Company Filing History:
Years Active: 2018-2020
Title: Innovations of Mohammed Shoaib
Introduction
Mohammed Shoaib is a prominent inventor based in Redmond, WA (US). He has made significant contributions to the field of machine learning, holding a total of seven patents. His work focuses on enhancing the efficiency and effectiveness of machine learning algorithms.
Latest Patents
One of his latest patents is titled "Scalable-effort classifiers for energy-efficient machine learning." This innovation allows for automatic and dynamic adjustments in computational effort based on the complexity of input data. Unlike traditional fixed-effort machine learning, which applies a single classifier algorithm universally, scalable-effort machine learning utilizes a series of classifiers with increasing complexity and accuracy. This approach enables more efficient processing of data, particularly in distinguishing between simple and complex datasets.
Another notable patent is "Context-awareness through biased on-device image classifiers." This invention facilitates efficient image processing by extracting features from multiple images and classifying them into distinct sets. The system identifies false positives among the first set of images and transmits only the relevant data to a remote device. This method conserves memory, reduces processor load, and minimizes energy consumption at the local device, while also optimizing network bandwidth usage.
Career Highlights
Mohammed Shoaib is currently employed at Microsoft Technology Licensing, LLC, where he continues to innovate in the field of technology. His work has garnered attention for its potential to revolutionize machine learning applications.
Collaborations
He collaborates with talented individuals such as Jie Jerry Liu and Swagath Venkataramani, contributing to a dynamic and innovative work environment.
Conclusion
Mohammed Shoaib's contributions to machine learning through his patents demonstrate his commitment to advancing technology. His innovative approaches are paving the way for more efficient and effective solutions in the field.
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