This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Huawei Technologies Co., Limited. Active years: 2025.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2025
Title: Marziehsadat Tahaei: Innovator in Neural Network Compression
Introduction
Marziehsadat Tahaei is a prominent inventor based in Montreal, Canada. He has made significant contributions to the field of artificial intelligence, particularly in the area of neural networks. His innovative work focuses on improving the efficiency of computations within compressed neural networks.
Latest Patents
Marziehsadat Tahaei holds 1 patent for his invention titled "Methods and systems for compressing a trained neural network and for improving efficiently performing computations of a compressed neural network." This patent describes methods and systems for compressing a neural network that performs inference tasks. The invention involves obtaining data samples from a training dataset and inputting them into a trained neural network to generate predictions. Additionally, it incorporates a Kronecker neural network to enhance the prediction process. The invention computes two types of losses, which are combined to adjust the learnable parameters of the Kronecker neural network.
Career Highlights
Marziehsadat Tahaei is currently employed at Huawei Technologies Co., Limited, where he continues to advance his research in neural networks. His work is instrumental in developing more efficient AI systems that can handle complex computations.
Collaborations
Throughout his career, Marziehsadat has collaborated with notable colleagues, including Ali Ghodsi and Mehdi Rezagholizadeh. These collaborations have further enriched his research and contributed to the advancement of technology in the field.
Conclusion
Marziehsadat Tahaei is a key figure in the innovation of neural network technologies. His contributions are paving the way for more efficient AI systems, showcasing the importance of research and development in this rapidly evolving field.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
