This inventor holds 1 USPTO granted patent. Top assignees: Constructor Education and Research Genossenschaft, Constructor Technology Ag. Active years: 2026.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
1 out of 18 
1 out of 29 Years Active: 2026
Title: Nikita Kazeev: Machine Learning for Defect Properties in 2D Materials.
Introduction
Nikita Kazeev is an inventor associated with Singapore. His work includes a patent application focused on applying machine learning to predict properties of defects in two-dimensional materials.
Latest Patents
Kazeev is associated with 1 patent, titled “Sparse Representation for Machine Learning the Properties of Defects in 2D Materials.” The invention describes a method for predicting at least one property of a crystal containing a point defect. It uses sampled material and defect structures as data for a neural network, which receives structural information and may also process a cloud of defect points or a global state vector. The network outputs a vector representing a target quantity related to the defect and crystal.
Career Highlights
Kazeev has been associated with Constructor Technology AG and Constructor Education and Research Genossenschaft. The available information does not specify his roles or dates of employment at these organizations.
Collaborations
His listed coworkers include Andrey Ustyuzhanin and Abdalaziz Rashid Al-Maeeni. The available information does not detail their specific contributions to the patent.
Conclusion
Nikita Kazeev’s patent work applies neural-network methods to the study of point defects in two-dimensional materials, connecting machine learning with materials research.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile