Hi there, I鈥檓 Xinrui (Ryan) Jiang, a master鈥檚 student in EE at Stanford University. Prior to that, I received my B.Eng from Fudan University. During my undergraduate study, I was fortunate to be advised by Professor Zhengzhong Tu at Texas A&M University and Professor Berkin Bilgic at Martinos Center for Biomedical Imaging/Harvard Medical School.
My current interests include AI agents and visual creation, with recent work on tool-using agents for video editing and generative model evaluation. My earlier research focused on low-level vision, including image super-resolution and quantitative MRI reconstruction. I enjoy starting from real-world needs and observations, framing concrete technical problems, and developing practical methods and systems to address them.
馃摑 Publications
4KAgent: Agentic Any Image to 4K Super-Resolution
Yushen Zuo, Qi Zheng, Mingyang Wu, Xinrui Jiang, Renjie Li, Jian Wang, Yide Zhang, Gengchen Mai, Lihong V. Wang, James Zou, Xiaoyu Wang, Ming-Hsuan Yang, Zhengzhong Tu
Paper 路 Code 路 Project Page
- We present 4KAgent, an agentic image super-resolution generalist designed to universally upscale any image to 4K resolution, regardless of input type, degradation level, or domain.
NLCG-Net: A Model-Based Zero-Shot Learning Framework for Undersampled Quantitative MRI Reconstruction
Xinrui Jiang, Yohan Jun, Jaejin Cho, Mengze Gao, Xingwang Yong, Berkin Bilgic
Paper 路 Code 路 Presentation
- We purposed NLCG-Net, a model-based and data-driven framework achieved via self-supervised learning, which incorporates nonlinear conjugate gradient optimization and Neural Network Regularization in a iterative manner and achieves zero-shot quantitative MRI reconstruction.
馃搶 Projects
SUMFORU: An LLM-Based Review Summarization Framework for Personalized Purchase Decision Support
- We developed SumForU, a persona-steerable review summarization system built on Thinking Machine鈥檚 Tinker platform. This system fine-tunes LLMs on Amazon 2023 reviews and optimizes for user-aligned summaries via preference-based reinforcement learning.
馃捇 Internships
- 2026.06 - 2026.09, Machine Learning Engineer at DoorDash. Agentic editing orchestrator for multi-defect video repair
- 2025.03 - 2025.08, Machine Learning Engineer at Microsoft. Failure-driven, self-refining LLM-as-a-Judge for large-scale generative media evaluation
- 2024.01 - 2024.04, Machine Learning Engineer at TikTok/Bytedance. Multimodal content understanding and unsupervised mining for short-form video
馃帠 Selected Awards
- 2023.09 Suiwei Scholarship (top 1%)
- 2022.09 National Scholarship (top 1%)
馃専 Fun
In my spare time, I enjoy running (about 3.2 miles each time), building LEGO sets, and hanging out with my American Shorthair cat, Dafu.
