Location History:
- London, GB (2022 - 2024)
- Reading, GB (2024)
Company Filing History:
Years Active: 2022-2024
Title: Jiazuo Zhang: Innovator in Machine Learning for Subsurface Classification
Introduction
Jiazuo Zhang is a prominent inventor based in London, GB. He has made significant contributions to the field of machine learning, particularly in the classification of subterranean formations. With a total of 3 patents, his work is paving the way for advancements in geological assessments.
Latest Patents
One of Jiazuo Zhang's latest patents focuses on "Probability distribution assessment for classifying subterranean formations using machine learning." This innovation involves executing machine-learning models to classify subsurface rock by training various models with different probability distributions. The selection of the most suitable model is based on the similarity of data points between training and test datasets. This method enhances the accuracy of predicting classifications, such as lithology, for hydrocarbon formations.
Another notable patent is "Classifying downhole test data." This invention outlines methods for classifying test data by determining variable types in a multivariate test vector. The process includes finding the closest match between variable types used in machine-learning models and those in the test vector. By selecting the most appropriate model based on similarity values, this approach improves the classification of test vectors.
Career Highlights
Jiazuo Zhang has worked with notable companies in the industry, including Landmark Graphics Corporation and Total SE. His experience in these organizations has contributed to his expertise in machine learning applications for geological assessments.
Collaborations
Jiazuo has collaborated with professionals such as Graham Baines and Gavin Henry Graham, further enhancing his innovative work in the field.
Conclusion
Jiazuo Zhang's contributions to machine learning and subsurface classification are noteworthy. His patents reflect a commitment to advancing technology in geological assessments, making him a significant figure in the field.