Redmond, WA, United States of America

Ahmed Awadalla


Average Co-Inventor Count = 6.0

ph-index = 1


Company Filing History:


Years Active: 2023-2024

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2 patents (USPTO):Explore Patents

Title: Ahmed Awadalla: Innovator in Machine Learning

Introduction

Ahmed Awadalla is a notable inventor based in Redmond, WA (US). He has made significant contributions to the field of machine learning, particularly in the training of machine learning models. With a total of 2 patents, his work is recognized for its innovative approach to model training.

Latest Patents

One of Ahmed's latest patents is titled "Joint learning from explicit and inferred labels." This patent relates to the training of machine learning models. The method involves providing a machine learning model that includes a first classification layer, a second classification layer, and an encoder that feeds into both classification layers. The process includes obtaining first training examples with explicit labels and second training examples with inferred labels, which are based on actions associated with the second training examples. The model is trained using both types of examples, considering the training loss for explicit and inferred labels. The outcome is a trained machine learning model that incorporates the encoder and the first classification layer.

Career Highlights

Ahmed Awadalla is currently employed at Microsoft Technology Licensing, LLC. His role at this leading technology company allows him to work on cutting-edge innovations in machine learning. His expertise in the field has positioned him as a valuable asset to his team and the broader technology community.

Collaborations

Ahmed collaborates with talented individuals such as Subhabrata Mukherjee and Guoqing Zheng. These collaborations enhance the innovative potential of their projects and contribute to advancements in machine learning.

Conclusion

Ahmed Awadalla is a prominent inventor whose work in machine learning is paving the way for future innovations. His contributions, particularly in training models with explicit and inferred labels, demonstrate his commitment to advancing technology.

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