Joonghyuk Hahn

About Me

I am a PhD candidate in Computer Science at Theory of Computation (ToC) Lab, Yonsei University. My research bridges formal language theory and natural language processing (NLP), with a focus on topics such as M-unambiguous languages, language sparsity, and probability convergence. On the NLP side, I work on few-shot learning, self-training techniques, and grammar-based data augmentation. I’m nearing the end of my PhD and have published multiple papers in both theoretical and applied domains.

Research

• M-equivalence, strong M-equivalence, and language sparsity
• Formal language theory and computational complexity
• Natural language processing (NLP) with a focus on few-shot learning and self-training techniques
• Grammar-based data augmentation and its application in text classification
• Parikh matrix mapping and its relevance to computational linguistics

Recent News

• 📄 I had an oral presentation of our paper, TCProF: Time-Complexity Prediction SSL Framework, in NAACL 2025. Read more
• 📄 Advanced code time complexity prediction approach using contrastive learning accepted at EAAI 2025. Read more
• 📄 Characterizations of M-equivalence and Weak M-relation accepted at IJFCS 2025. Read more