Junyong Lee

이준용

Ph. D. Candidate

Yonsei University

Intersection of Machine Learning & Quantum Computing

I'm Junyong, a Ph.D. candidate at Yonsei University working with Prof. Shiho Kim. I have a dual interest that keeps my brain busy: making machines smarter with Machine Learning and exploring the future of computation with Quantum Computing.

My true talent isn't writing code, but figuring out what to write. Python is my go-to for the execution part. And how do I come up with the ideas? I'm a firm believer in "beer-storming" over brainstorming.

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news

Sep 2025 | Successfully wrapped up my role as a mentor for the "Q-MAML for High Energy Physics" project in the GSoC 2025 program. [Medium]

Sep 2025 | Presented our paper, "Aligning Multimodal LLMs with Patient-Physician Dialogues," at the MICCAI 2025 Workshop. [Full Paper]

Apr 2025 | Our work on Quantum Model-Agnostic Meta-Learning (Q-MAML) has been officially published at AAAI 2025. [Full Paper]

Apr 2025 | Two of our papers, one on data-centric approaches for NISQ computers and another on gate selection in quantum circuits, have been accepted to the QDML 2025 Workshop.

Mar 2025 | Our paper on uncertainty prediction in autonomous driving using VisionLLMs, presented at the AAAI 2025 LM4Plan Workshop.

Mar 2025 | Our paper, "Enhancing Circuit Trainability with Selective Gate Activation Strategy," has been accepted for a full presentation at the QC+AI Workshop at AAAI 2025 in Philadelphia. [Paper]

Sep 2024 | Presented two posters on our latest research in Quantum Diffusion Models and AI Explainability at the IEEE International Conference on Quantum Computing and Engineering (QCE24). [Poster1] [Poster2]

Educations

Ph.D. in Integrated Technology

Yonsei University, Seoul, South Korea Mar 2021 - Present (Expected Graduation: Aug 2026)

Visiting Scholar
- Carnegie Mellon University, Pittsburgh, PA, USA (Fall 2023)
Advisor: Prof. Shiho Kim
Key Research Areas: Quantum Computing, Meta-Learning, Hybrid Quantum-Classical Systems, AI Accelerators.