Planetary AI: Data & Experimentation

This webpage integrates a virtual gallery of lunar petrography, an experimental AI chatbot, and an AI literacy curriculum as a multimodal testbed, aiming to use petrographic and geochemical data to explore how AI supports lunar science, museums and mineral galleries, youth engagement, and public understanding.

Virtual Gallery

Images were obtained from Virtual Microscope and subsequently aligned using Python.

Olivine Chat

This is an experimental AI chatbot that will be upgraded over time.

Planetary AI Curriculum

Youth participating in this paid Planetary AI curriculum will work with PPL/XPL images of Apollo lunar thin sections using vision language models; analyze terresrial, lunar, and ureilite olivine-specific geochemical datasets with machine learning techniques; develop skills in critically evaluating AI outputs through scientific reasoning; co-author the interpretive logic of museum kiosk chatbots; and transfer these AI and data-analysis skills to applications such as natural hazard susceptibility.

The AI literacy curriculum is informed by our previous public webinars and the work presented below:

• P. Wang, D. Pelaia, Z. Zou, S. Xiao, A. He, N. He, F. Zhu, N. Mao, J. Wu, J. Wu, C. Neal, and S. Huang," OCR-Enabled Dataset Assembly for Machine Learning in Olivine Geochemistry," ESS Open Archive, December 24, 2025. DOI: 10.22541/essoar.176659907.72242256/v1
• P. Wang and S. Huang, "NSF AISL: Responsible AI in Planetary Scientific Practice," ASEE, 2026
• P. Wang, D. Pelaia, Z. Zou, S. Xiao, A. He, N. He, F. Zhu, N. Mao, J. Wu, J. Wu, C. Neal, and S. Huang, "AI-powered Data Extraction, Integration, and Analysis on the Geochemistry of Returned Lunar Samples,” AGU, 2025.
• D. Pelaia, N. He, and P. Wang, “FLASH: An AI Chatbot for Real-Time Flash Flood Risk Detection and Information Dissemination,” ESS Open Archive, 2025.
• M. Powell, G. Xu, S. Huang, B. Duggan, B. Alexander, P. Wang, V. Mclemore, Virginia, E. Owen, and S. Wei, "Critical Mineral Resource in Heavy Mineral Beach-Placer Sandstone Deposits in New Mexico," GSA, 2025. 10.1130/abs/2025AM-11007.
• Z. Zou, D. Pelaia, N. He, S. Jones, P. Wang, S. Huang, and B. Duggan, "Exploring Trace Element Fingerprinting in Water Samples with Artificial Intelligence," AGU, 2024
• P. Wang, et al., “Experimenting with Emerging Artificial Intelligence and Augmented Reality Technologies Utilizing Planetary Science Data for STEM Education and Public Outreach,” LPI Contributions, vol. 3040, no. 1338, 2024.
• P. Wang and S. Huang, “BOARD #396: NSF AISL: Incorporating Linear Algebra in an AI Literacy Curriculum in Informal and Formal Learning Settings,” in Proc. ASEE Annu. Conf. Expo., 2024. doi: 10.18260/1-2--55770.
• P. Wang, "Engaging Communities in Geo-STEM with Technology," 72nd Annual Meeting of the Rocky Mountain Section, GSA, 2022.

Feedback from participants in our public webinars:

“Dear Ping, I hope this email finds you well. I would like to share some good news with you and Dr. Huang. I got accepted into Caltech! Caltech just released their decisions today. I can't wait to share this good news with you. I would like to thank you for your support of the past 4 years! On many weekends we met to discuss research projects, learn AI and planetary science. And last summer, I felt grateful for the experiences researching with a team under Dr. Huang's guidance at UTK. With your tremendous support, I learned so much regarding research approaches and went further into the realm of AI and Planetary Science. In the meantime, I enjoyed the journey learning and researching, and overcame all the challenges along the way. It really was a precious life changing experience and I appreciate it! Best regards, Alice Z.”

"Good evening Mrs. Wang, I hope you're doing well! I just wanted to let you know that I just got admitted to Princeton University!!! I'm so grateful to have met you and learned from you over the past few years! Thank you so much for all of your support and mentorship throughout this entire process! I appreciate all that you've done for me so much! Warm regards, Nathan H."

We wanted to thank Dr. Brian Duggan (UTK), Dr. Stein Jacobsen (Harvard Univ), Dr. Hairuo Fu (Brown Univ), Dr. Nick Dygert (UTK), Dr. Justin Simon (Johnson Space Center), Dr. Jian Wu (ODU), Dr. Shane Byrne (U.Arizona), Dr. Clive Neal (Notre Dame), Troy Harris (now studying at Stanford), Anya Zhang (studying at Stanford), Alice Zou (now studying at Catech), and Nathan He (who will be studying at Princeton). Particularly, we wanted to thank Dominick Pelaia, a high school student at L&M STEM Academy, Knoxville, TN, who has been working on creating AI chatbots for natural hazards. Dominick has contributed a lot to our curriculum! Nathan Mao, a high school student at the Harker School, San Jose, attended our public webinar sereis and started working on developing classification and segmentation methods for lunar thin section imagery. Two other high school students in the Cambridge area are also working on it, too!

AI-enabled Kiosk Chatbots & Interactive Exhibits

We invite museums / mineral galleries to collaborate on developing and deploying kiosk chatbots and interactive exhibits as platforms for planetary science research, planetary explorations, and public engagement.

Petrographic & Geochemical Datasets

We invite AI researchers to collaborate on planetary science/exploration-focused multimodal learning, explainable and uncertainty-aware AI, and human–AI interaction in public scientific contexts. Collaborations can involve model development, interface design, interpretability studies, or comparative experiments using the planetary datasets and museum deployment.

Acknowledgement

This work is developed by PI Ping Wang who is a Research Scientist at Planetary Science Institute, and is supported by the National Science Foundation under Grant No. DRL-2314155. Any opinions, findings, and conclusions or recommendations expressed are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Contact

pwang@psi.edu