Zae Myung Kim

I am a third-year Ph.D. candidate in the Minnesota NLP group led by Prof. Dongyeop Kang at University of Minnesota Twin Cities.

My research interests center on developing a “meta-scaffolding paradigm” that integrates discourse structures, dataset metadata, and metacognitive feedback into the training loop of large language models to stabilize learning and produce interpretable, coherent long-form text. I design disciplined training schemes that slash data and compute demands, curtail manual prompt engineering, and steer model reasoning toward human-like cognitive patterns.

Before joining the Ph.D. program, I worked as a researcher at NAVER LABS Europe and Papago team at NAVER Korea, where I researched on various topics in neural machine translation (NMT), such as analysis of language-pair-specific multilingual representation, document-level NMT with discourse information, cross-attention-based website translation, and quality estimation for evaluating NMT models.

I received a B.Eng. degree in Computer Science from Imperial College London in 2011. From 2012 to 2013, I served in the Republic of Korea Army Special Forces as an army interpreter and a geospatial image analyst. In 2016, I received an M.S. degree in Computer Science from Korea Advanced Institute of Science and Technology (KAIST).

During the Spring 2024 semester, I organized the meetings and seminars for Textgroup, an interdisciplinary reading group focused on language. Additionally, since October 2020, I have been leading Seeking-SOTA, a deep learning study group that convenes weekly. This group brings together researchers, academics, and professionals in South Korea, all dedicated to staying at the cutting edge of the field of deep learning. Let me know if you are interested in joining either of these groups!

My Ph.D. program is generously supported by 3M Science and Technology Fellowship and Doctoral Dissertation Fellowship.