Project Roadmap

1. Understanding the Project

2. Curation of the Materials

3. Replication of the Project

4. Current Status Update

What is EEPS 1720?

• Research Goal: Identify recent work leveraging machine learning to tackle climate change, focusing on climate science and adaptation.

• Target Audience: Students concentrating in Earth Environmental and Planetary Sciences (EEPS) or Computer Science.

• Course Structure: Mix of reading, discussing relevant literature, and completing an original project as part of a multidisciplinary team.

Overarching Concepts

1. Climate Theme and Machine Learning Topic:

   • Climate Science:

     • Climate Models and Prediction

     • Physics-informed learning & emulators

   • Disasters and Extreme Weather:

     • Explainable AI (XAI) & Uncertainty quantification

   • Farms and Forests:

     • Computer Vision: Super Resolution

   • Ocean and Marine Ecosystems:

     • Policy Optimization for Ecosystem Management

Selected Papers

• Curation of the Materials: Selection based on the criteria of readability and the level of background required.

Metrics for Assessing Scholarly Articles

• Readability: Scale from 1-10, with 10 being the easiest to read.

• Level of Background Required: Categorized as Low, Medium, or High.

• Goal: Assemble a syllabus with an equal workload across units, balancing the level of difficulty for each assignment.