KI / ML · Robotik · ROS2 · Gazebo · Computer Vision
Raja Hammad Naseer
KI- & Robotik-Systeme — von der Wahrnehmung bis ins Produkt.
M.Sc. Computer & Systems Engineering student building AI/ML systems and ROS2-based autonomous-vehicle architectures with real-time perception — and integrating them into full-stack products that actually ship.
M.Sc. Computer & Systems Engineering student with industry experience in AI/ML systems, software engineering, and technical project collaboration. Experienced in developing and integrating complex software systems — including ROS2-based autonomous-vehicle architectures and real-time perception pipelines. Strong analytical mindset with an interest in systems engineering, structured problem solving, and interdisciplinary technical coordination.
0+
years full-time industry experience
0
production systems shipped & live
0
web apps with zero downtime
C1 · B1
English · German Urdu native
02
Fähigkeiten / Capabilities
Drei Felder
full-stack + AI
A / Robotik
Robotics & Autonomy
ROS2-based autonomous-vehicle architectures, real-time perception and multi-object tracking — designed and validated in Gazebo simulation.
ROS2Gazebo SimOpenCVYOLOv8
B / KI
AI / ML Engineering
Computer-vision inference, RAG pipelines and LLM agents — from model integration to deployable services.
PyTorchONNXRAGLangChain
C / Integration
Full-Stack Integration
React + Node + Docker, end to end — so the models and pipelines actually ship as real products under production load.
React/NextNode.jsRESTDocker
03
Ausbildung & Forschung / Education
In der Forschung verwurzelt
control · CV
Okt 2025 — heute · Deutschland
M.Sc. Computer & Systems Engineering
Technische Universität Ilmenau
Note 1,3 · Research Seminar
TEC Cooling Control
Modelled a TEC system (PT2 + dead time), identified parameters via open-loop step test, and tuned a PID controller with anti-windup on Arduino. Rise time 34 min, steady-state error <0.3 °C.
Laufend · SS2026 Group Study
Modular ROS2 Autonomy
Designing a modular autonomous-driving architecture with defined subsystem interfaces for perception, control and safety — coordinating multi-agent interaction in Gazebo Sim.
Note 1,3 · Research Skills
UAV Multi-Object Tracking
Built a real-time tracking pipeline and benchmarked ByteTrack vs. Norfair on MOTA, ID-switch rate and FPS across simulated UAV flight maneuvers.
2019 — 2023 · Pakistan
B.Sc. Computer Science
SZABIST
04
Ausgewählte Arbeit / Selected Work
Dinge, die live gingen
6 systems
01
▸ AI · Retrieval / Backend
Air-Gapped Semantic Search Engine
Three microservices — an ONNX embedding service (~3× faster on CPU), HNSW vector search returning the top-30 in ~10 ms, and a cross-encoder reranker for top-10 precision. Fully local, no external APIs.
A React.js dashboard + Node.js/Express REST API + MongoDB, deployed via Docker across multiple live camera installations. The backend integrates a YOLOv8/ONNX inference service for real-time face recognition and whitelist state management.
ReactNode.jsExpressMongoDBDockerYOLOv8ONNX
Live · multi-sitePrivate · NDA
03
▸ Fullstack · Computer Vision
WorkAI — Industrial AI Monitoring
A full-stack monitoring platform: a React.js real-time dashboard, Node.js REST APIs and MongoDB event logging, all containerised with Docker. Pose-estimation and face-recognition pipelines are exposed as backend services.
A full-stack student marketplace built from scratch: user profiles, listings, search, filtering, an admin panel and a responsive UI — validated through user interviews with TU Ilmenau students.
Upload multiple CVs and paste a job link or description — CoverCare analyses your experience against the role and generates a tailored cover letter, then exports it as a polished PDF. Dual AI engine: Gemini 2.5 or local Llama 3.2 via Ollama.
An LLM agent with dynamic tool use: live web-search grounding, chain-of-thought reasoning, and structured argument / counter-argument output with citation tracking.
Delivered 3 production web applications with zero reported downtime — architecting full-stack Node.js/React.js systems and owning Docker-based CI/CD pipelines from first commit through release.
Eliminated manual customer-support bottlenecks by building a RAG pipeline, engineering the prompt chain, and integrating it via REST API into the existing web infrastructure.
Shaped the company's AI tooling strategy by benchmarking competing LLM frameworks and presenting findings — adopted directly into the production stack.
2023 — 2024 · Pakistan
Artificial Intelligence Engineer
VisionTech360
Shipped EMACS — a full-stack access-control platform — to production across multiple live camera installations: React.js dashboard, Node.js/Express REST API, MongoDB event store, all containerised with Docker.
Designed a concurrent multi-stream backend handling simultaneous video feeds with real-time whitelist state management and timestamped event logging — exposed cleanly to the frontend over REST.
Owned the deployment lifecycle from proof-of-concept to production; integrated YOLOv8/ONNX inference as a backend service with a repeatable Docker release workflow.
