Diogo Campas
Computer Vision and Machine Learning Engineer @ Infinite Foundry
About
Computer Vision and Machine Learning Engineer with a background in Electrical and Computer Engineering, driven by the challenge of turning AI ideas into systems that work reliably in the real world. Experience includes real-time computer vision, machine learning and AI-driven automation, with a strong focus on building and deploying solutions that make it past the prototype stage. Balances strong theoretical foundations with hands-on engineering across the full AI lifecycle, from data and model development to deployment and continuous improvement. Works closely with cross-functional teams, bringing clear communication, practical problem-solving and a collaborative approach to ensure technical work supports real product needs. Beyond technology, has played competitive football since 2007 at district and national levels, an experience that shaped discipline, resilience and a strong sense of commitment to the team.
Portugal
Santa Maria da Feira
Computer Software
Python (Programming Language), Resolução de problemas, Generative Adversarial Networks (GANs), Software Development, Point Clouds, Object Detection, Object Tracking, OpenCV, Agile Methodologies, English, Electronics, Data Analysis, Image Analysis, SQL, Git, Research Skills, Image Processing, C (Programming Language), PyTorch, Deep Learning
Experience
Computer Vision and Machine Learning Engineer
Infinite Foundry
Porto, Portugal
Designed and deployed real-time computer vision systems for industrial and sports-related applications, using deep learning models for object detection, tracking, classification, and 3D human pose estimation. Applied computer vision and geometric analysis techniques to extract actionable insights from video and 3D data, including point cloud processing and spatial measurements to support automation, analytics, and decision-making. Collaborated closely with cross-functional teams, including industrial and product engineers, to integrate AI-driven solutions into real-world workflows, improving efficiency, safety, and overall system reliability.
Research Assistant
INESC TEC
Porto, Portugal
Research on generating synthetic 3D medical imaging data using advanced deep learning generative models, with a focus on improving data quality and clinical relevance. Worked alongside clinicians to evaluate model outputs and assess clinical applicability, bridging technical development with real-world medical imaging needs.
Summer Internship
INESC TEC
Porto, Portugal
Summer internship in Centro de Telecomunicações e Multimédia (CTM) at INESC TEC Development and study of Deep Generative Models for Breast MRI images augmentation
Student Intern
Bosch Portugal
Ovar, Aveiro, Portugal
Integration of a new sensor into a development board for IoT devices and its integration into a Bluetooth Mesh network in order to establish communications.
Education
Faculdade de Engenharia da Universidade do Porto
Electrical and Computer Engineering
Faculdade de Engenharia da Universidade do Porto
Electrical and Computer Engineering
Diogo Campas's Contact Information
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