Baldur Andrew Steingrimsson

Title: Baldur Andrew Steingrimsson: Innovator in Machine Learning and Alloy Design

Introduction

Baldur Andrew Steingrimsson is a notable inventor based in Hillsboro, OR (US). He has made significant contributions to the fields of machine learning and materials science, holding a total of 4 patents. His innovative work focuses on enhancing product design and alloy development through advanced computational techniques.

Latest Patents

One of his latest patents is titled "Machine learning to accelerate alloy design." This invention presents an innovative framework for the application of machine learning to identify alloys or composites with desired properties. The framework identifies the corresponding driving factors for each output property of interest, which may include material composition, heat treatment, process, microstructure, temperature, strain rate, environment, or testing mode. The model assumes the selection of an optimization technique suitable for the application at hand, starting with simple linear or quadratic regression analysis. Additionally, it presents a physics-based model for predicting ultimate tensile strength, accounting for physical dependencies and underlying physics as a priori information. If an artificial neural network is deemed suitable, custom kernel functions consistent with the underlying physics are suggested to achieve better predictions and extract the most from the limited input data available.

Another significant patent is "Decisions with big data." This invention outlines a framework for applying artificial intelligence to aid in product design, mission planning, or retail planning. It introduces a novel approach for applying predictive analytics to train a system model for product design. The invention assimilates the definition of meta-data for design containers to that of labels for books in a library. It represents customers, requirements, components, and assemblies as database objects with relational dependence. Design information can be harvested to improve decision fidelity for new designs by providing a database representation of the design content. Furthermore, a retrieval model operates on archived design containers, yielding results likely to satisfy user queries. This model, based on latent semantic analysis, predicts the degree of relevance between accessible design information and a query, presenting the most relevant previous design information to the user.

Career Highlights

Baldur has worked with Imagars LLC, where he applied his expertise in machine learning and product design. His innovative contributions have significantly impacted the development of advanced materials and design methodologies.

Collaborations

Baldur has collaborated with notable professionals in his field, including Anand Kulkarni and Kwan Yi. Their combined