Rui (Ray) Ding
12 entries · Atom

Updates

Building an Autonomous Discovery Loop: DToR + T³ + RAPIDS

Three threads of our work from the past two years are now mature enough to wire together into one autonomous discovery loop for the data-scarce, un...

RAPIDS Accepted at ICML 2026 AI4Physics Workshop

Our paper “Geometry, Not Energy Surface, Drives the Neutral MLIP–DFT Gap in Atomistic Interaction Surrogates”, the study behind RAPIDS, has been ac...

Schmidt Seed Fund Award: PFAS-Selective Membrane Interfaces

I’ve been awarded a 2026 AI in Science Schmidt Fellowship Seed Fund ($33K, as PI) for the project “AI-Guided Discovery of PFAS-Selective Membrane I...

T³ Framework Accepted to SIGKDD 2026 AI4Science (and ICLR 2026 AI4Mat Spotlight)

Our paper proposing the Text-Twin-Translation (T3) framework has been accepted to the SIGKDD 2026 AI4Science Track (CORE A*). The same work was a S...

Two Papers at NeurIPS 2025 Workshops

Two co-first-authored papers accepted at NeurIPS 2025 workshops, both focused on making AI practical for materials and experimental discovery. AI4...

BRAINIAC Progress Update

Submitted our NSF ACCESS progress report for the BRAINIAC project. Summary of current status: Completed: Published proof-of-concept as MSDE cov...

MSDE Cover Article on Neuromorphic Sensor Design

Our paper on neuromorphic spiking graph neural networks for FET sensor design has been published as the cover article in Molecular Systems Design &...

Paper Published in Science Advances

Our work on multi-stage machine learning for catalyst discovery is now published in Science Advances. The paper combines data mining, active learn...

NSF ACCESS Allocation for BRAINIAC

Received an NSF ACCESS allocation (1.5M credits) to support the BRAINIAC project. The computing resources will enable large-scale LLM processing of...

Review Published in Chemical Society Reviews

Our comprehensive review on machine learning for electrocatalyst design has been published in Chemical Society Reviews. The article surveys ML appl...

Preprint: Multi-Stage ML for Catalyst Discovery

Posted our preprint on multi-stage machine learning for electrocatalyst discovery. The work combines data mining, active learning, and domain adapt...

Joining UChicago and Argonne

Started as an Eric and Wendy Schmidt AI in Science Fellow at the University of Chicago, with a joint appointment as Resident Associate at Argonne N...