Minkyu Jeon

mj7341@princeton.edu / Google Scholar / LinkedIn / X

Minkyu Jeon

Minkyu Jeon is a Ph.D. candidate in the Department of Computer Science at Princeton University, advised by Prof. Ellen D. Zhong. His research develops generative and representation learning methods for scientific inverse problems, with a current focus on heterogeneous cryo-EM reconstruction and AI-driven de novo protein design. He is a former summer research intern and contractor at Prescient Design (Genentech), and a former Associate Computational Biologist and visiting graduate student at the Broad Institute of MIT and Harvard.

Research Interests

My research focuses on generative models, representation learning, and 3D reconstruction for scientific inverse problems, with an emphasis on cryo-EM heterogeneous 3D reconstruction.

Another key area of my research is AI for Science. I am currently working on AI agents for scientific discovery, adaptive masked diffusion models, and scalable generative models for vision and proteins. A major current direction is agentic inference-time scaling for de novo protein design, where LLM-guided search, structural validation, and iterative refinement are combined into executable design workflows.

Selected Projects

News

Date Update
05-2026 Added the current project hub for agentic inference-time scaling for de novo protein design.
04-2026 Preprint released: ConforNets — Latents-Based Conformational Control in OpenFold3.
02-2026 Our work, a transformer-based hypernetwork for cryo-EM reconstruction, has been accepted to CVPR 2026.
12-2025 Preprint released: CryoHype — Reconstructing a thousand cryo-EM structures with transformer-based hypernetworks.
12-2025 Preprint released: CHIMERA — Adaptive Cache Injection and Semantic Anchor Prompting for Zero-shot Image Morphing.
11-2025 Started part-time research internship at Prescient Design (Genentech).
10-2025 Two papers accepted at NeurIPS 2025 Machine Learning for Structural Biology (1 poster and 1 Oral).
06-2025 Excited to begin summer internship at Genentech’s Prescient Design.
06-2025 Preprint released: R3eVision — Survey on Robust Rendering, Restoration, and Enhancement for 3D Low-Level Vision.
05-2025 Passed the general exam. Now I’m a PhD candidate!
09-2024 Our CryoBench paper on cryo-EM heterogeneous reconstruction benchmarks accepted to NeurIPS 2024 (Spotlight).
08-2024 Presented CryoBench paper at Flatiron Institute.
07-2024 Instructed high school students at AI4ALL Princeton.
02-2024 Gave an invited lecture on k-SALSA at CMU MetaMobility Lab.
09-2023 Starting Ph.D. journey at Princeton!
01-2023 Starting an Associate Computational Biologist role at the Broad Institute of MIT and Harvard.
11-2022 Paper on self-supervised representation learning for localization accepted to Information Sciences Journal 2023.
09-2022 Paper on saliency-guided point cloud data mixup accepted to NeurIPS 2022.
07-2022 Paper on GAN-based privacy preservation of retina images accepted to ECCV 2022.
09-2021 Starting as a visiting graduate student at the Broad Institute of MIT and Harvard.

Teaching

Contact

mj7341@princeton.edu / Google Scholar / LinkedIn / X

See publications for a fuller list, or my CV.