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This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.
This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Please email datascience@stanford.edu to receive the registration passcode. We kindly ask that you register using your Stanford email.
Hosted by Stanford Data Science and the Stanford Doerr School of Sustainability, the fourth Sustainability Data Science Conference (April 17) unites data and sustainability scientists to tackle pressing environmental challenges using innovative datasets, methods, and algorithms.
Students and postdocs will give 8–10-minute presentations, sharing novel datasets, data-driven analyses, or key research questions requiring data science and AI.
| Time | Session Title | Speaker(s) |
| 9:00 – 9:30 AM | Registration & Breakfast | |
| 9:30 – 9:40 AM | Opening Remarks | David Lobell |
| 9:40 – 10:40 AM | Session 1: Remote Sensing & Large-Scale Modeling | |
| Smoke on the Water: Wildfire Impact on Cyanobacterial Bloom Proliferation | Teso Coker | |
| Towards Precision Environmental Health: Estimating Individual Air Pollution Exposure with AI | Ziv Lautman | |
| Governing Generative Landscape Design: Spatial AI and Indigenous Protocols for Heritage Reconstruction in Morocco’s High Atlas | Hamza Woodson | |
| The Child Health Burden of Stagnant Water | Steve Berggreen | |
| The Urban Infill Paradox: Integrating Community, Code, and Carbon | Eunice Jung | |
| Agent-Based Modeling of Food Market Dynamics Under Climate Variability in Karnataka | Aarabhi Achanta | |
| 10:40 – 10:45 AM | How the SDSS Center for Computation Can Support Your Data Science Research | Ellianna Abrahams, Brian Chivers |
| 10:45 – 11:00 AM | Break | |
| 11:00 AM – 12:00 PM | Session 2: Machine Learning & Energy Systems | |
| On the Adversarial Robustness of Hydrological Models | Joseph Janssen | |
| Adaptive energy planning unlocks diverse decarbonization pathways and mitigates lock in risks | Mofan Zhang | |
| 3D Scene Reconstruction and Plant Segmentation using Density Based Clustering and Gaussian Splatting | Rudraksh Mohapatra | |
| Probing the Mechanistic Understanding of an AI Foundation Model Fine-tuned for Air Quality Forecasting | Jason Hu | |
| Transfer Learning for Battery State-of-Health Estimation via Electrochemical Impedance Spectroscopy | Sai Thatipamula | |
| A New Intelligence Layer for LFP Batteries: Reliable State of Charge Estimation for Optimal Energy Dispatch | Andrea Lanubile | |
| 12:00 – 1:00 PM | Lunch | |
| 1:00 – 2:10 PM | Session 3: Statistics, Causal Inference & LLMs | |
| Rice methane emission prediction using minimal empirical sampling | Zhenglin Zhang | |
| Tropical Cyclone Intensity Drives Nonlinear Increases in Dengue Burden | Emma Krasovich Southworth | |
| Corporate Carbon Accountability: Searching for Credible Signals in Public/Private Reports | Aldis Elfarsdottir | |
| Climate attribution in local news coverage of natural hazards | Ekaterina Landgren | |
| The socio-economic impacts of sand mining in India | Suraj R Nair | |
| Can the past predict the future? Climate risks, sovereign debt, and a data driven "storylines" approach | June Choi | |
| The Hidden Energy Costs Of "Set It and Forget It" Parameters In Heating, Ventilation, and Air Conditioning Operations | Rebecca Grekin | |
| 2:10 – 2:20 PM | Closing Remarks |
