Hemil Shah

Title: Hemil Shah - Innovator in Energy Forecasting

Introduction

Hemil Shah is a notable inventor based in Maharashtra, India. He has made significant contributions to the field of energy forecasting through his innovative work. His expertise in deep learning models has positioned him as a key figure in the intersection of technology and energy management.

Latest Patents

Hemil Shah holds a patent for a deep learning model designed for energy forecasting. This system is capable of receiving user inputs that indicate a target variable to be forecasted over a future time window. It determines independent variables that influence the target variable and generates a set of candidate variables, including combinations of these independent variables. The system employs a random forest classifier to identify a subset of candidate variables that have a threshold level of influence on the target variable. Subsequently, it constructs a machine-learning model that receives the identified subset of candidate variables as inputs to generate a forecast of the target variable. The model is trained using historical data to enhance its forecasting accuracy.

Career Highlights

Hemil Shah is currently associated with SAS Institute Inc., where he applies his skills in data science and machine learning. His work focuses on developing advanced analytical solutions that drive efficiency and innovation in energy forecasting.

Collaborations

Hemil collaborates with talented professionals such as Richa Chauhan and Harish Yadav, contributing to a dynamic work environment that fosters innovation and creativity.

Conclusion

Hemil Shah's contributions to energy forecasting through his patented deep learning model exemplify the impact of innovative thinking in technology. His work not only enhances forecasting accuracy but also supports the broader goals of energy management and sustainability.