Worlds
Kenta Nakajima has a diverse work experience spanning various roles and industries. Kenta currently holds the position of Senior Deep Learning Engineer at Worlds since March 2023. Prior to this, they worked at H&P Technologies as a Deep Learning Engineer for Computer Vision from December 2020 to February 2023. Before that, they served as a Data Analytics Consultant at MCERI from August 2015 to December 2020. Additionally, they held multiple roles at Texas A&M University, including Graduate Representative and SPE Co-Chair. Kenta also gained experience through internships at InsidePetroleum.com and MEENCO, as well as research and teaching positions at Waseda University. Kenta furthered their knowledge in the industry through a production and reservoir engineering field internship at JX Nippon Oil & Gas Exploration Co.
Kenta Nakajima completed their education in a chronological order as follows:
From 2021 to 2022, Kenta obtained a Master's degree in Computer Science from The University of Texas at Austin.
Prior to that, they pursued their Doctor of Philosophy - PhD in Petroleum Engineering from 2017 to 2020 at Texas A&M University.
Before their Ph.D., they earned a Master of Science - MS degree in Petroleum Engineering from Texas A&M University from 2015 to 2017.
Kenta Nakajima's undergraduate studies were focused on Environment and Natural Resource Engineering. Kenta obtained a Bachelor of Science - BS degree from Waseda University, which they attended from 2011 to 2015.
In addition to their formal education, Kenta Nakajima has also acquired various certifications. Kenta completed courses such as "Introduction to Java and Object-Oriented Programming," "HTML, CSS, and JavaScript for Web Developers," "Convolutional Neural Networks," "Deep Learning Specialization," "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization," "Neural Networks and Deep Learning," "Sequence Models," and "Structuring Machine Learning Projects" from Coursera. The certificates were obtained between 2019 and 2021.
Worlds
Worlds' spatial models enable their clients to remotely observe, analyze and learn from their physical environments in ways that have never been possible before. Their SpatialSense platform combines deep learning AI with sensor networks inside of a spatial model to create near-live, 4D simulations of real-world scenes. It's now possible for organizations to remotely sense all of their physical environments from a single interface.