Hugo Siqueira Gomes Email & Phone Number

Niterói, Rj, Br

Vancouver, British Columbia, Canada

• Development of 2D and 3D AI tools in a vision software forinline measurement and inspection solutions.• Development of smart camera projects with 2D/3D tools and calibration methods.• Designed and deployed a real-time Anomaly Detection pipeline, leveraging deep learning to streamline workflow for labeling, training, and testing models• Ported and optimized vision tools pipeline to a vision software of 3D smart sensors, using C, C++, and Python.• Developed GoAIK module, enabling integration between with GoPxL and Cognex, a leading machine vision software, improving data accuracy and processing time.• Technologies: C, C++, Python, Deep Learning, Anomaly Detection, Computer Vision, Machine Learning.

North Vancouver, British Columbia, Canada

• Implemented a pick and place robotic solution using Universal Robots and Realsense/Kinect/Ensenso cameras.• Implemented a computer vision pipeline (data labeling for 3D segmentation, training and evaluating model) for point cloud classification using PointCNN.• Implemented a production-level QT desktop application forrobotic tool.• Technologies: Reinforcement learning, Open3D, Pytorch, Universal Robots, Computer Vision.

Rio De Janeiro, Brazil

• Implemented a hand tracking system to work in low-light conditions using numerous realsense cameras.• Implemented a pose estimation system and OSC server in Unity Engine.• Technologies: Machine learning, Computer Vision, Unity Engine, RealSense, OSC, Python, and C#.

Nevada, United States

• Implemented a manageable infrastructure forimage processing in cloud servers reducing process time by 30%.• Automatized time-consuming tasks (10TB training data for annotation) using SOTA deep learning methods.• Presented key findings for end customers to the team leader and wrote an executive report.• Technologies: Deep Learning, Computer Vision, AWS, Docker, and Python.

Rio De Janeiro, Brazil

• Deployed 100+ wearable applications that gather training data and send to docker containers.• Processed 1TB of previously inaccessible data for a Human Activity Recognition system, improving prediction accuracy by 50% and speed by 400% forreal-time client impact tracking.• Technologies: Deep Learning, Time Series, Docker, Python, C++, and Javascript.

Master'S Degree, Electrical And Computer Engineering, Machine Learning

Thesis: Meta Learning Population-Based Algorithms in Black-box Optimization Fellowships: • Institute Intelligence and Data (IID) • Mitacs.

Bachelor'S Degree, Computer Science

Thesis: Towards Deep Q-Caching Fellowships: • National Council of Scientific Researches Scholarship • Institutional Scientific Initiation.