Stanford Bits & Watts is a major new Stanford University initiative focused on innovations for the 21st century electric grid—a new grid paradigm that is needed to incorporate large amounts of clean power and a growing number of distributed energy resources, while simultaneously enabling grid reliability, resilience, security and affordability. Stanford has a culture of cross-campus collaboration, entrepreneurial spirit, and deep engagement with the industry and our ecosystem. Bits & Watts Leadership is committed to bring resources together to create strategic value for their members in these times of significant change.

Invited by Prof Arun Majumdar, the co-director of Stanford Bits & Watts Initiative, LKYCIC adjunct fellow, Dr Andy Zheng, gave a talk on “Digitalize and Electrify City’s Fleets” via tele-conference with the Bits & Watts research team, who are involved in the EV50 project (50% penetration of Electric Vehicles in all passenger cars). Please find the video for the talk to Stanford Bits & Watts team on 13 Feb 2020 (PST), as well as the abstract.


On-demand mobility services have grown explosively in recent years, often at the cost of public transit ridership, threatening global targets for air pollution and carbon emissions. Electrifying taxi and ride-hailing fleets is often challenged by upfront purchase cost, charging infrastructure, and charging time. Based on 20,000 electric taxis in Shenzhen, China, our research shows that such barriers can be vastly reduced with intelligent charging coordination, enabled by real-time dataset of vehicle trajectories, energy consumption, and charging station availability. Moreover, digitalization, along with fleet electrification, can be an enabler for a host of data-driven optimizations and policies to transform urban mobility towards the goals of lower carbon emissions, less congestion, and better fiscal sustainability. A few examples of AI research opportunities with such high-quality dataset will also be discussed.

About the speaker and PAIR

Dr Andy Zheng is the founder of Aspiring Citizens Cleantech that built the PAIR mobility big data platform for digitalizing and electrifying city’s fleets. With a plug-and-play ease of scaling, PAIR’s cloud-based SaaS platform now processes data of 2.8 million taxi and ride-hailing trips daily, and serves 4 major Chinese cities of 60,000 taxis (about 30,000 are electric vehicles).

He is also an adjunct fellow at the Lee Kuan Yew Centre for Innovative Cities, working on the Smart Scaling initiative that believes in inclusive and scalable smart city innovations. His research interests in renewable energy and innovation have led him to focus on researching and developing novel data-driven solutions that optimize energy use and minimize carbon footprint in a smart city context.

He earned his PhD in Mechanical Engineering from the University of California Berkeley in 2014 He has been working on innovative solutions to empower the taxi and ride-hailing industry. His views on reforming taxi industry have been published in top Chinese media and he is also involved in Buenos Aires’ taxi modernization effort.