AI for Social Good: Between My Research and the Real World

Authors

  • Zheyuan Ryan Shi Carnegie Mellon University

Keywords:

AI For Social Good, Food Security, Data Science, Online Learning, Bandit, Data-driven Optimization

Abstract

AI for social good (AI4SG) is a research theme that aims to use and advance AI to improve the well-being of society. My work on AI4SG builds a two-way bridge between the research world and the real world. Using my unique experience in food waste and security, I propose applied AI4SG research that directly addresses real-world challenges which have received little attention from the community. Drawing from my experience in various AI4SG application domains, I propose bandit data-driven optimization, the first iterative prediction-prescription framework and a no-regret algorithm PROOF. I will apply PROOF back to my applied work on AI4SG, thereby closing the loop in a single framework.

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Published

2021-05-18

How to Cite

Shi, Z. R. (2021). AI for Social Good: Between My Research and the Real World. Proceedings of the AAAI Conference on Artificial Intelligence, 35(18), 15732-15733. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17863

Issue

Section

The Twenty-Sixth AAAI/SIGAI Doctoral Consortium