Carlos W Morato

Biography

Education: PhD Mechanical Engineering University of Maryland, College Park MS Aerospace Engineering University of Maryland, College Park MS Computer Science San Andres University Summa Cum Laude MS Computers with Applications University of Catalonia Distinction BS Computer Science Technical University of Oruro High Distinction Carlos Morató, PhD is Principal Scientist in Machine Learning and Machine Perception in the Mechatronics and Sensors Group at ABB US Corporate Research. He conducts research on remote sensing, sensor fusion, virtual and augmented reality, HRI, intelligent robotics and robot perception with strong focus in machine learning, statistical modeling, predictive modeling and computer vision algorithms. His particular interest is the research and development of Deep learning based end-to-end machine intelligence. He received his PhD in Mechanical Engineering from University of Maryland – College Park. He also holds a M.Sc. in Aerospace Engineering from University of Maryland – College Park, a M.Sc. in Computer Technology from University of Catalonia and a M.Sc. in Computer Science from San Andres University. He is Adjunct Professor at Worcester Polytechnic Institute. His professional experience also includes roles as Senior Scientist at MITRE where he was investigating and developing new navigation and perception systems for Drone technology. Robot Motion Researcher with MRC, Laboratory that develops UGVs, USSV, HRI and state-of the art planning techniques. Computer Vision Expert with SSL, Laboratory that develops Unmanned Robots for Space and Deep ocean exploration and new technologies for HRI and Human factors. Research Scientist with IDSIA investigating Metaheuristics and Probabilistic Program Evolution for NP problems applied in the transportation and telecommunication. R&D Engineer with 123ID Inc. developing innovative security technologies using Finger Print Authentication, Neural Vector Identification and Neural Face Recognition. He worked as the lead R&D Engineer with the Bolivian Ministry of Agriculture to develop computer vision/machine learning technologies that monitor and control the quality of Quinoa production.

Research Interest

Deep Learning; Reinforcement Learning; Topological Data analysis; Manifold Learning; Machine and Computer vision; Meta-heuristic algorithms for combinatorial optimization problems; Exploratory, Inferential, Predictive and Causal Data analysis; Robot Path, Trajectory and Motion Planning; Autonomous Robot Navigation, SLAM and AR