Yuan Chiang
Scholar

Yuan Chiang

Google Scholar ID: kZ2LfBoAAAAJ
UC Berkeley, Lawrence Berkeley National Laboratory
geometric deep learningcomputational materials sciencematerials theoryAI for Science
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Citations & Impact
All-time
Citations
961
 
H-index
10
 
i10-index
12
 
Publications
20
 
Co-authors
0
 
Contact
Emailcyrusyc@berkeley.eduCVOpen ↗TwitterOpen ↗GitHubOpen ↗LinkedInOpen ↗
Publications
3 items
MLIP Arena: Advancing Fairness and Transparency in Machine Learning Interatomic Potentials via an Open, Accessible Benchmark Platform
2025
Cited
0
UniRestore: Unified Perceptual and Task-Oriented Image Restoration Model Using Diffusion Prior
2025
Cited
0
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
arXiv.org · 2024
Cited
0
Resume (English only)
Academic Achievements
  • - Publications:
  • - 2025, NeurIPS Spot: 'MLIP Arena: Advancing Fairness and Transparency in Machine Learning Interatomic Potentials via an Open, Accessible Benchmark Platform'
  • - 2024, ICLR-AI4Mat Poster: 'LLaMP: Large language model made powerful for high-fidelity materials knowledge retrieval and distillation'
  • - 2023, 'A foundation model for atomistic materials chemistry'
  • - 2022, 'Encoding protein dynamic information in graph representation for functional residue identification', published in 'Cell Reports Physical Science'
  • - Projects: Trained MACE-MP-0 and built MLIP Arena
Research Experience
  • - Work experience: Conducting research at UC Berkeley and LBNL
  • - Research projects: Development and benchmarking of foundation machine learning interatomic potentials (MLIP) and using them as a probe to understand and design ferroelectric materials and metal-salt interfaces in Gen IV molten salt fission reactors (MSRs)
  • - Position: PhD candidate
Education
  • - Degree: PhD candidate
  • - School: UC Berkeley and Lawrence Berkeley National Laboratory
  • - Advisor: Prof. Mark Asta
  • - Time: Not specifically mentioned
  • - Major: Materials Science and Engineering
Background
  • - Research interests: Computational materials physics and chemistry at the atomic and molecular levels, with an emphasis on ab-initio calculations, molecular dynamics, and AI/ML to tackle challenges across energy, materials, pharmaceutics, devices, and computing.
  • - Professional field: Materials Science and Engineering
  • - Introduction: A PhD candidate at UC Berkeley and LBNL, focusing on the development and benchmarking of foundation machine learning interatomic potentials (MLIP) and using them as a probe to understand and design ferroelectric materials and metal-salt interfaces in Gen IV molten salt fission reactors (MSRs).
Miscellany
  • - Personal interests: Not specifically mentioned
  • - Other: Collaborated with Prof. Gábor Csányi, Prof. Aditi Krishnapriyan, and many others through these works.
Co-authors
0 total
Co-authors: 0 (list not available)