a soldering iron.