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Ph.D. student in Earth Sciences at Cornell University
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Portrait of Yulong Liu

Yulong Liu

Ph.D. student in Earth Sciences at Cornell University.

I work across computational mechanics, implicit neural representation, poromechanics, and subsurface energy systems, with a focus on surrogate modeling for coupled multiphysics problems in Earth science. I am also increasingly interested in homogenization theory and physics-aware implicit neural representations.

Computational mechanicsImplicit neural representationPoromechanics
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Program
Ph.D. in Earth Sciences
Advisor
Chloé Arson
Focus
Computational mechanics · INR · Poromechanics
Base
Ithaca, New York
Email
yl3825@cornell.edu

Research

Current directions in my work.

01

Computational mechanics

Developing deformation, damage, and fracture models for geomaterials within the MOOSE finite element framework.

02

Implicit neural representation

Continuous neural representations, physics-informed neural networks, and operator-learning surrogates for geometry-aware, physics-aware prediction, with growing interest in homogenization theory and physics-aware INR methods.

03

Poromechanics

Mechanics and transport in porous subsurface media, with a focus on poromechanics and multiscale transport.

Publications

Current publication list.

  1. 2026 Preprint

    CodeMOOSE: Multi-Agent Collaborative Framework for Multiphysics MOOSE Language

    Yulong Liu(co-first author, corresponding author), Zhenghan Song

    arXiv preprint, January 2026

    Open-source release in preparation.

  2. 2026 Conference paper

    Operator Learning Surrogate Modeling of Hydraulically Fractured Geothermal Injection-Production Systems: A Cornell Case Study

    Yulong Liu, Jonah Botvinick-Greenhouse, Yunan Yang, Chloé Arson

    ARMA 2026, Tucson

    Find in Scholar
  3. 2026 Preprint

    A Physics-Informed Neural Network for Modeling Pressurized Cavities of Arbitrary Smooth Shape Embedded in Heterogeneous Rock

    Yulong Liu, Chloé Arson

    Research Square preprint

    Currently under review.

    Read preprint
  4. 2026 Journal article

    Numerical assessment of plasticity development and energy expenditure of ant-like microtunnelling

    M. Belachew, Yulong Liu, J. D. Frost, Chloé Arson

    Tunnelling and Underground Space Technology, 172, 107501

    Open journal page
  5. 2025 Conference paper

    Physics-informed neural network surrogate modeling of pressurized cavity in homogeneous and bilayered media

    Yulong Liu, Chloé Arson

    ARMA US Rock Mechanics/Geomechanics Symposium, D022S018R006

    Find in Scholar
Comparative field plots for displacement, stress, and error around a circular cavity.
Stage-wise stress evolution figure from ant-like microtunnelling study.
Generalization comparison across fracture configurations.

Education

Academic path.

2024 - Present · Ithaca, New York

Cornell University

Ph.D. student in Earth Sciences

Department of Earth and Atmospheric Sciences · GPA 3.88 / 4.3

2020 - 2024 · Shenyang, China

Northeastern University

B.S. in Mining Engineering

College of Engineering · GPA 3.94 / 4.5

Undergraduate thesis A Unified Model for Microseismic Signal Classification and Arrival-Time Picking Based on Deep Learning

Awards & service

Recognition and academic contribution.

Awards

  • 2025 · Estwing Hammer Award, outstanding EAS graduate student of 2024
  • 2024 · Outstanding Thesis, outstanding undergraduate thesis
  • 2024 · National Scholarship, most outstanding student in the university
  • 2023 · First Class Scholarship
  • 2022 · Autumn Scholarship and Golden Seed Scholarship

Academic service

  • Reviewer, Rock Mechanics and Rock Engineering
  • Reviewer, International Conference on Artificial Neural Networks 2026

Talks

Invited seminar.

Invited seminar

December 31, 2025

A Physics-Informed Neural Network for Modeling Pressurized Cavities of Arbitrary Smooth Shape Embedded in Heterogeneous Rock

Southwest Petroleum University seminar series, Chengdu, China