Milpitas, CA, United States of America

Vrishti Gulati

This inventor holds 1 USPTO granted patent. Top assignee: Microsoft Technology Licensing, LLC. Active years: 2025.


% Patents Active = 100.0

Average Co-Inventor Count = 6.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Vrishti Gulati: Innovator in Deep Embedding Learning Models

Introduction

Vrishti Gulati is an accomplished inventor based in Milpitas, CA (US). She has made significant contributions to the field of machine learning, particularly in the development of deep embedding learning models. Her innovative work has led to the filing of a patent that showcases her expertise and creativity in technology.

Latest Patents

Vrishti holds a patent for "Deep embedding learning models with mimicry effect." In this invention, a separate mimicry machine-learned model is trained for each of a plurality of different item types. Each model is designed to estimate the effect of mimicry for a user, utilizing their user profile or other information during prediction time. The outputs of these models can be used independently to perform various actions, such as modifying the location of a user interface element, or they can serve as input to an interaction machine-learned model. This model is trained to determine the likelihood of a user interacting with a particular item, such as a potential feed item. Vrishti has 1 patent to her name.

Career Highlights

Vrishti is currently employed at Microsoft Technology Licensing, LLC, where she continues to push the boundaries of technology through her innovative work. Her role at Microsoft allows her to collaborate with some of the brightest minds in the industry, contributing to cutting-edge advancements in machine learning.

Collaborations

Some of Vrishti's notable coworkers include Chun Lo and Ye Tu. Their collaboration fosters a creative environment that enhances the development of innovative solutions in their field.

Conclusion

Vrishti Gulati is a pioneering inventor whose work in deep embedding learning models exemplifies her commitment to advancing technology. Her contributions are shaping the future of machine learning and user interaction.

Profile summary based on public USPTO records.
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