The Syracuse Center of Excellence (CoE) is a collaborative organization that accelerates the development of innovations for a sustainable future. As New York State’s Center of Excellence in Environmental and Energy Systems, we have engaged more than 200 private companies, organizations, and academic institutions to create new products and services in indoor environmental quality, clean and renewable energy, and water resource management.
A collaborative organization, CoE works in partnership with CenterState CEO, SUNY College of Environmental Science and Forestry (ESF), SUNY Upstate Medical University, and dozens of industry partners. Additional economic development partners include CenterState CEO’s INSPYRE Innovation Hub, the New York State Science & Technology Law Center, the Central New York Biotech Accelerator, and many other regional organizations.
CoE is housed in an iconic $41-million R&D facility opened in 2010, constructed adjacent to other CNY innovation assets and University Hill in downtown Syracuse. The facility has earned international recognition for its Willis H. Carrier Total Indoor Environmental Quality (TIEQ) Laboratory, which has been used for ground-breaking research such as a study with Harvard University measuring the impact of indoor quality on the cognitive function of office workers.
Currently, CoE faculty are working on multiscale physical testbed and modeling, simulation and visualization tools with advanced sensor capabilities, intelligent and AI-driven building controls, and energy-efficient technologies designed to enhance industry-academic-community collaborations. CoE also houses a Building Training and Assessment Center to provide specialized training to students and professionals in building performance.
CoE’s associated faculty labs and groups offer additional state-of-the-art research capabilities in advanced materials for air cleaning, CO2 absorption, energy conversion and storage, material emissions testing, ventilation, building enclosure assemblies and systems, cold climate heat pumps, and AI/ML-based model predictive control algorithms.