Sherif Barrad

Title: Sherif Barrad: Innovator in Time-Series Forecasting

Introduction

Sherif Barrad is a notable inventor based in Ile-Bizard, Canada. He has made significant contributions to the field of deep learning and quantum computing. His innovative approach to time-series forecasting has garnered attention in the tech community.

Latest Patents

Sherif Barrad holds a patent for "Methods and apparatus for time-series forecasting using deep learning models of a deep belief network with quantum computing." This patent describes an apparatus that includes a Deep Belief Network (DBN) configured to receive input data via a processor. The processor initializes weights for a learning model of the DBN based on the input data. It generates a representation of the input data and transmits the weights, input data, and representation to a quantum compute device. The processor receives sampled values from the quantum compute device using an optimization function and updates the weights to train the learning model. The trained model is capable of generating an updated representation of the input data and producing output data via a regression layer.

Career Highlights

Sherif Barrad is currently employed at Ernst & Young LLP, where he applies his expertise in deep learning and quantum computing. His work focuses on developing advanced methodologies for data analysis and forecasting.

Collaborations

Sherif has collaborated with notable colleagues, including Ricardo A Collado and Biren Agnihotri. Their combined efforts contribute to the advancement of innovative technologies in their field.

Conclusion

Sherif Barrad's work in time-series forecasting and deep learning represents a significant advancement in the intersection of technology and data analysis. His contributions continue to influence the development of innovative solutions in the industry.