Benjamin Segal

Title: Innovations by Benjamin Segal in Demand Forecasting

Introduction

Benjamin Segal is an accomplished inventor based in Dallas, TX, known for his contributions to the field of demand forecasting. He has been instrumental in developing innovative solutions that leverage deep learning techniques to enhance forecasting accuracy. With a total of 2 patents, Segal's work is making a significant impact in the industry.

Latest Patents

Segal's latest patents focus on a deep learning-based demand forecasting system. This method involves training a neural network to approximate forecasting errors of a passenger-demand forecasting model. The process includes calculating historical passenger demand forecasts for various key levels and departure dates, applying a dropout model to create a training sample, and training the neural network to approximate forecasting errors. The system ultimately calculates future passenger demand forecasts and approximates the associated forecasting errors for upcoming departure dates.

Career Highlights

Benjamin Segal is currently employed at American Airlines, Inc., where he applies his expertise in demand forecasting to improve operational efficiency. His innovative approaches have garnered attention and recognition within the industry, showcasing his commitment to advancing technology in transportation.

Collaborations

Segal collaborates with talented colleagues, including Na Deng and Ou Bai, who contribute to the development and refinement of forecasting models. Their teamwork enhances the effectiveness of the solutions they create.

Conclusion

Benjamin Segal's work in deep learning-based demand forecasting exemplifies the intersection of technology and innovation in the transportation sector. His contributions are paving the way for more accurate and efficient demand forecasting methods.