This inventor holds 2 USPTO granted patents. Top assignee: Autodesk, Inc.. Active years: 2022-2026.
Company Filing History:
Years Active: 2022-2026
Title: Innovations of Markus Bussmann in Machine Learning
Introduction
Markus Bussmann is a notable inventor based in Mississauga, Canada. He has made significant contributions to the field of machine learning, particularly in the area of interface construction. His work has implications for various applications in numerical simulations and computational geometry.
Latest Patents
Markus Bussmann holds a patent titled "Machine learning approach to piecewise linear interface construction." This patent encompasses methods, systems, and apparatuses, including medium-encoded computer program products, for implementing a machine learning approach for piecewise linear interface construction. The patent details a process that involves obtaining a cell fraction for a mesh cell, a normal vector perpendicular to a linear interface, and geometry information of the mesh cell. The geometry information includes at least two data values, which are normalized to reduce them to at least one data value. The output value is obtained from a machine learning algorithm that has been previously trained using normalized geometry information from multiple different cells of the same mesh type. The linear interface for the mesh cell is then determined based on the output value, the normal vector, and the geometry information. This linear interface is utilized in numerical simulation processing of the mesh.
Career Highlights
Markus Bussmann is currently employed at Autodesk, Inc., where he continues to innovate and develop new technologies. His work at Autodesk has allowed him to apply his expertise in machine learning to real-world problems, enhancing the capabilities of software used in design and engineering.
Collaborations
Markus has collaborated with Mohammadmehdi Ataei, contributing to advancements in their field through shared knowledge and expertise.
Conclusion
Markus Bussmann's contributions to machine learning and interface construction demonstrate his innovative spirit and commitment to advancing technology. His patent and work at Autodesk highlight the importance of machine learning in modern computational applications.