Armanda is a doctoral candidate at NYU working at the intersection of the learning sciences, AI, and ethical HCI. Her dissertation, overseen by Professors Xavier Ochoa, Todd Gureckis, and He He, explores open questions on using multimodal large language models to model inclusion and facilitate how people can learn to be more inclusive. Her work as a senior research scientist at the Center for R/AI advances research on how people teach and learn about responsible AI topics. She holds an M.S. from the NYU Center for Data Science, a masters in interactive technology from NYU Tisch, and a doctorate in literature and ethics from Columbia University. In her free moments, she likes to spend time with her family, create interactive textile art, and read.
Selected publications
Using Case Studies to Teach Responsible AI to Industry Practitioners
Julia Stoyanovich, Rodrigo Kreis Paula, Armanda Lewis, and Chloe Zheng
In Proceedings of the AAAI Conference on Artificial Intelligence 2025
@inproceedings{stoyanovich_meta_eaai25,title={Using Case Studies to Teach Responsible AI to Industry Practitioners},author={Stoyanovich, Julia and de Paula, Rodrigo Kreis and Lewis, Armanda and Zheng, Chloe},year={2025},booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},keywords={education},pages={29062-29069},url={https://doi.org/10.1609/aaai.v39i28.35177},doi={https://doi.org/10.1609/aaai.v39i28.35177}}
We Are AI: Taking Control of Technology
Julia Stoyanovich, Armanda Lewis, Eric Corbett, Lucius Bynum, Lucas Rosenblatt, and Falaah Arif Khan
In Proceedings of the AAAI Conference on Artificial Intelligence 2025
@inproceedings{stoyanovich_weareai_eaai25,title={We Are {AI}: Taking Control of Technology},author={Stoyanovich, Julia and Lewis, Armanda and Corbett, Eric and Bynum, Lucius and Rosenblatt, Lucas and {Arif Khan}, Falaah},year={2025},booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},keywords={conference,education,weareai},pages={29070-29077},url={https://doi.org/10.1609/aaai.v39i28.35178},doi={https://doi.org/10.1609/aaai.v39i28.35178}}
Teaching Responsible Data Science
Armanda Lewis, and Julia Stoyanovich
International Journal of Artificial Intelligence in Education (IJAIED) 2022
@article{LewisStoyanovich21,author={Lewis, Armanda and Stoyanovich, Julia},title={Teaching Responsible Data Science},journal={International Journal of Artificial Intelligence in Education (IJAIED)},volume={32},number={3},pages={783--807},year={2022},keywords={journal,education,rds},addendum={Special Issue: The FATE of AI in Education: Fairness, Accountability, Transparency, and Ethics},doi={https://doi.org/10.1007/s40593-021-00241-7},site={https://dataresponsibly.github.io/rds/},}