Portfolio / 2026
SENSORS IN STREETS · PIXELS IN POCKET
Made by one. Shipped to many.
I'm Halid, an embedded systems engineer turned independent builder. From April 2024 to April 2026 I worked at Ekin Smart City Technologies in Ankara, a global smart-city company headquartered in Türkiye, fusing radar, LiDAR, and camera data into real-time traffic systems running on NVIDIA Jetson edge hardware.
Since 2026 I'm in Karlsruhe, pursuing a Computer Science master's at KIT and shipping iOS apps on the side. Small, opinionated tools for everyday problems. The work on this page sits at the seam where sensors meet screens.
/ Toolbox
Embedded · Vision
C/C++ · Python · NVIDIA Jetson · OpenCV / YOLO · Kalman / EKF · IMX678 · MIPI · V4L2 · ANPR · Embedded Linux
App · Web
Swift / SwiftUI · React Native · Next.js
Quality
ISTQB Tester
For roles, the long version with dates, employers, and references. Always available on request.
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AI language coach for medical professionals.
Specialized prep for IELTS, TOEFL, Goethe and the German Fachsprachenprüfung (FSP). Roleplay patient anamnesis with AI, present cases to an AI Oberarzt, and get instant feedback on Arztbriefe.
/ Also on macOS
Your Mac's vitals, dropped from the notch.
Your MacBook notch, turned into a Dynamic Island.
Tap a module ↑
Protect your Mac and your private files — with your face.
/ Also on the web
50+ cities · 4 continents · radar / LiDAR / cameras
From April 2024 to April 2026 I worked at Ekin Smart City Technologies in Ankara, a global smart-city company shipping license-plate recognition (ANPR), traffic, and public‑safety systems, fusing radar, LiDAR, and camera data into real-time pipelines on NVIDIA Jetson edge hardware.
The work taught me how data, hardware, and policy interlock to make a city function, and where the elegant theory of an algorithm meets the gritty reality of weather, dust, and a camera that drifts six degrees over a week.
/ Where I worked
ANPR, traffic management platforms, and the orchestration that keeps a city moving.
Camera networks, video analytics, and the hard edge cases that come with deploying them at scale.
Sensor telemetry, real-time pipelines, and the unglamorous work of turning noise into signal.
Detection, recognition, and edge inference: where models meet the constraints of real hardware.
/ Selected case studies
Real-time vehicle speed detection and tracking by fusing radar, LiDAR, and camera data with an Extended Kalman Filter. C++ on NVIDIA Jetson, weather-resilient.
Real-time ANPR for embedded devices. Optimised YOLOv5 and YOLOv8s models for Jetson Nano with TensorFlow Lite. The kind of system that lives outside the lab, in real weather and real traffic.
Python tooling for temporal and spatial calibration between 77 GHz mmWave radar and IP camera systems. NTP for inter-sensor sync, robust enough to deploy across crews.
Bring-up and tuning of IMX678 MIPI camera modules on NVIDIA Jetson: colour, exposure, gain. Managed JetPack lifecycle across the device fleet, wrote Linux systemd services for the edge runtime, and integrated robotic peripherals.
Currently exploring roles where this experience matters. Engineering, product, or the messy space in between.
Get in touch/ Archive
Open to roles in mobile, smart-city, or product, and to projects and collaborations that don't fit a label. Drop a note, even if it's just to say hi.
Ask Halid
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