Publications (6)
Funding AI for Good: A Call for Meaningful Engagement
Hongjin Lin, Anna Kawakami, Catherine D'Ignazio +2
Artificial Intelligence for Social Good (AI4SG) is a growing area that explores AI's potential to address social issues, such as public health. Yet prior work has shown limited evi…
PCTreeS: 3D Point Cloud Tree Species Classification Using Airborne LiDAR Images
Hongjin Lin, Matthew Nazari, Derek Zheng
Reliable large-scale data on the state of forests is crucial for monitoring ecosystem health, carbon stock, and the impact of climate change. Current knowledge of tree species dist…
"Come to us first": Centering Community Organizations in Artificial Intelligence for Social Good Partnerships
Hongjin Lin, Naveena Karusala, Chinasa T. Okolo +2
Artificial Intelligence for Social Good (AI4SG) has emerged as a growing body of research and practice exploring the potential of AI technologies to tackle social issues. This area…
Consistent Explanations in the Face of Model Indeterminacy via Ensembling
Dan Ley, Leonard Tang, Matthew Nazari +3
This work addresses the challenge of providing consistent explanations for predictive models in the presence of model indeterminacy, which arises due to the existence of multiple (…
GenAI for Systems: Recurring Challenges and Design Principles from Software to Silicon
Arya Tschand, Chenyu Wang, Zishen Wan +21
Generative AI is reshaping how computing systems are designed, optimized, and built, yet research remains fragmented across software, architecture, and chip design communities. Thi…
Hevelius Report: Visualizing Web-Based Mobility Test Data For Clinical Decision and Learning Support
Hongjin Lin, Tessa Han, Krzysztof Z. Gajos +1
Hevelius, a web-based computer mouse test, measures arm movement and has been shown to accurately evaluate severity for patients with Parkinson's disease and ataxias. A Hevelius se…