Robotics Software Engineer & M.Sc. Computational Materials Science
I build autonomous systems that work in the real world — behavior tree mission planners, Nav2 integration, and the backend APIs bridging robots and operators. Based in Dresden, Germany.
Backend Engineer & M.Sc. Computational Materials Science
I design and ship production-grade backend systems — REST APIs, microservices, CI/CD pipelines, and the integration layer between software and physical hardware. 27 delivered projects, 100% success rate.
ML Engineer & M.Sc. Computational Materials Science
I apply machine learning to real engineering problems — materials microstructure modelling, FEM simulation, and computer vision pipelines on autonomous robots. Research-backed, production-minded.
Robotics software engineer and master's student at TU Bergakademie Freiberg, specialising in Computational Materials Science — ML for materials and finite element simulation.
My work sits at the intersection of autonomous systems and backend infrastructure — mission logic that decides what a robot does, and the APIs that let humans monitor it in real time. Most recently at EnQineering GmbH: full UGV software stack in ROS2, behavior trees, Nav2, REST/ROS2 bridge, Gazebo simulation tools.
Backend engineer with 6+ years of shipping production systems — genealogy platform data infrastructure, IIoT dashboards for industrial robots, and a REST/ROS2 integration layer for an autonomous UGV. 27 Upwork projects, 100% Job Success Score.
I'm comfortable with the full backend stack and particularly strong at the hardware-software boundary where most backend engineers stop — writing the API layer that a physical robot actually talks to.
ML engineer and master's student at TU Bergakademie Freiberg — research focus on machine learning for materials science, training models on microstructure data and integrating ML with FEM pipelines.
On the applied side: computer vision for autonomous robotics — OpenCV anomaly detection and YOLOv8 on ROS2, sensor fusion (GPS + IMU), and signal processing (PID/LQR controllers, DSP estimators) from applied Upwork work.
Full software stack for an autonomous fire-fighting UGV in ROS2 Jazzy. Behavior tree mission layer (BehaviorTree.CPP) — task sequencing, fallback logic, reactive replanning. Nav2 path planning, REST API ↔ ROS2 bridge, Gazebo simulation with sim/real mode switching. Code under NDA.
Backend integration layer for an autonomous ground vehicle — REST API bridge between mission control and the ROS2 runtime, JWT-authenticated mission dispatch, WebSocket telemetry, ReactJS operator dashboard. CI/CD pipelines and automated testing infrastructure.
Computer vision pipeline on a deployed UGV — camera-based fire detection feeding into a ROS2 behavior tree via OpenCV. Sensor fusion layer combining GPS, IMU, and lidar into the Nav2 costmap. Real-time inference constraints on embedded hardware.
Robotic arm manipulation with UR5, Dobot CR5, and SJ602-A. Pick-and-place sequences, multi-robot TCP/IP coordination, trajectory planning with MoveIt. Fixed ROS Noetic compatibility issues in the official CR5 repository (original code only worked on Melodic). Proposed and partially implemented an interface redesign for the SJ602-A. Taught ROS workshops to 20+ students.
Built the backend from scratch for a genealogy research platform — data mining infrastructure with rotating proxy systems for public historical registries at scale, REST + GraphQL APIs, ReactJS frontend, CI/CD pipelines.
27 completed projects, 100% Job Success Score. Automation, scientific computing, full-stack. PID/LQR controllers in MATLAB (4.8★), multi-signal DSP estimator, gRPC client in Java (5.0★), browser automation suites for UK clients, data scraping pipelines.
Autonomous patrol robot with reactive BT mission planning, Nav2, camera-based anomaly detection (OpenCV + YOLOv8), GPS/IMU telemetry, and sim/real switching.
Lightweight browser-based visualizer for BehaviorTree.CPP XML files. Live XML editor, pan/zoom canvas, vertical/horizontal layout, minimap, node search. Zero dependencies. Single HTML file. Alternative to Groot2 without any install.
Async Python SDK for industrial robot arm control via ROS2. Built from real CR5 and UR5 fiber composite layup work at NUST (2023–2024). Currently migrating from ROS1 Noetic to ROS2 Jazzy — this is v0.1.0 of that migration.
TurtleBot3 navigation and autonomy stack implemented for ROS2 Jazzy. Part of a structured robotics learning roadmap: TurtleSim → TurtleBot3 → Husky + custom packages → multi-robot cooperation.
