Rafael Horschutz Nemoto
About Rafael Horschutz Nemoto
Rafael Horschutz Nemoto is a Senior Data Scientist specializing in Production Optimization at Cognite in Oslo, Norway. He has a diverse background in engineering and research, with experience in various roles at companies such as Bosch Rexroth, IBM Research, and Baker Hughes.
Work at Cognite
Rafael Horschutz Nemoto has been employed at Cognite as a Senior Data Scientist in Production Optimization since 2021. His role focuses on leveraging data science techniques to enhance production processes and optimize performance. He is involved in various projects that aim to improve operational efficiency through data-driven insights.
Education and Expertise
Rafael holds an Engineer's degree in Mechatronic Engineering from Escola Politécnica da Universidade de São Paulo, completed in 2008. He also earned a Doctor of Science (D.Sc.) in Mechanical Engineering with a focus on Energy & Fluids from the same institution between 2009 and 2012. Additionally, he studied Mechanical Engineering at Technische Universität Darmstadt for a year in 2007. His educational background supports his expertise in data science and engineering methodologies.
Background
Rafael began his career as an Engineering Intern at Bosch Rexroth in 2007, where he worked in Mobile Hydraulics for five months. He then joined IBM Research as a Research Staff Member, focusing on Natural Resources Optimization from 2012 to 2013. He has held various positions in reputable organizations, including Baker Hughes, GE Global Research, and The University of Tulsa, where he served as a Research Associate in Petroleum Engineering from 2018 to 2020.
Achievements
Rafael has submitted six patents to the United States Patent and Trademark Office (USPTO), showcasing his contributions to innovation in engineering and data science. He has developed an online calibration tool for multiphase flow meters for Harbour Energy and is currently working on deploying virtual multiphase flow meters for Santos in Australia. His academic contributions include eight publications in peer-reviewed journals and conferences.
Methodologies and Technologies
Rafael utilizes Six Sigma and Design for Six Sigma (DFSS) methodologies to support improvement and innovation in his projects. He has implemented a machine learning-powered advisory system to address riser-induced slugging for Harbour Energy in the UK. His work emphasizes the integration of advanced technologies in optimizing production processes and enhancing operational efficiency.