Jaime Maqueda
Forward Deployed Engineer @ HappyRobot
About
Transforming the future of industries through AI – that’s my mission! As a researcher and engineer, I’m harnessing the power of artificial intelligence to revolutionize process planning, decision-making, and automation, particularly in manufacturing. From developing transformer-based models that streamline production sequencing to creating cutting-edge AI-driven solutions for smart factories, I’m all about driving efficiency and innovation in complex, customizable environments. My expertise spans robotics, computer vision, and cyber-physical systems, blending deep learning with real-world applications that reduce human intervention and enhance productivity across various engineering fields. Whether it’s optimizing production through digital twins, designing scalable AI architectures, or exploring new challenges in different industries, I’m passionate about solving problems with practical, data-driven solutions. With hands-on experience in both research and applied AI, I aim to bridge the gap between theory and real-world impact – from academic collaborations to industry projects. My goal is to push AI’s role beyond traditional boundaries, contributing to more intelligent, adaptable, and sustainable systems across a range of sectors.
United States
San Francisco
Information Technology & Services
C++, CUDA, Datasets, Building Information Modeling (BIM), Project Management, Team Leadership, Life Cycle Assessment, Process Engineering, Computer Vision, OpenCV, Smart Manufacturing, Process Automation, Image Sensors, Recurrent Neural Networks (RNN), Structural Health Monitoring, Convolutional Neural Networks (CNN), TensorFlow, Robot Operating System (ROS), Regression Models, LiDAR
Experience
Forward Deployed Engineer
HappyRobot
San Francisco, California, United States
Graduate Research Assistant
George W. Woodruff School of Mechanical Engineering
Atlanta, Georgia, United States
Architected and trained a novel transformer-based encoder-decoder network using PyTorch on a GPU cluster, automating manufacturing process sequencing from voxel data, with potential to reduce human intervention by 70%. Developed a full-stack Flask-based web platform, integrating supervised and unsupervised learning tools for AI-driven decision-making in manufacturing, including classification, part retrieval, and 3D CNN autoencoders. Generated a synthetic dataset of 1M+ samples using FreeCAD macros, enhancing model training for deep learning applications in manufacturing.
Undergraduate Research Assistant
Universidad Politécnica de Madrid
Madrid, Spain
Developed a computer vision-based perception algorithm using OpenCV and RGB-D sensors, enhancing a collaborative robot's ability to autonomously grasp and manipulate objects in a smart manufacturing environment. Aligned the robotic perception operation with the manufacturing process, optimizing the handling of customized parts and improving production workflow efficiency. Conducted real-time implementation and validation, achieving a 95% success rate in autonomous grasping and contributing to the development of adaptive, process-aware robotic systems.
Education
Georgia Institute of Technology
MSc Mechanical Engineering - Artificial Intelligence Track
Relevant courses: Machine Learning for Robotics; Computer Vision; Research in Machine Learning, Robotics and Vision
Universidad Politécnica de Madrid
MSc Industrial Technologies Engineering
Relevant courses: Automation and Control; Electronic Systems Design; Supply Chain Networks; Financial Management; Project Management
RWTH Aachen University
International Exchange - Faculty of Mechanical Engineering
Relevant courses: Computational Intelligence; Artificial Neural Networks in Structural Mechanics; Continuum Mechanics
Universidad Politécnica de Madrid
BSc Industrial Technologies Engineering - Intelligent Systems and Structures Track
Relevant courses: Thermodynamics; Material Sciences; Fluid Mechanics; Structural Analysis Thesis: Developed a computer vision algorithm with OpenCV for robotic grasp detection, automating product handling by collaborative robots in a smart manufacturing environment
Jaime Maqueda's Contact Information
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