Xiangyu Yin

Argonne National Laboratory, Lemont IL

I am an Assistant Computational Scientist at Argonne National Laboratory, working at the intersection of X-ray science, artificial intelligence, and scientific automation. I joined Argonne in 2023 as a Postdoctoral Appointee; before that, I studied computational materials and process systems engineering at Carnegie Mellon University. I am interested in developing intelligent systems that accelerate, automate, and advance scientific discovery.

News

Oct 9, 2026 I presented our poster on claim-aware observability for autonomous scientific agents at LM4Sci@COLM 2026 in San Francisco.

Sept 28, 2026 Our paper Strategies for Deploying AI Agents in Production at Scientific User Facilities is out on arXiv.

Sept 21, 2026 I gave a talk titled Modernizing Classic Forward Models with Differentiable Programming at the New Computational Methods for Imaging at Light and Electron Sources workshop of the Bay Area Light Sources Joint Users’ Meeting.

Aug 18, 2026 Our papers XRF-to-Optical Field-of-View Localization with Vision Language Models and Acquisition Geometry-Assisted Whole-Group Localization of X-ray Fluorescence Maps in Optical Microscopy Images are out on arXiv, with code (1, 2).

July 27, 2026 Our paper Artifact-centered Claim-aware Observability for Autonomous Scientific Agents got accepted by LM4Sci@COLM 2026.

July 22, 2026 I gave a talk on agentic AI for X-ray data analysis in the Workflows Community Talks series.

May 12, 2026 Our paper CVEvolve: Autonomous Algorithm Discovery for Unstructured Scientific Data Processing is out on arXiv.

May 6, 2026 I won a Distinguished Contributor Award for MRS Spring 2026 Tutorial MT01. Check out the tutorial website

March 24, 2026 Our paper AlphaDiffract: Automated Crystallographic Analysis of Powder X-ray Diffraction Data is out on arXiv.

March 5, 2026 Our paper Autonomous Algorithm Discovery for Ptychography via Evolutionary LLM Reasoning is out on arXiv.

Jan 1, 2026 Our paper MapsTorch: automatic differentiation for X-ray fluorescence data analysis is published on the Journal of Synchrotron Radiation.

Sept 20, 2025 Our paper Adapting general-purpose foundation models for X-ray Ptychography in Low-Data Regimes got accepted by AI4Mat@NeurIPS 2025.

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