Mohammad Ghasemzadeh

Title: Innovations by Mohammad Ghasemzadeh

Introduction

Mohammad Ghasemzadeh is an accomplished inventor based in San Diego, CA. He has made significant contributions to the field of machine learning, with a focus on hardware-based acceleration and model training techniques. His innovative approaches have led to the development of two notable patents.

Latest Patents

Ghasemzadeh's latest patents include a method for hardware-based machine learning acceleration. This method involves partitioning input data into batches for processing by a hardware accelerator implementing a machine learning model. The approach allows for real-time updates of a probability density function associated with the model, enhancing the efficiency of data processing. His second patent focuses on training machine learning models with limited training data. This method transforms a trained model by replacing layers with a dictionary matrix and a coefficient matrix, resulting in a reduced-dimension representation of the model's weight matrix.

Career Highlights

Ghasemzadeh is affiliated with the University of California, where he continues to advance research in machine learning and artificial intelligence. His work has garnered attention for its practical applications and innovative methodologies.

Collaborations

He collaborates with notable colleagues, including Bita Darvish Rouhani and Farinaz Koushanfar, contributing to a dynamic research environment that fosters innovation.

Conclusion

Mohammad Ghasemzadeh's contributions to machine learning through his patents and research at the University of California highlight his role as a leading inventor in the field. His innovative methods are paving the way for advancements in technology and data processing.