End-to-end robotics project implementations from idea to product. A living collection covering system design, embedded control, ROS2 integration, and deployment — the full journey from concept to working hardware.
A domain-specific language for industrial robot arm control. Readable by non-roboticists. Maps cleanly onto real motion primitives (MOVJ, MOVL). Intent is separate from execution — every motion is kinematically proven before it reaches hardware. Derived from hands-on CR5 and UR5 layup work at NUST.Intent → Admission → Kinematic Proof → Execution → Supervision
Pick-and-place layup sequences with Dobot CR5 and SJ602-A arms in ROS Noetic and Melodic. Multi-robot TCP/IP coordination with MoveIt and MoveGroup. Fixed Noetic compatibility bugs in the official CR5 repository — original code only functional on Melodic. Includes documentation.
Original ROS1 Noetic codebase for the CR5 fiber composite layup sequences at NUST. Cartesian-space motion planning, MoveIt trajectories, multi-robot TCP/IP coordination. Direct ancestor of the robolink SDK.
ROS Melodic simulation — TIAGo picks coloured objects from one table, places them on different tables by colour. Variations include: object detection + avoidance with Octomap, multi-room navigation, and Aruco marker detection. A lengthy, complex project covering perception, manipulation, and planning end-to-end.
Autonomous vehicle competition using the Carla simulator with a ROS bridge. Full navigation pipeline: camera and lidar integration, path planning, vehicle control logic. Carla experience is uncommon and directly relevant to ADAS and simulation engineering roles.
Advanced Driver Assistance System for an urban concept race car. Ran on Raspberry Pi 4, displayed live GPS map on a 7-inch screen alongside fuel metrics and vehicle telemetry. Key challenge: correctly placing the location marker on a custom map of the Indonesian competition circuit. Built with Python Qt.
Winnow your AI chat history — view, search, and prune exported conversations from Claude and ChatGPT in one offline HTML file. No server, no install, no account. Drop your exported JSON, cut the dead ends, export clean context. Everything runs locally — your data never leaves your machine.
Bio-inspired MAV with a flapping wing mechanism — 22g including embedded control electronics. Full mechanical design, fabrication, and MCU-based servo control. Achieved stable controlled flight. At 22g, structural resonance and power density are the dominant engineering constraints.
Two-axis camera-enabled car with WiFi and Bluetooth control. ESP32-CAM module provides live video feed. Control via WiFi and Bluetooth. Two-axis camera gimbal for remote viewing. Designed as a wireless surveillance platform.
Arduino UNO-controlled motor car receiving instructions from an ESP8266 over WiFi. Demonstrates serial communication between a WiFi-capable module and a microcontroller, and remote command parsing over a local network.
Home automation project using an ESP8266 for WiFi-connected light control. Remote switching and scheduling over a local network. A practical introduction to IoT architecture: device firmware, local network protocol, and simple control interface.
RC 2-wheel drive robot built on Arduino UNO. Wireless control via radio module. PWM motor speed control and steering logic. One of the foundational embedded projects that led to more complex autonomous systems work.
Autonomous line-following robot with IR sensor array and PID-based motor control. Tuned for smooth curve following at speed. A classic control systems problem in hardware — the same PID logic that appears in motor controllers and flight controllers.
Fast C directory tree viewer for Linux and Windows with smart grouping of numbered files. Built for developers who work with large codebases and simulation output directories. Cross-platform, dependency-free, single binary.
Full-stack ESG reporting tool — enter GHG emissions data, visualise scope breakdowns, generate AI-powered reduction strategies, and export a branded PDF report. Built with Next.js 15 (App Router), SQLite, Zod validation, Recharts, and GPT-4o for strategy generation.
Browser-based spreadsheet for language learning and vocabulary recording workflows. Upload a word list, record or play back pronunciations per row, and download individual audio clips. Built for hiring freelancers to record how they pronounce words — each row is a word, each action cell a micro-studio.
PID and LQR controller implementations, double pendulum simulation, and a multi-signal DSP estimator — delivered as Upwork projects with 4.8–5.0★ ratings. Directly applicable to robotics control, embedded signal processing, and sensor fusion.
Solid State Physics · Semiconductors · Thermodynamics · Finite Element Methods · ML for Materials · Microstructure Modelling.
Control systems · Robotics · Mechatronics · Fluid dynamics. Final project: 22g flapping wing ornithopter. Shell Autonomous Programming · Shell Eco Marathon international competitions.