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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.
We're pleased to invite you to the inaugural data science for sustainability series event! This session is a Lunch & Learn on Data Fusion for Sustainability, an informal gathering to discuss methodologies for combining heterogeneous data sources and their applications to sustainability challenges. Please register here!
This session will cover:
Current data fusion techniques and emerging approaches
Case studies: remote sensing + ground truth validation, ML + physics-based models, multi-sensor integration
Applications across climate, energy, agriculture, and conservation research
Opportunities for cross-disciplinary collaboration
Why this matters: Many of us work with incomplete datasets or face challenges in model validation. This session will explore how data fusion approaches are addressing these gaps and may offer relevant methods for your own research.
Event details:
Date: January 22, 2026
Time: 12:00 - 1:30 pm
Location: E365 Conference Room, CoDa Building
Lunch provided!