Urbana, IL, United States of America

Ashutosh Garg

This inventor holds 4 USPTO granted patents. Top assignees: Microsoft Technology Licensing, LLC, Hewlett-Packard Development Company, L.p.. Active years: 2004-2008.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Ashutosh Garg. Retrieved from https://idiyas.com/inventor/ashutosh-garg-g1elfkwy

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


% Patents Active = 25.0

Average Co-Inventor Count = 2.4

ph-index = 4

Forward Citations = 228(Granted Patents)


Company Filing History:


Years Active: 2004-2008

Loading Chart...
4 patents (USPTO):Explore Patents

Title: Innovations of Ashutosh Garg

Introduction

Ashutosh Garg is a prominent inventor based in Urbana, IL (US). He has made significant contributions to the fields of machine learning and predictive analytics. With a total of 4 patents, his work focuses on enhancing classification accuracy and context awareness through innovative methodologies.

Latest Patents

One of his latest patents is titled "Maximizing mutual information between observations and hidden states to minimize classification errors." This invention relates to a system and methodology that facilitates machine learning and predictive capabilities in a processing environment. It introduces a Mutual Information Model that aids in predictive state determinations based on signal or data analysis, effectively reducing classification errors. The model parameters are computed by maximizing a convex combination of the mutual information between hidden states and observations, as well as the joint likelihood of states and observations in training data. Once the model parameters are learned, new data can be accurately classified.

Another notable patent is "Layered models for context awareness." This invention provides a system and methodology that offers layered probabilistic representations for sensing, learning, and inference from multiple sensory streams at various levels of temporal granularity and abstraction. The methods enhance robustness to subtle environmental changes and enable model adaptation with minimal retraining. An architecture of Layered Hidden Markov Models (LHMMs) is employed, with parameters learned from stream data over different time periods, allowing for inferences related to context and activity from perceptual signals.

Career Highlights

Ashutosh Garg has worked with notable companies such as Microsoft Technology Licensing, LLC and Hewlett-Packard Development Company, L.P. His experience in these organizations has contributed to his expertise in the field of technology and innovation.

Collaborations

Throughout his career, Ashutosh has collaborated with esteemed professionals, including Nuria M Oliver and Simon Kasif. These collaborations have further enriched his work and expanded his impact in the field.

Conclusion

Ashutosh Garg's innovative contributions to machine learning and predictive analytics demonstrate his commitment to advancing technology. His patents reflect a deep understanding of complex systems and a drive to improve classification accuracy and context awareness. His work continues to influence the field and inspire future innovations.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
Loading…