Dr Phong Le

Reader in Machine Learning

Researcher profile

Email

pl200@st-andrews.ac.uk

 

Research areas

I am a machine learning researcher with extensive experience in both academia and industry, specializing in natural language processing and machine learning. I am passionate about translating cutting-edge research into real-world applications, and I maintain a deep curiosity about fundamental scientific mysteries—particularly the emergence of human language.

See more https://lephong.github.io/

PhD supervision

• Aarushi Sharma
• Victor Yuan

Selected publications

• An emergent communication framework for honeybee waggle dance

  Siregar, N., Le, P. & G. Alhama, R., 21 Apr 2026, The evolution of language: proceedings of the 16th international conference on the evolution of language (EVOLANG XVI). Hartmann, S., Sibierska, M., Fröhlich, M., Jadoul, Y., Josserand, M., Matzinger, T., Mudd, K., Nölle, J., Pleyer, M., Wacewicz, S. & Żywiczyński, P. (eds.). Nijmegen: The Evolution of Language Conferences, p. 435-442 8 p. (International conference on the evolution of language).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Hierarchical Text Classification with LLM-Refined Taxonomies

  Golde, J., Jedema, N., Krishnan, R. & Le, P., 2026, Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers). p. 214–228

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Open access

  Multi-parameter control for the (1+(λ,λ))-GA on OneMax via deep reinforcement learning

  Nguyen, T., Le, P., Doerr, C. & Dang, N., Aug 2025, Proceedings of the 18th ACM/SIGEVO Conference on Foundations of Genetic Algorithms. ACM

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• On the importance of reward design in reinforcement learning-based dynamic algorithm configuration: a case study on OneMax with (1+(λ,λ))-GA

  Nguyen, T., Le, P., Biedenkapp, A., Doerr, C. & Dang, N., Jul 2025, Proceedings of the genetic and evolutionary computation conference 2025 (GECCO '25). New York: ACM, p. 1162 - 1171

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

 

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