IDEaS Short Talks Presents Emanuele Di Lorenzo

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Event Details
  • Date/Time:
    • Monday November 19, 2018 - Tuesday November 20, 2018
      2:30 pm - 2:59 pm
  • Location: TSRB Auditorium; 2:30pm
  • Phone:
  • URL:
  • Email:
  • Fee(s):
    Free
  • Extras:
Contact

ideas@gatech.edu

Summaries

Summary Sentence: Emanuele Di Lorenzo talks about ”Predicting How Social-Ecological Systems Respond to Climate Forcing"

Full Summary: No summary paragraph submitted.

Media
  • Emanuele Di Lorenzo, Georgia Tech Emanuele Di Lorenzo, Georgia Tech
    (image/png)
IDEaS Short Talks and Networking Social
 
”Predicting How Social-Ecological Systems Respond to Climate Forcing"” by Emanuele Di Lorenzo

Monday, November 19, 2018
Part of Two Short 30-MinuteTalks from 2-3 pm
Networking Social from 3-3:30 pm
Technology Square Research Building (TSRB) Auditorium
(You are welcome to attend any part of these events as your schedule permits.)
 
IDEaS is running a series of short talks to learn about research across the Georgia Tech campus. The presentations are from broadly different topics and accessible to those in other research areas. Come chat with colleagues and learn more about what’s new in Data Science! 
 
Emanuele Di Lorenzo
Professor in the School of Earth & Atmospheric Sciences 
Georgia Institute of Technology
2:30 - 3:00 pm
 
”Predicting How Social-Ecological Systems Respond to Climate Forcing"
 
Abstract: Modeling and predicting the response of social-ecological-environmental systems (SEES) to external perturbations like climate forcing is complex because of the assumption that both climate and social-ecological dynamics are characterized by large degrees of freedom, and that relationships are highly non-linear. But what if that was not true? What if we could develop models that keep track only of the dominant underlying dynamics of the SEES? In the climate community, we are developing advanced model of the earth system that can resolve environmental changes almost at the human scale (~10km) generating PB of information. However, the link between these earth system model and models of the social-ecological dynamics are still an impossible challenge limiting our ability to generate integrated understanding and to predict how SEES respond to climate forcing. This is not only due to the large dimensionality of the social-ecological systems but also because of the uncertainties that exist in defining the fundamental equation of the SEES dynamics. Under the assumption that statistical data-driven models can potentially bridge the gap between climate, ecological and social dynamics, and potentially extract low-dimensional relationship that capture most of the evolution of a given SEES, I will present a few case studies that I would like to explore with colleagues at Georgia Tech using novel approaches in data science.

Bio: Dr. Emanuele Di Lorenzo is Professor and Director of the Program in Ocean Science and Engineering (http://www.ocean.gatech.edu) at the Georgia Institute of Technology in Atlanta, USA. His research interests are in the field of multi-scale climate and ocean dynamics (large-scale, regional and coastal), climate impacts on marine ecosystems and social-ecological systems. In his research, Dr. Di Lorenzo attempts to explain the dominant (e.g. low order) dynamics of the ocean and marine ecosystem variability and change by combining available observations with a hierarchy of numerical models (e.g. dynamical and statistical) of ranging complexity. Dr. Di Lorenzo also serves as the Vice-Chair of Science Board for the North Pacific Marine Science Intergovernmental Organization (PICES) and as Chair of their Physical Oceanography and Climate committee. He is also co-chair of the US CLIVAR Phenomena, Observations, and Synthesis Panel and a member of Future Earth Ocean Knowledge Network. Recently, he has led the new OceanVisions joint initiative between Georgia Tech, Stanford, Scripps and Smithsonian (www.oceanvisions.org).

 

 

Additional Information

In Campus Calendar
Yes
Groups

EAS, Ocean Science and Engineering (OSE)

Invited Audience
Faculty/Staff, Postdoc, Graduate students, Undergraduate students
Categories
Seminar/Lecture/Colloquium
Keywords
real-time data, data science, School of Earth & Atmospheric Sciences, EAS Seminar
Status
  • Created By: nlawson3
  • Workflow Status: Published
  • Created On: Nov 14, 2018 - 11:18am
  • Last Updated: Nov 14, 2018 - 12:33pm