North York, Canada

Junheng Wang


Average Co-Inventor Count = 6.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2022-2023

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2 patents (USPTO):Explore Patents

Title: Junheng Wang: Innovator in Predictive Modeling for Autonomous Devices

Introduction

Junheng Wang is a notable inventor based in North York, Canada. He has made significant contributions to the field of predictive modeling, particularly in the context of autonomous devices. With a total of 2 patents to his name, Wang's work is paving the way for advancements in machine learning and automation.

Latest Patents

Wang's latest patents focus on systems and methods for training predictive models for autonomous devices. These innovations involve a method that includes receiving a rasterized image associated with a training object. By inputting this image into a first machine-learned model, a predicted trajectory of the training object is generated. The method further includes converting the predicted trajectory into a rasterized trajectory that spatially corresponds to the rasterized image. Additionally, a second machine-learned model is utilized to determine the accuracy of the predicted trajectory based on the rasterized trajectory. The overall loss for the first machine-learned model is then determined based on this accuracy, allowing for the training of the model by minimizing the overall loss.

Career Highlights

Junheng Wang is currently associated with UATC, LLC, where he continues to innovate in the field of predictive modeling. His work is instrumental in enhancing the capabilities of autonomous devices through advanced machine learning techniques.

Collaborations

Wang collaborates with talented individuals such as Henggang Cui and Sai Bhargav Yalamanchi, contributing to a dynamic and innovative work environment.

Conclusion

Junheng Wang's contributions to predictive modeling for autonomous devices highlight his role as a leading inventor in the field. His innovative patents and collaborative efforts are set to influence the future of machine learning and automation.

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