Karthik Mohan Mokashi

Title: Karthik Mohan Mokashi: Innovator in Machine Learning and Failure Mode Analytics

Introduction

Karthik Mohan Mokashi is a prominent inventor based in San Ramon, CA (US). He has made significant contributions to the field of machine learning, particularly in the area of failure mode analytics. With a total of 4 patents to his name, Mokashi is recognized for his innovative approaches to enhancing machine learning pipelines.

Latest Patents

One of Mokashi's latest patents focuses on a system and method for training and validating models in a machine learning pipeline for failure mode analytics. This innovative approach includes an unsupervised training phase, a validation phase, and a supervised training and scoring phase. The method involves receiving a request to create a machine learning model for failure mode detection associated with an asset. It retrieves historical notification data of the asset and generates an unsupervised machine learning model through unsupervised learning on the historical notification data. This unsupervised learning identifies failure topics from text included in the historical notification data and maps these identified failure topics to a plurality of predefined failure modes for the asset. The generated unsupervised machine learning model is then stored via a storage device.

Career Highlights

Karthik Mokashi is currently employed at SAP SE, where he continues to develop innovative solutions in machine learning. His work has been instrumental in advancing the capabilities of failure mode analytics, making significant strides in how organizations can predict and manage potential failures in their systems.

Collaborations

Mokashi collaborates with talented professionals in his field, including coworkers Lukas Carullo and Patrick Brose. Their combined expertise fosters a creative environment that drives innovation and enhances the development of cutting-edge technologies.

Conclusion

Karthik Mohan Mokashi is a notable inventor whose work in machine learning and failure mode analytics is paving the way for advancements in predictive technologies. His contributions are shaping the future of how organizations approach failure detection and management.