The Center of Excellence in Earth Systems Modeling & Observations (CEESMO)
Seung Hee Kim-sekim@chapman.edu
Menas Kafatos- kafatos@chapman.edu
Susan Yang-kyang@chapman.edu
Dimitar Ouzounov-ouzounov@chapman.edu
College: Schmid College of Science and Technology
Website: https://www.chapman.edu/scst/research/centers-of-excellence/earth-observing/index.aspx
Overview of scholarly research/creative activity: The Center of Excellence in Earth Systems Modeling & Observations (CEESMO) is an interdisciplinary research unit. The Center focuses on observations of the Earth and modeling and analyzing the Earth systems with particular emphasis on natural hazards such as wildfires, severe weather, floods, dust storms, and earthquakes.
Specific projects working on: CEESMO has been working on multiple projects and details are described below:
- Classification and predictors analysis of heavy rain over Korean peninsula using dual-polarimetric radar and machine learning supported by KMA for 3 years.
- Estimating the wildfire risks using SMAP soil moisture satellite and vegetation data in California, especially along the wildland-urban interface.
- Monitoring and understanding the population hot and cold spots during the wildfire emergency and COVID-19 using crowdsourced population data from Facebook.
- Multi-parameter observations of geosphere interaction linked to natural disasters and interdisciplinary studies of earthquake hazards.
- Assessment of aerosol optical depth in background and polluted conditions using AERONET and VIIRS Satellite data
- In experimental neuroscience, we study 5-HT3 receptors, which play important roles in the pathogenesis and treatment of nausea and vomiting as well as regulation of peristalsis and pain transmission, and α7 nACh.
- Research on mathematical frameworks to address the issues of qualia and conscious awareness. Such approaches are consistent with quantum mechanical views of the role of observation.
Number of students looking to work with: 1-2
Time commitment for students: Meet once a week
When students are needed: Spring 2021
Requirements for students who work with you: Fluent in Python and other programming language, knowledge on machine learning technique
What would students be expected to do: To run machine learning models.