Company Filing History:
Years Active: 2022
Title: Shunan Guo: Innovator in Predictive Technologies
Introduction
Shunan Guo is a prominent inventor based in Shanghai, China. He has made significant contributions to the field of predictive technologies, particularly through his innovative patent. His work focuses on utilizing advanced neural networks to analyze and visualize outcomes based on historical data.
Latest Patents
Shunan Guo holds a patent titled "Predicting and visualizing outcomes using a time-aware recurrent neural network." This patent discloses systems and methods that predict and visualize outcomes based on past events. The analysis application encodes a sequence of events into a feature vector, which includes a numerical representation of each event's category and timestamp. By applying a time-aware recurrent neural network to this feature vector, the application can generate a set of future events, each associated with a probability and predicted duration. Additionally, it produces a sequence embedding that contains information about predicted outcomes and temporal patterns observed in the sequence of events. The application further employs a support vector model classifier to compute the likelihood of categorical outcomes for each event in the probability distribution. This innovative approach allows for the modification of interactive content based on the predicted categorical outcomes and probability distribution.
Career Highlights
Shunan Guo is currently employed at Adobe Inc., where he continues to develop cutting-edge technologies. His work at Adobe has positioned him as a key player in the realm of predictive analytics and machine learning.
Collaborations
Shunan collaborates with talented individuals such as Fan Du and Eunyee Koh, contributing to a dynamic and innovative work environment.
Conclusion
Shunan Guo's contributions to predictive technologies through his patent and work at Adobe Inc. highlight his role as a leading inventor in the field. His innovative approaches to analyzing and visualizing outcomes based on past events pave the way for advancements in various applications.