Company Filing History:
Years Active: 2024-2025
Title: Jingyi Han: Innovator in Automatic Post-Editing Technologies
Introduction
Jingyi Han is a prominent inventor based in Barcelona, Spain. He has made significant contributions to the field of machine translation, particularly in the area of automatic post-editing. With a total of 2 patents to his name, Han is recognized for his innovative approaches to enhancing translation quality through advanced technologies.
Latest Patents
Han's latest patents focus on systems and methods for automatic post-editing of machine translated content. One of his notable inventions involves presenting machine translated segments of a document along with their associated quality estimation scores. This method allows for the invocation of an automated post-editing system for segments that exhibit unsatisfactory translation quality. By inputting these segments into a generative AI model, Han's approach produces revised translations that meet or exceed predetermined quality thresholds. His work emphasizes the iterative nature of the generative AI process, ensuring that the final output achieves a satisfactory translation.
Career Highlights
Jingyi Han is currently employed at SDL Inc., where he continues to develop and refine his innovative technologies. His work at SDL Inc. has positioned him as a key player in the advancement of machine translation systems. Han's dedication to improving translation quality has garnered attention within the industry, making him a respected figure among his peers.
Collaborations
Han collaborates with talented individuals such as Mihai Vlad and Dragos Stefan Munteanu. These partnerships enhance the creative process and contribute to the development of cutting-edge solutions in the field of machine translation.
Conclusion
Jingyi Han's contributions to automatic post-editing technologies reflect his commitment to innovation in machine translation. His patents and work at SDL Inc. demonstrate his expertise and dedication to improving translation quality through advanced methodologies.