Srivatsava Daruru

Title: Srivatsava Daruru: Innovator in Data Processing and Machine Learning

Introduction

Srivatsava Daruru is a prominent inventor based in Mountain View, CA (US). He has made significant contributions to the fields of data processing and machine learning, holding a total of 5 patents. His innovative work focuses on improving the efficiency of training data labeling and enhancing data access through vector indexing.

Latest Patents

One of his latest patents is titled "Method for filtering and semi-automatically labeling training data." This method provides an efficient way to assign sentiments or other manual labels to textual training data. It utilizes an embedding model to project user text into an embedding vector within an embedding space. The method calculates distances, such as cosine similarities, between this embedding vector and those of previously labeled user text training examples. The closest labeled text is identified, and its label is prospectively applied to the new user text for user approval. Users can either approve the label, adding it to the training data, or decline it and apply an alternative label.

Another notable patent is "Generation and utilization of vector indexes for data processing systems and methods." This patent describes systems and methods that analyze a corpus of data to identify multiple documents. The system generates vector indexes for these documents, enabling quick access and identification of answers to questions related to the data corpus.

Career Highlights

Throughout his career, Srivatsava has worked with notable companies such as ServiceNow, Inc. and Microsoft Technology Licensing, LLC. His experience in these organizations has allowed him to refine his skills and contribute to significant advancements in technology.

Collaborations

Some of his coworkers include Mitul Tiwari and Quaizar Vohra, with whom he has collaborated on various projects, further enhancing his innovative contributions to the field.

Conclusion

Srivatsava Daruru's work in data processing and machine learning exemplifies the impact of innovation in technology. His patents reflect a commitment to improving the efficiency of data handling and training processes. His contributions continue to influence the landscape of machine learning and data processing systems.