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Asad Ullah

@asadullah1

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Azure-certified Deep Learning Engineer specializing in Computer Vision and AI solutions.

Germany

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What I'm looking for

I am looking for a challenging role in AI where I can innovate and grow.

I am a dedicated Computer Vision Deep Learning Engineer with a strong background in developing innovative AI solutions. Currently, I work at Fraunhofer IDG, where I focus on projects like Strawberry Disease Detection and Autobahn Road Crack Detection. My expertise includes training advanced models such as YOLOX and Faster R-CNN, and I have successfully deployed real-time detection systems using NVIDIA Jetson technology.

Previously, I served as a Research Assistant at Fraunhofer IDMT, where I contributed to sound analysis projects and co-authored a peer-reviewed paper. My academic journey includes a Master’s in Media Technology, where I honed my skills in deep learning and digital signal processing. I am passionate about leveraging technology to solve real-world problems and continuously seek opportunities to expand my knowledge and impact in the field.

Experience

Work history, roles, and key accomplishments

Current

Computer Vision Deep Learning Engineer

Current

Fraunhofer IDG

Jan 2024 - Present (1 year 4 months)

Currently working on projects involving disease detection in strawberries using multispectral and RGB images. Developed and trained models like YOLOX and Faster R-CNN for various applications, including real-time obstacle detection on Jetson Orin. Streamlined workflows and deployed interactive demos for stakeholder validation.

YOLOX Transformers CVAT Gradio TensorRT Linux

Research Assistant

Fraunhofer IDMT

Aug 2022 - Nov 2023 (1 year 3 months)

Conducted research on deep learning methods for sound polyphony estimation. Implemented YOLOv4 for sound analysis and co-authored a peer-reviewed paper. Developed models to improve sound event detection performance significantly.

YOLOv4 OpenCV Python CUDA Deep Learning

Werk Student Deep Learning

SKOR

Feb 2022 - Aug 2022 (6 months)

Worked on automated dart scoring by training YOLOv4 on AWS SageMaker. Developed real-time inference systems for dart detection and scoring, achieving high accuracy.

YOLOv4 AWS Sagemaker OpenCV Linux CUDA

Research Associate

Data Analytics Lab, LUMS

Oct 2019 - Mar 2020 (5 months)

Analyzed electric grid data and classified biomedical signals using machine learning models. Published research on EMG signal classification.

Python Machine Learning Data Analysis EMG Signal Classification Research

Education

Degrees, certifications, and relevant coursework

Technical University Ilmenau

Master's in Media Technology, Media Technology

2020 - 2023

Studied various aspects of media technology including digital signal processing, deep learning, advanced psychoacoustics, image processing, software architecture, and system security.

University of Engineering and Technology Peshawar

Bachelor in Mechatronics Engineering, Mechatronics Engineering

2012 - 2016

Focused on mechatronics engineering with coursework in signal and systems, digital logic design, object-oriented programming, microcontrollers, electric circuit analysis, control systems, and robotics.