Mark Sayre

Title: Mark Sayre: Innovator in Predictive Modeling and Software Coding

Introduction

Mark Sayre is a prominent inventor based in Springfield, MA, with a remarkable portfolio of 11 patents. His work primarily focuses on predictive modeling and software coding, showcasing his expertise in artificial intelligence and user-friendly software solutions.

Latest Patents

One of Sayre's latest patents is titled "Systems and methods for predictive modeling." This invention discusses methods and systems for an interdependent series of AI models. In this embodiment, a processor receives projection assumption inputs from a user device and executes a population builder machine learning model to predict a dynamic adjustment table. It applies the model to population data to generate a value population file, simulating a subset of the population based on the predicted table. The file contains value cells representing instances of a product. The device then runs a mortality machine learning model to determine mortality data for the product using the simulated population. Finally, it executes a flow projection model to generate a projection report for the product, incorporating mortality data and projection assumptions.

Another significant patent is "Systems, devices, and methods for software coding." This invention provides methods and systems that allow dynamic rendering of a reflexive questionnaire based on a modifiable spreadsheet for users with little to no programming experience. Some methods comprise receiving a modifiable spreadsheet with multiple rows, each row comprising rendering instructions for a reflexive questionnaire from a first computer. This includes data type cells, statement cells, logic cells, and field identifiers. The system renders a graphical user interface on a second computer, which includes a label and an input element corresponding to the rendering instructions of the first row of the spreadsheet. It then receives an input from the second computer and evaluates the input against the logic cell of the spreadsheet. In response to the input complying with the logic cell, it dynamically renders a second label and a second input element based on the logic of the first row.

Career Highlights

Throughout his career, Mark Sayre has made significant contributions to the fields of predictive modeling and software development. He has worked with notable companies, including Hitps LLC and Massachusetts Mutual Life Insurance Company, where he has applied his innovative ideas to real-world applications.

Collaborations

Mark has collaborated with talented individuals such as Harish Krishnaswamy and Sam Elsamman, further enhancing his work through shared expertise and insights.

Conclusion

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