Qian Wang

Title: Qian Wang: Innovating Resource Scheduling and High Slope Deformation Prediction

Introduction:

Qian Wang, a Beijing-based inventor, has made significant contributions to the fields of resource scheduling for deep learning frameworks and high slope deformation prediction. With an impressive portfolio of 146 patents, Wang has showcased his expertise in developing novel methods and systems to address critical challenges in these domains. This article delves into his latest patents, key career highlights, notable collaborations, and the impact of his innovations.

Latest Patents:

One of Wang's recent patents is the "Method and apparatus for scheduling resource for deep learning framework." This invention presents an automated approach to manage the allocation and release of resources for deep learning training tasks. By leveraging a Kubernetes platform, Wang's method intelligently schedules physical machines to initiate the training, ensuring efficient resource utilization.

Another notable invention is the "Prediction method and system of high slope deformation." This patent introduces a prediction method that utilizes historical deformation data and Support Vector Machine (SVM) models. By optimizing parameter groups using a Particle Swarm Optimization (PSO) algorithm, Wang's system accurately predicts high slope deformations, aiding in proactive measures to mitigate risks.

Career Highlights:

Qian Wang has been associated with leading companies in the technology sector. He has contributed his expertise to Boe Technology Group Co., Ltd., a renowned technology company specializing in display solutions. Working with Beijing Boe Optoelectronics Technology Co., Ltd., he has been at the forefront of developing cutting-edge technologies and innovative solutions.

Collaborations:

Throughout his journey, Wang has collaborated with esteemed colleagues to bring his inventions to life. Notably, he has worked closely with Xiaochuan Chen and Wenqing Zhao, who have made significant contributions to their respective fields. These collaborations have allowed Wang to refine his ideas and leverage complementary expertise, resulting in groundbreaking innovations.

Conclusion:

Qian Wang's contributions in resource scheduling for deep learning frameworks and high slope deformation prediction have propelled these fields forward. Through his patents, Wang showcases his ability to develop efficient solutions that automate resource allocation and accurately forecast deformations. His career highlights and collaborations demonstrate his commitment to impactful and collaborative innovation. As an inventor of significant repute, Qian Wang continues to inspire and contribute to advancements in the world of technology.