School of Engineering
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Katie Wu
Ph.D. Student in Environment and Resources, admitted Autumn 2022
Ph.D. Minor, Civil and Environmental EngineeringBioKatie's research explores how community-driven social interventions and infrastructure development impact community and climate resilience in informal settlements. Her work advances how we operationalize resilience to better inform community-based strategies, policy, and investments that support urban transformation for vulnerable populations. She incorporates participatory methods essential for driving community-led efforts, ensuring a community's deep participation in every step of the iterative analysis, planning, and decision-making processes, in collaboration with multi-sectoral partners and decision-makers. Katie integrates advanced data science techniques, including network science and graph neural networks (GNNs), with community-generated, ground-truthed data to redefine how resilience is measured and applied for more equitable, community-driven strategies for sustainable development. She uses unconventional data sources, such as satellite imagery and citizen-sourced data, to model the built and natural environment in areas with limited conventional data.
Prior to Stanford, Katie studied data science and AI for Product Innovation at Duke University, where she obtained a Master of Engineering Management (MEM). She was a Sustainability Graduate Intern at Lyft, Inc., where she completed and rebuilt their 2020 Greenhouse Gas (GHG) Inventory and Report and designed an air quality model forecasting potential health benefits of EV adoption for underserved communities. She received an M.S. in Medical Science from the University of Colorado School of Medicine and a B.S. in Animal Science with Distinction in Research from Cornell University. Katie is a Dean's Graduate Scholar in the Doerr School of Sustainability, an Emerson Consequential Scholar with the Stanford Technology Ventures Program (STVP), a Graduate Fellow at the Stanford Institute for Human-Centered AI (HAI), and a Stanford Dalai Lama Fellow. -
Yaochun Yu
Assistant Professor of Civil and Environmental Engineering
BioMy research focuses on functional environmental microbiology and environmental analytical chemistry to uncover and harness microorganisms for chemical biotransformation. We integrate high-resolution mass spectrometry, meta-omics sequencing, molecular microbiology and biochemistry, and computational modeling to identify the functional microbes, genes, and enzymes that drive these processes. Building on these mechanistic insights, we aim to develop environmentally benign chemicals and novel biosolutions for bioremediation and waste-to-resource recovery.
I am also interested in how anthropogenic perturbations (i.e., chemical exposure) reshape microbial biodiversity and ecosystem function across natural and engineered ecosystems. We aim to resolve these cause–effect relationships and, using standardized and synthetic microbial communities, run comparable, hypothesis-driven experiments that translate fundamental insights into predictive tools and practical interventions. The aim is to help keep human activities within the safe operating space of planetary boundaries while advancing environmental and public health. -
Haoqi (Nina) Zhao
Assistant Professor of Civil and Environmental Engineering
BioNina joined Stanford CEE as an Assistant Professor in Summer 2026. Her research bridges computational metabolomics and exposomics to uncover unknown lifestyle chemicals and their impacts on health. Nina earned her B.S. from Peking University, her Ph.D. from the University of Washington, and was a postdoctoral scientist at UC San Diego. She received the Pathway to Independence Award (K99/R00) from the National Institutes of Health in 2025.
The Zhao Lab at Stanford will operate at the interface of environmental chemistry, environmental health, and computational mass spectrometry. We aim to identify previously unrecognized chemical drivers that influence human and ecosystem health. We pursue this goal by developing innovative computational and analytical methods centered around untargeted mass spectrometry. Through these efforts, we aim to enable precision environmental health strategies, inform public health policies, and inspire sustainable chemical design.
Current research interests include (but are not limited to):
1.Leveraging mass spectrometry data repositories and advanced informatics tools to systematically map the chemical exposome.
2.Developing tools and resources for mass spectrometry data analysis to advance exposomics research.
3.Investigating host-microbiome-xenobiotic interactions and their impacts on human health.
4.Integrating toxicology with untargeted screening to accelerate the discovery and risk assessment of unknown molecules.
5.Pediatric environmental health: chemical exposures through breastfeeding and their implications for infant development.
6.Traffic-related chemical pollution: environmental fate, occurrence, and relevance to human exposures.