This inventor holds 3 USPTO granted patents and 2 published patent applications. Top assignee: Shanghaitech University. Active years: 2026.
Company Filing History:
Years Active: 2026
Title: Chaolin Rao: Innovator in Neural Radiance Field Training
Introduction
Chaolin Rao is a prominent inventor based in Shanghai, China. He has made significant contributions to the field of machine learning, particularly in the area of neural radiance fields. His innovative work has led to the development of a unique patent that enhances the training processes of machine learning models.
Latest Patents
Chaolin Rao holds a patent titled "Methods and systems for training quantized neural radiance field." This computer-implemented method involves encoding a radiance field of an object onto a machine learning model. The training process utilizes a set of training images of the object, which includes a first training process using a plurality of first test sample points, followed by a second training process using a plurality of second test sample points located within a threshold distance from the surface region of the object. The method also includes obtaining target view parameters indicating a view direction of the object, obtaining a plurality of rays associated with a target image of the object, and rendering colors associated with the pixels of the target image by inputting the render sample points to the trained machine learning model. Chaolin Rao has 1 patent to his name.
Career Highlights
Chaolin Rao is affiliated with ShanghaiTech University, where he continues to advance his research in machine learning and artificial intelligence. His work has garnered attention for its innovative approach to training neural networks, making significant strides in the efficiency and effectiveness of machine learning applications.
Collaborations
Chaolin Rao collaborates with notable colleagues, including Minye Wu and Xin Lou. Their combined expertise contributes to the advancement of research in their respective fields.
Conclusion
Chaolin Rao is a key figure in the development of methods for training quantized neural radiance fields. His contributions to machine learning and artificial intelligence are paving the way for future innovations in the field.