Fengqi Li
Assistant Professor of Architecture, School of Architecture, RPI
Dr. Fengqi (Frank) Li is an Assistant Professor of Architecture at Rensselaer Polytechnic Institute (RPI) and a former R&D Associate Staff Member in the Grid-Interactive Controls Group at Oak Ridge National Laboratory (ORNL). His work sits at the intersection of architecture, computational design, and energy systems—advancing urban building energy modeling (UBEM), AI-driven urban and energy planning, and community-scale electrification and climate resilience. Drawing on experience in research, education, and architectural practice, Dr. Li takes cross-disciplinary approaches that anticipate a future urban context defined by renewable integration, material intelligence, and high-variability data, motivating alternative planning frameworks. His research develops computational tools for urban design and planning that account for the energy paradigm shift from fossil fuels to renewable resources, examining how buildings with integrated distributed energy resources (DERs) may reshape urban form, infrastructure roles, and emergent urban topologies.
Before joining RPI as faculty, Dr. Li led DOE initiatives with public, private, and academic partners across building-, district-, and grid scales—serving as software development lead and project lead for Model America/AutoBEM, the Future Typical Meteorological Year (fTMY) datasets, and integrated urban–grid co-planning frameworks. He also held project leadership roles on major awards across DOE’s Energy to Communities (E2C) program, the Technology Commercialization Fund, and contributed to the Southwest Urban Corridor Integrated Field Laboratory (SW-IFL) project.
Dr. Li earned his Ph.D. from the Center for Architecture, Science and Ecology (CASE), where he developed Infomorphism, a hybrid planning framework grounded in Zero Energy Building (ZEB) principles that derives energy-based zoning to prioritize local renewable utilization. The framework integrates AI-based computational models to optimize collective urban form and local energy-exchange networks, maximizing the absorption, storage, and sharing of renewable energy while reducing operational uncertainty and supporting equitable access. Infomorphism was demonstrated in multiple Manhattan neighborhoods, with results published in Building Simulation (2023), SimBuild(2022), and SimAUD (2022).
Dr. Li also holds an M.S. in Architecture from The Cooper Union (Merit Scholar), an M.Arch from Syracuse University (Dean’s Citation), and a B.Eng. in Architecture from East China Jiaotong University. Awards include a Laka Competition ’17 Honorable Mention and a thesis Citation for Wall Parley, an AI-enabled interactive wall installation. His work has been exhibited at the Venice Biennale, Shenzhen–Hong Kong Bi-City Biennale, and the Tallinn Architecture Biennale. He is an ASHRAE associate member, an IBPSA-USA voting member, and a peer reviewer for Energy & Buildings, Nature Scientific Data, and Science and Technology for the Built Environment.
MEDIA
March 5, 2024 “CASE Graduate Profiled for Work With Oak Ridge National Lab”
