Joyce Galang

M. Sc. (External PhD)

Research interest

My research investigates the robustness and reliability of large language models for high-uncertainty decision-making, with venture capital investment as the primary application domain. Current streams include agent systems, retrieval-augmented reasoning, failure modes of LLMs, and uncertainty quantification. I am especially interested in how a model's own uncertainty becomes entangled with the inherent uncertainty of the decision itself.

Supervision

I am happy to supervise theses and guided research projects. If you are interested, please share a few details about your background using the following link, so I can match you with a project that fits your interests.

Publications

Galang, J. A. C., Mosca, E., Malberg, S., & Groh, G. (2026). LLMs for Venture Capital Investment: Approaches and Open Problems. In Proceedings of the IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI 2026). Springer Nature. (forthcoming)

Bae, J. Y., Malberg, S., Galang, J. A. C., Retterath, A., & Groh, G. (2026). DIALECTIC: A Multi-Agent System for Startup Evaluation. In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2026), Industry Track (pp. 711–727). Association for Computational Linguistics.