School of Engineering
Showing 101-150 of 649 Results
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Elizabeth Sattely
Associate Professor of Chemical Engineering
BioPlants have an extraordinary capacity to harvest atmospheric CO2 and sunlight for the production of energy-rich biopolymers, clinically used drugs, and other biologically active small molecules. The metabolic pathways that produce these compounds are key to developing sustainable biofuel feedstocks, protecting crops from pathogens, and discovering new natural-product based therapeutics for human disease. These applications motivate us to find new ways to elucidate and engineer plant metabolism. We use a multidisciplinary approach combining chemistry, enzymology, genetics, and metabolomics to tackle problems that include new methods for delignification of lignocellulosic biomass and the engineering of plant antibiotic biosynthesis.
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Michael Saunders
Professor (Research) of Management Science and Engineering, Emeritus
BioSaunders develops mathematical methods for solving large-scale constrained optimization problems and large systems of equations. He also implements such methods as general-purpose software to allow their use in many areas of engineering, science, and business. He is co-developer of the large-scale optimizers MINOS, SNOPT, SQOPT, PDCO, the dense QP and NLP solvers LSSOL, QPOPT, NPSOL, and the linear equation solvers SYMMLQ, MINRES, MINRES-QLP, LSQR, LSMR, LSLQ, LNLQ, LSRN, LUSOL.
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Carine Sauquet
Administrative Associate, Civil and Environmental Engineering
BioCarine provides administrative support to Prof.Jenna Davis & Prof. Alexandria Boehm & Prof. Meagan Mauter and their teams. Carine earned a Master’s in Computer Science Law and New Technologies, and Bachelor Degree in Business Law from University Paris XI in France. She has a background managing legal operational teams.
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Ludwig Schmidt
Assistant Professor of Computer Science
BioLudwig Schmidt is an assistant professor at Stanford University in the Computer Science Department and Stanford Data Science. Ludwig’s research interests revolve around the empirical foundations of machine learning, often with a focus on datasets, reliable generalization, multimodality, and language models. Recently, Ludwig’s research group contributed to open source machine learning by creating OpenCLIP, DCLM, and the LAION-5B dataset. Ludwig completed his PhD at MIT and was a postdoc at UC Berkeley. Ludwig’s research received a new horizons award at EAAMO, best paper awards at ICML & NeurIPS, a best paper finalist at CVPR, and the Sprowls dissertation award from MIT.