Company Filing History:
Years Active: 2025
Title: Jihan Yin: Innovator in Data Curation and Sampling Techniques
Introduction
Jihan Yin is a prominent inventor based in San Francisco, CA. He has made significant contributions to the field of data science, particularly in the areas of data curation and sampling techniques. With a total of 3 patents, his work is paving the way for advancements in machine learning and data management.
Latest Patents
Jihan Yin's latest patents include innovative techniques that enhance the efficiency of data handling. One of his patents, titled "Automatic Data Curation," outlines a method for curating a data sample set. This technique involves determining data sampling criteria based on specific objectives for a machine learning model. It also includes selecting unlabeled data samples to be labeled and added to the data sample set, thereby improving the model's performance.
Another notable patent is "Unique Sampling of Datasets," which presents a technique for sampling from a dataset. This method determines multiple embeddings for various data points and populates a tree structure with these embeddings. By traversing this tree structure, a subset of embeddings is sampled, resulting in a dataset that corresponds to the selected data points.
Career Highlights
Jihan Yin is currently employed at Scale AI, Inc., where he applies his expertise in data science to develop cutting-edge solutions. His work at Scale AI has positioned him as a key player in the industry, contributing to the company's mission of enhancing data utilization for machine learning applications.
Collaborations
Throughout his career, Jihan has collaborated with talented individuals such as Chiao-Lun Cheng and Diego Ardila. These collaborations have fostered a creative environment that encourages innovation and the sharing of ideas.
Conclusion
Jihan Yin's contributions to data curation and sampling techniques are noteworthy and impactful. His patents reflect a deep understanding of machine learning and data management, positioning him as a leading inventor in his field. As he continues to innovate, the implications of his work will undoubtedly influence the future of data science.