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How Many Cycles Does a Random Permutation Have? (Part 1)

12 minute read

Published:

A few days ago, I was doom-scrolling on Instagram and came across a post that shared an interview problem of a quant firm: “Let $C_n$ denote the number of cycles in a random permutation of $[2n] = \{1,2,\ldots,2n\}$ whose lengths are greater than $n$. What is $\lim_{n \to \infty} \mathbb{E}[C_n]$?”. It caught my attention almost immediately, since permutation problems were among my favorites back when I did competitive programming. “This should be quite easy for me,” I said to myself, and started doing some calculations. Oh boy. It opened up a whole rabbit hole, leading me to a bunch of related questions, and a few interesting findings of my own, that ended up consuming most of my weekend.

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publications

Technical Report for ICML 2024 Automated Math Reasoning Challenge: Solving Optimization Problems with Open Source Large Language Model

Published in AI4Math @ ICML, 2024

This technical report presents an approach utilizing open-source Large Language Models for Automated Optimization Problem-solving With Code Challenge at the ICML 2024 AI4Math Workshop.

Recommended citation: Duc M. Nguyen, and Sungahn Ko. 2024. Technical Report for ICML 2024 Automated Math Reasoning Challenge: Solving Optimization Problems with Open Source Large Language Model. In AI for Math Workshop @ ICML 2024, Vienna, Austria.
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DG Comics: Semi-Automatically Authoring Graph Comics for Dynamic Graphs

Published in IEEE VIS, 2024

This paper introduces DG Comics, a novel comic authoring tool for dynamic graphs that allows users to semi-automatically build and annotate comics.

Recommended citation: Kim, J., Lee, H., Nguyen, D. M., Shin, M., Kwon, B. C., Ko, S., & Elmqvist, N. (2024). Dg comics: Semi-automatically authoring graph comics for dynamic graphs. IEEE Transactions on Visualization and Computer Graphics.
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VEHME: A Vision-Language Model For Evaluating Handwritten Mathematics Expressions

Published in EMNLP Main Conference, 2025

The paper introduces VEHME, a vision-language model for automated grading of handwritten math solutions.

Recommended citation: Thu Phuong Nguyen, Duc M. Nguyen, Hyotaek Jeon, Hyunwook Lee, Hyunmin Song, Sungahn Ko, and Taehwan Kim. 2025. VEHME: A Vision-Language Model For Evaluating Handwritten Mathematics Expressions. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 31781–31801, Suzhou, China. Association for Computational Linguistics.
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‘Here, Let Me Help’: An Empirical Study of User Interventions in Human–Web Agent Collaboration

Published in ACM CHI, 2026

This work presents an empirical study of user interventions in human–web agent collaboration.

Recommended citation: Joohee Kim, Sungbeon Cho, Duc M. Nguyen, Jaehyeong Jeon, Minjeong Shin, and Sungahn Ko. 2026. "Here, Let Me Help": An Empirical Study of User Interventions in Human–Web Agent Collaboration. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems, Barcelona, Spain.
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Technical Report for AI4Math-2026 Track 3: VeraPhys: Verified Ensemble Repair for Multimodal Physics Reasoning

Published in AI4Math @ ICML, 2026

This technical report presents an approach utilizing open-source Large Language Models for Automated Optimization Problem-solving With Code Challenge at the ICML 2026 AI4Math Workshop.

Recommended citation: Duc M. Nguyen, and Sungahn Ko. 2026. Technical Report for AI4Math-2026 Track 3: VeraPhys: Verified Ensemble Repair for Multimodal Physics Reasoning. In AI for Math Workshop @ ICML 2026, Vienna, Austria.
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teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.