Mher Hakobyan

Title: Mher Hakobyan: Innovator in Data Aggregation and Machine Learning

Introduction

Mher Hakobyan is a prominent inventor based in Mountain View, California. He has made significant contributions to the fields of data aggregation and machine learning. With a total of two patents to his name, Mher is recognized for his innovative approaches to handling unstructured data.

Latest Patents

Mher's latest patents include an "Apparatus and method for aggregating and evaluating multimodal, time-varying entities." This invention involves a non-transitory computer-readable storage medium that executes instructions to receive various sources of unstructured data. The data is characterized by multiple modes of semantically distinct types and time-varying instances. The invention forms an entity by combining these data sources and creates a representation that includes numeric vectors computed using machine learning embedding models. Proximity searches are then performed on these embeddings within an index.

Another notable patent is the "Apparatus and method for transforming unstructured data sources into both relational entities and machine learning models that support structured query language queries." This patent also utilizes a non-transitory computer-readable storage medium to process unstructured data. It forms an entity with relational data attributes and creates a representation that includes embeddings. An enrichment model is developed to predict properties of the entity, allowing for efficient query processing.

Career Highlights

Mher Hakobyan is currently employed at Graft, Inc., where he continues to innovate in the realm of data processing and machine learning. His work focuses on transforming unstructured data into usable formats for various applications.

Collaborations

Mher collaborates with talented individuals such as Adam Jamison Oliner and Maria Kazandjieva. Their combined expertise contributes to the advancement of their projects and innovations.

Conclusion

Mher Hakobyan stands out as an influential inventor in the technology sector, particularly in data aggregation and machine learning. His patents reflect a deep understanding of unstructured data and its potential applications. His contributions are paving the way for future innovations in the field.