24012 Ecosystem-Based Research Acceleration with AI for Geographical and Social Analysis
Project Description:
Since 2017, RMDS Lab has been a leading developer of ecosystem-based acceleration approaches for data-driven knowledge discovery. Through AI, RMDS’s systems, delivered via AI GPTs and AI assistants, have been serving research labs and researchers worldwide.
Under this project, students will learn and experience the impacts of RMDS’s ecosystem-based acceleration with AI and explore their applications in their respective fields. Students will also have opportunities to contribute to new developments and refinements through data, algorithm, or application development.
Students will learn to:
- Collect and integrate data and documents from various sources.
- Apply the RMDS methodology and workflow technology to research projects in their field of interest.
- Utilize AI and data technologies to assist in developing RMDS acceleration solutions.
Upon completing the research project, students will be invited to present their findings at the Spatial Data Lab’s annual symposium. Additionally, they are encouraged to submit their written reports for publication.
Intern Tasks and Responsibilities:
Students will use the RMDS frameworks and tools to review literature, collect, process, and prepare data, and then assist in building or refining an AI acceleration application in a specialized field. They will also compile final reports and presentations on their projects.
Minimum qualifications of Intern student:
College students who are Interested in research methods and AI with some learning plus strong self-motivation.
Term of the Project: Range from one semester to one academic year.
Mentors:
- Dr. Alex Liu, former IBM Chief Data Scientist and RMDS Lab director.
- Dr. Tom Lu, NASA JPL Senior AI Scientist
- Dr. Hui Su, Adjunct Professor of UCLA and lead of a Global GeoAI Project
- Professor Sijun Wang, Marketing Professor at LMU