The Fastest Path to Zero Initiative at the University of Michigan was launched in 2019 to support the University’s commitment to lead in research and policy development surrounding clean energy.

The Fastest Path team is committed to driving the rapid deployment of carbon-free energy solutions to combat climate change. We’re on a mission to empower communities and policymakers with the tools, knowledge, and resources needed to achieve equitable and sustainable energy transformations. From nuclear energy to other zero-carbon alternatives, we focus on practical, scalable solutions that meet the diverse needs of today’s energy landscape.

Our work spans from deep technical research to hands-on community engagement, ensuring that all stakeholders—from policymakers and energy developers to local leaders—are equipped to lead in the transition to a clean energy future. We believe that the path to zero carbon emissions is not just a technological challenge but also a social one, and we are committed to advancing energy justice, inclusivity, and sustainability in every project we undertake.

By collaborating with communities, governments, industry, and academia, we are accelerating the transition to a cleaner, safer, and more equitable energy future for all.

Gender Champions in Nuclear Policy

Fastest Path is proud to be a Gender Champion in Nuclear Policy, a leadership network dedicated to breaking down gender barriers in the nuclear field. We pledge to:

• Include in at least one public speech, presentation, or article per academic semester, content about the problems related to gender inequality, need for better inclusivity, and ways to address it.
• Establish a list of women experts endorsed by Fastest Path to Zero by September 2020. As we are approached for quotes or interviews, we will refer to this list and actively track our suggestions as well as the response of the inquiring organization.
• Track our invitation and acceptance lists for our major public events to ensure we are inviting women and getting participation. We will analyze the acceptance statistics to revise our approach if we fall short.