NICE America Research, Inc Employee Directory
Research ServicesCalifornia, United States11-50 Employees
Who are we? China Energy is the world’s largest electric utility, producing over 15% of China’s electricity. It operates the world’s largest generation fleet of coal-fired power plants and wind turbines. The National Institute of Clean and low-carbon Energy (NICE) was founded in 2009 and employs over 400 researchers at its HQ in Beijing. As the corporate R&D division of China Energy, NICE is charged with developing and commercializing clean energy technologies. NICE America opened in 2016 and is the North American subsidiary of NICE. Our mission is to leverage the strengths of China Energy and the US innovation ecosystem to create, incubate, and launch the next generation of energy technologies. We're building a team with technical backgrounds from across a range of technical disciplines. How do we approach technology development? NICE America takes a system-level approach towards technology development. We begin by evaluating the business and technology landscapes in order to understand the gaps and identify opportunities and requirements for new technology. During this process, we draw on our perspective of the situations in both the US and China to generate insights that help us focus on where we can develop unique and meaningful solutions. Projects at NICE America range from early stage exploratory research through technology demonstration in support of commercial venture launches. For individual projects, we start with the end in mind. Success is defined in terms of new technology needs to enable potential business models. With our goal to catalyze the development of clean energy technologies, we try hard to celebrate projects that teach us why we need to abandon a particular technical path as much as we celebrate projects that produce significant commercial revenue. What are we working on? NICE America currently has projects in four thematic areas – Hydrogen energy, Energy storage solutions, Shale gas and chemicals, and Data-driven optimization.
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