School of Engineering
Showing 161-170 of 477 Results
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Meagan Mauter
Associate Professor of Photon Science, Senior Fellow at the Woods Institute for the Environment and at the Precourt Institute for Energy and Associate Professor, by courtesy, of Chemical Engineering and of Civil & Environmental Engineering
BioProfessor Meagan Mauter is appointed as an Associate Professor of Civil & Environmental Engineering and as a Center Fellow, by courtesy, in the Woods Institute for the Environment. She directs the Water and Energy Efficiency for the Environment Lab (WE3Lab) with the mission of providing sustainable water supply in a carbon-constrained world through innovation in water treatment technology, optimization of water management practices, and redesign of water policies. Ongoing research efforts include: 1) developing automated, precise, robust, intensified, modular, and electrified (A-PRIME) water desalination technologies to support a circular water economy, 2) identifying synergies and addressing barriers to coordinated operation of decarbonized water and energy systems, and 3) supporting the design and enforcement of water-energy policies.
Professor Mauter also serves as the research director for the National Alliance for Water Innovation, a $110-million DOE Energy-Water Desalination Hub addressing water security issues in the United States. The Hub targets early-stage research and development of energy-efficient and cost-competitive technologies for desalinating non-traditional source waters.
Professor Mauter holds bachelors degrees in Civil & Environmental Engineering and History from Rice University, a Masters of Environmental Engineering from Rice University, and a PhD in Chemical and Environmental Engineering from Yale University. Prior to joining the faculty at Stanford, she served as an Energy Technology Innovation Policy Fellow at the Belfer Center for Science and International Affairs and the Mossavar Rahmani Center for Business and Government at the Harvard Kennedy School of Government and as an Associate Professor of Engineering & Public Policy, Civil & Environmental Engineering, and Chemical Engineering at Carnegie Mellon University. -
Michaëlle Ntala Mayalu
Assistant Professor of Mechanical Engineering and, by courtesy, of Bioengineering
BioDr. Michaëlle N. Mayalu is an Assistant Professor of Mechanical Engineering. She received her Ph.D., M.S., and B.S., degrees in Mechanical Engineering at the Massachusetts Institute of Technology. She was a postdoctoral scholar at the California Institute of Technology in the Computing and Mathematical Sciences Department. She was a 2017 California Alliance Postdoctoral Fellowship Program recipient and a 2019 Burroughs Wellcome Fund Postdoctoral Enrichment Program award recipient. She is also a 2023 Hypothesis Fund Grantee.
Dr. Michaëlle N. Mayalu's area of expertise is in mathematical modeling and control theory of synthetic biological and biomedical systems. She is interested in the development of control theoretic tools for understanding, controlling, and predicting biological function at the molecular, cellular, and organismal levels to optimize therapeutic intervention.
She is the director of the Mayalu Lab whose research objective is to investigate how to optimize biomedical therapeutic designs using theoretical and computational approaches coupled with experiments. Initial project concepts include: i) theoretical and experimental design of bacterial "microrobots" for preemptive and targeted therapeutic intervention, ii) system-level multi-scale modeling of gut associated skin disorders for virtual evaluation and optimization of therapy, iii) theoretical and experimental design of "microrobotic" swarms of engineered bacteria with sophisticated centralized and decentralized control schemes to explore possible mechanisms of pattern formation. The experimental projects in the Mayalu Lab utilize established techniques borrowed from the field of synthetic biology to develop synthetic genetic circuits in E. coli to make bacterial "microrobots". Ultimately the Mayalu Lab aims to develop accurate and efficient modeling frameworks that incorporate computation, dynamical systems, and control theory that will become more widespread and impactful in the design of electro-mechanical and biological therapeutic machines.
