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UID:0-1762@hmc.edu
DTSTART;TZID=America/Los_Angeles:20260313T110000
DTEND;TZID=America/Los_Angeles:20260313T121500
DTSTAMP:20260227T234209Z
URL:https://www.hmc.edu/calendar/events/cs-colloquium-speaker-david-lebaue
 r-computation-for-climate-modeling-agriculture-under-uncertainty/
SUMMARY:CS Colloquium Speaker: David LeBauer\, “Computation for Climate: 
 Modeling Agriculture Under Uncertainty’
DESCRIPTION:“Computation for Climate: Modeling Agriculture Under Uncertai
 nty”\nAbstract\nClimate mitigation in agriculture is ultimately a modeli
 ng problem: how do we turn complex biology and sparse data into reliable d
 ecisions? Soil carbon and greenhouse gas emissions arise from nonlinear pr
 ocesses\, incomplete records\, and uncertain futures. Converting those dyn
 amics into decision-ready tools requires integrating computer science\, st
 atistics\, and domain science in ways that are rigorous\, transparent\, an
 d scalable.\n\nDavid LeBauer will describe his path from ecology to buildi
 ng climate modeling systems that support governments and startups working 
 on carbon and greenhouse gas accounting in managed lands. He chose to buil
 d a career at the intersection of open-source software\, quantitative mode
 ling and public policy.\n\nLeBauer will introduce the computational archit
 ecture behind these systems in accessible terms: how biological processes 
 are encoded in models\, how Bayesian calibration constrains parameters usi
 ng noisy data\, how ensemble simulations and sensitivity analysis propagat
 e and decompose uncertainty\, and how software design and open science pra
 ctices determine whether tools are interpretable\, reproducible\, transpar
 ent and scalable for real-world decision-making.\n\nThe broader message is
  that impactful climate work requires scientific depth\, disciplined softw
 are engineering\, and a commitment to transparency and reproducibility\, a
 nd that there are multiple viable paths to building such a career.\nSpeake
 r\nDavid LeBauer (PhD\, earth system science\, UC Irvine) is a scientist a
 nd consultant working at the boundary of ecology\, statistics\, and scient
 ific computing. He builds open\, reproducible modeling and data infrastruc
 tures that couple process-based ecosystem models\, field measurements\, an
 d Bayesian inference to make ecological predictions transparent\, scalable
 \, and decision-relevant. He is founder of The LeBauer Approach and Modeli
 ng Lead and Project Manager for California’s statewide cropland carbon m
 onitoring and modeling initiative. Previously\, he founded the Data Scienc
 e team at the University of Arizona and led model calibration and validati
 on at Indigo Ag in support of carbon credit protocols. He is creator and l
 ong-time co-lead of the open-source PEcAn ecosystem modeling platform and 
 has led open data and cyberinfrastructure efforts supporting model–data 
 synthesis\, forecasting\, and data-intensive agricultural research.
CATEGORIES:Faculty,Staff,Students
LOCATION:Shanahan Center\, 320 E. Foothill Blvd.\, Claremont\, CA\, 91711\,
  United States
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