Muhammad A.

Key Skills

Software

Don't disclose

Other

Top Subject Matter

Industrial automation & SCADA systems

Web scraping & data extraction

AI agents & RAG systems

Top Data Types

3D Sensor

Document

Image

Top Task Types

Data Collection

Function Calling

Freelancer Overview

Junior Data Scientist, covolv.ai (data validation and 3D perception model development). Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose, Other, and EasyOCR. Education includes Master of Science, Universita degli Studi di Milano-Bicocca (2023) and Bachelor of Science, National University of Computer and Emerging Sciences (2021). AI-training focus includes data types such as 3D Sensor and Document and labeling workflows including Evaluation, Rating, and Data Collection.

Labeling Experience

Electrical and System Design Engineer, A176lab (AI-enabled OCR extraction and anomaly validation in monitoring pipeline)

DocumentFunction Calling

Led the engineering of an industrial multi-source monitoring system that consolidated heterogeneous platform data for automated production, fault, and tracker reporting. Implemented OCR-based digitization to extract tracker readings unavailable via APIs, including validation to flag anomalies before storage. Normalized extracted and ingested data into a consistent schema and powered live dashboards with automated notifications for stakeholders. • Performed OCR digitization of tracker readings from interfaces • Added validation checks to detect anomalous extracted values • Integrated multi-source extraction and normalization into pipelines • Delivered live monitoring outputs that support automated alerting

2025 - Present

Automation and Quality Control Engineer, TecnoEuro SRL (AI-driven quality pipelines)

OtherDocumentData Collection

Created data-driven quality control pipelines and integrated AI-guided process control into robotic manufacturing systems. Worked with industrial data streams to improve consistency and reduce rework by incorporating automated AI-informed decision logic. While explicit human labeling is not stated, the role involved preparing and leveraging structured quality-control datasets for AI-guided operation. • Built/curated datasets for quality-control decision support • Integrated AI-guided control logic into manufacturing processes • Improved consistency by monitoring and using data signals • Supported evaluation of process outcomes using collected metrics

2023 - 2024

Junior Data Scientist, covolv.ai (data validation and 3D perception model development)

Don't disclose3D Sensor

Built data validation pipelines for large-scale sensor and image inputs used in autonomous vehicle workflows. Developed 3D perception models with PyTorch and PointNet to learn from processed 3D point data and related imagery. Implemented validation logic to improve data quality prior to model training and downstream use. • Validated and filtered sensor/image-derived training data quality • Prepared data for 3D perception modeling (point-based inputs) • Supported model training and evaluation readiness • Used anomaly/consistency checks to reduce label noise

2021 - 2022

Education

Work History