Ul LLC

Mario Xerri

Mahmood Tabaddor

Anthony Tassone

Pravinray D Gandhi

Scot Webster

Priyansu Panda

John C Jones

Systems and methods for using machine learning to assess eligibility for product certification are disclosed. According to certain aspects, a server computer may train a set of machine learning models using a set of training data, where the set of machine learning models may be specific to products and certifications for the products. The server computer may access product specifications associated with a set of products sought to be certified, and may analyze the product specifications using the an appropriate machine learning model(s), the output of which may indicate whether the set of products is eligible for certification, the set of products is ineligible for certification, or the product specifications need further review.

Technologies for using machine learning to determine product certification eligibility

Systems and methods for using machine learning models to predict an outcome of a product test are described. According to certain aspects, an electronic device may generate a machine learning model using training data indicating a set of results of a set of products tested according to a specific product test. The electronic device may access a set of inputs comprising a set of additional results of at least one additional product tested according to a modified product test, and input the set of inputs into the machine learning model. Based on an output of the machine learning model, the electronic device may predict whether the at least one additional product would pass or comply with the original specific product test.

Using machine learning to virtualize product tests

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Melville, NY, United States of America

Mario Xerri