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Alice Chen Zhang

Data Science Manager, Charging/Energy Services & Cycle Plan Analytics, Ford

Talk Title: Driving Sustainability at Ford: How Data Science enables the transition

Abstract: Ford Motor Company is committed to building a sustainable future for transportation. Our presentation will begin with a brief overview of Ford’s sustainability journey and the transition to electric vehicles. We aim to showcase the valuable contributions of data scientists in this transformative process by exploring two specific use cases. One case involved using statistical modeling to support product design enhancement, while the other focused on developing models to enhance the electric vehicle customer charging experiences. In both cases, we utilized connected vehicle data and automotive expertise to create analytical models that address business challenges. We will also discuss the obstacles we faced, such as missing data and real-world noise factors. Additionally, we will discuss the customizations of statistical and/or AI/ML models using domain knowledge and physics-based models. Finally, we will conclude by sharing some data-driven business insights and applications.

Bio: Dr. Alice Chen Zhang is a data science manager at Global Data Insights & Analytics, Ford, leading Charging/Energy Services & Cycle Plan Analytics. With a Ph.D. in Applied Mathematics, she has been with Ford since 2015, contributing to On-Road Big Data Analytics, Electric Vehicle Analytics, Sustainability, and Reductive Design. Currently, she leads product teams to deliver data analytics products and services enhancing the customers’ charging experience, supporting Ford’s energy services, and ensuring regulatory compliance through connected vehicle data. Dr. Zhang was honored as the technology Rising Star at the 2022 Women of Color STEM Conference and received the 2018 Henry Ford Technology Award (highest technical achievement award at Ford). Known as a people leader, she is dedicated to fostering an inclusive work environment where all employees feel valued and supported.

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