Cambridge, MA, United States of America

Matthew E Brand

USPTO Granted Patents = 57 

Average Co-Inventor Count = 1.4

ph-index = 12

Forward Citations = 562(Granted Patents)

Forward Citations (Not Self Cited) = 555(Oct 12, 2025)


Inventors with similar research interests:


Location History:

  • Cambridge, MA (US) (2000 - 2013)
  • Newtonville, MA (US) (2009 - 2015)
  • Newton, MA (US) (2003 - 2022)

Company Filing History:


Years Active: 2000-2025

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Areas of Expertise:
Metalens Technology
Machine Learning Optimization
Freeform Optics
Radiation Therapy Planning
Image Processing Techniques
Elevator Scheduling Systems
3D Reconstruction
Facial Animation Synthesis
Geometric Primitives
Motion Planning Algorithms
Wireless Ad-Hoc Networks
Resource Allocation Strategies
57 patents (USPTO):Explore Patents

Title: Matthew E Brand: Innovating Path Generation and Neural Network Training

Introduction:

In the realm of innovations and patents, Matthew E Brand stands as an accomplished inventor and researcher based in Cambridge, MA. With an impressive collection of 56 patents, he has made significant contributions to areas such as path generation and neural network training. This article explores Matthew E Brand's latest patents, career highlights, collaborations, and his valuable insights in the field.

Latest Patents:

1. System and Method for Generating Optimal Lattice Tool Paths:

This patent introduces a data conversion system that utilizes algorithms to generate optimal lattice tool paths. By employing a combination of lattice full algorithms and dynamic programming algorithms, the system effectively forms target polylines and divides them into line segments. Through rational vector approximation, the lower convex hull lines are aligned with these admissible points, ultimately leading to the formation of a final polyline that sits on or above the target polyline.

2. Machine Learning via Double Layer Optimization:

Matthew E Brand's second recent patent focuses on a computer-based system that enhances neural network training. Employing a double layer optimization approach, the system minimizes differences between the network's outputs and input labels, as well as reducing distances between non-negative output vectors and their corresponding input vectors. This optimization procedure helps to refine the parameters of the neural network and improve its overall performance.

Career Highlights:

Matthew E Brand's career has been characterized by his association with esteemed research institutions and companies. Notably, he has worked at Mitsubishi Electric Research Laboratories, Inc., where he has evidently made significant contributions in his field. With 56 patents to his name, Matthew's career highlights showcase his keen ability to innovate and bring novel concepts to fruition.

Collaborations:

Throughout his journey, Matthew E Brand has had the opportunity to collaborate with talented individuals in the field of innovations and patents. Notable among his collaborators are Daniel Nikolaev Nikovski and Srikumar Ramalingam. These partnerships likely played a pivotal role in shaping and refining his ideas, leading to the development of groundbreaking inventions.

Conclusion:

Matthew E Brand, based in Cambridge, MA, has undoubtedly established himself as a highly respected innovator in path generation and neural network training. His extensive patent portfolio reflects his dedication to pushing the boundaries of technology and solving complex problems. With a spirit of collaboration and a talent for generating innovative ideas, Matthew continues to contribute to the realm of innovations and patents, leaving an indelible mark on the field.

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