Developed and implemented an autonomous driving feature enabling path planning and V2X communication in a 1:14 scale driving environment. Utilized a hall-mounted camera system with computer vision algorithms for vehicle localization and trajectory tracking. Created a track-specific dataset and trained a YOLO-based deep learning model for real-time object detection. Integrated a Kalman filter for object tracking and state estimation, enhancing detection stability and temporal consistency across frames.
NM
Noushiq Mohammed K
- Stuttgart, Germany
- 1 project
I am a versatile, analytical, and impact-driven engineering professional specialized in autonomous driving technologies and software development for intelligent mobility systems.
About
I am a versatile, analytical, and impact-driven engineering professional specialized in autonomous driving technologies and software development for intelligent mobility systems. With a strong foundation in computer vision, deep learning, data engineering, and software engineering, I have worked on hands-on projects that advance cutting-edge mobility solutions, currently being honed through my master’s program with a focus on AI integration in automated driving.
My experience spans designing and implementing multi-modal perception systems, managing large-scale data annotation pipelines, and leading cost data analysis projects. I have also contributed as a requirements engineer collaborating closely with developers to deliver functional modules ahead of schedule. Fluent in multiple programming languages and tools, I am passionate about leveraging technology to create smarter and safer autonomous vehicles.
- Joined September 2025
Languages
- EnglishFluent
- GermanIntermediate
- MalayalamFluent
- HindiIntermediate
- TamilIntermediate
Industry experience
- Computers & Electronics
- Healthcare
- Manufacturing
- Transportation & Logistics
- Professional Services
Projects · 1
Work experience· 6 roles
Master Thesis · Institute for Intelligent SystemsMar 2025 – Present · 1 yr 9 mos
Advancing multi-modal perception for LLM-based end-to-end autonomous driving by analyzing and evaluating LLM and multi-modal perception autonomous driving systems architecture, datasets, and training. Designed a method to integrate traffic light and sign ground truth data from CARLA through Python API to enhance LLM decision making. Developed a perception stack with a deep learning-based traffic light and sign recognition model and generated a dedicated traffic sign dataset for a closed-loop simulation system. Experienced in working with high-performance computing clusters and managing batch job scripting and Slurm workload management.
Working Student · Robert Bosch GmbHSep 2024 – Present · 2 yrs 3 mos
Provided active learning support for the lane detection model by improving data annotation and quality assurance processes for autonomous driving model training. Collaborated with labelers to optimize the pipeline for image data containing around 2 million frames. Created and refined labeling quality review documents for platforms such as Kognic, Telus, and Deepen AI, reducing systematic labeling errors by 20%.
Engineering Consultant (Part-Time) · EmuskiAug 2023 – Sep 2025 · 2 yrs 2 mos
Proactively collaborated with developers as a requirements engineer to design, develop, and test eight costing functional modules, delivering them two weeks ahead of schedule, significantly streamlining the software.
Cost and Data Analyst · General ElectricAug 2023 – Sep 2025 · 2 yrs 2 mos
Engineering Analyst · Advanced Structures IndiaDec 2021 – Sep 2025 · 3 yrs 10 mos
Graduate Apprentice Trainee · Bharat Heavy Electricals LtdNov 2019 – Sep 2025 · 5 yrs 11 mos
Education
M.Engg in Automotive Systems · Hochschule Esslingen2023 – 2025
B Tech in Mechanical Engineering · University of Calicut2014 – 2018
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