I’m a software engineer at Microsoft. I recently graduated from Harvey Mudd College with a B.S. in Mathematics and Computer Science. Formerly, I was a research intern at Professor George D. Montañez’s AMISTAD Lab, where I received the 2024 Barry Goldwater Scholarship and the 2025 CRA Outstanding Undergraduate Researcher Award.

Recent News

  • September 24th, 2025: Paper “Controllable Clustering with LLM-driven Embeddings” accepted to EMNLP 2025 Industry track (link)

  • July 29th, 2025: Extended paper “Analyzing and Comparing Machine Learning Models via Inductive Orientation” accepted to Lecture Notes in Artificial Intelligence ICAART post-publication issue (publication date: December 5th, 2025)

  • May 16th, 2025: Graduated from Harvey Mudd College and recieved the “Class of ‘94” Computer Science Departmental Award

  • May 12th, 2025: Presented at CRA Undergraduate Research Awardee Lightning Talks

  • February 23rd, 2025: Presented paper “Model Characterization with Inductive Orientation Vectors” at ICAART 2025

  • January 16th, 2025: Received CRA Outstanding Undergraduate Researcher Award (news item)

  • November 11th, 2024: Received Stavros Busenberg Prize in Applied Mathematics (Mathematics Departmental Award)

Publications

Pang-Naylor, K., Chen, E., Montañez, G. (in press). Analyzing and Comparing Machine Learning Models via Inductive Orientation. In International Conference on Agents and Artificial Intelligence. Springer International Publishing.

Pang-Naylor, K., Manivasagan, S., Zhong, A., Garg, M., Mondello, N., Buckner, B., Chang, J., Mahajan, K., Hashemi, M., & Casati, F. (2025). Controllable clustering with LLM-driven embeddings. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track (pp. 686–702). Association for Computational Linguistics. (ACL archive link)

Pang-Naylor, K., Chen, E., Montañez, G. (2025). Model Characterization with Inductive Orientation Vectors. In 17th International Conference on Agents and Artificial Intelligence (ICAART 2025). doi:10.5220/0013304400003890.

Pang-Naylor, K., Li, I., Rajesh, K., Montañez, G. D. (2024). Probabilistic Error Guarantees for Abductive Inference. IEEE International Conference on Future Machine Learning and Data Science (IEEE FMLDS). doi:10.1109/fmlds63805.2024.00038.