Company Filing History:
Years Active: 2020-2025
Title: Innovations of Inventor Xiao Zeng
Introduction
Xiao Zeng is a prominent inventor based in Lansing, MI (US), known for his contributions to the field of deep learning neural networks. With a total of 5 patents, Zeng has made significant strides in developing systems that enhance the efficiency and adaptability of artificial intelligence applications.
Latest Patents
Zeng's latest patents include groundbreaking work on "Systems and methods for implementing flexible, input-adaptive deep learning neural networks." This patent describes innovative systems and methods for creating computationally-efficient deep neural networks that adapt their complexity based on input data, such as video streams. The approach utilizes fine-grained design and an automatic method for generating optimal network architectures, which can be implemented in various devices, including smartphones and drones.
Another notable patent is "Systems and methods for providing flexible, multi-capacity models for use of deep neural networks in mobile devices." This invention allows mobile devices to utilize deep learning neural networks more effectively by considering the dynamics of runtime resources. The multi-capacity framework enables models to offer flexible resource-accuracy trade-offs, maximizing performance while efficiently using limited resources.
Career Highlights
Xiao Zeng is affiliated with Michigan State University, where he continues to push the boundaries of research in deep learning technologies. His work has garnered attention for its practical applications in mobile vision systems and other resource-constrained environments.
Collaborations
Zeng collaborates with talented individuals such as Mi Zhang and Kai Cao, contributing to a dynamic research environment that fosters innovation and creativity.
Conclusion
Xiao Zeng's contributions to deep learning neural networks exemplify the potential of innovative technologies in enhancing mobile applications. His patents reflect a commitment to advancing the field and improving the efficiency of artificial intelligence systems.