Long (Brian) Yang

Long (Brian) Yang

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🖋 About Me

My research interests include computational chemistry, materials science, and machine learning. Specifically, I focus on accelerating molecular dynamics simulations using neural network potentials (NNPs) and exploring novel materials for energy applications. I am passionate about leveraging machine learning to solve complex problems in materials discovery and optimization. My academic journey has been enriched by hands-on experience in research projects that bridge advanced computational techniques with real-world applications.

📖 Education

  • 2024.04 - Present, Master of Science in Computer Science and Energy Tokyo Institute of Technology (TokyoTech), Tokyo, Japan
    • Research Keywords: Molecular dynamics simulations, neural network potentials (NNPs), materials discovery, proton diffusion, machine learning.
  • 2018.09 - 2022.06, Bachelor of Engineering in Data Science China University of Petroleum, Beijing, China
    • Research Keywords: lung nodule segmentation, medical imaging, deep learning, big data analysis, statistical modeling.

🔥 News

📝 Publications

💬 Conference and Workshop

  • 2025.03.13, The Society of Chemical Engineers, Japan (SCEJ) 90th Annual Meeting
    Title: Molecular Dynamics Simulation of Proton Diffusion in Perovskite Oxides Using Neural Network Potentials
    Authors: (Stu) Yang Long, (Reg) Ishikawa Atsushi
    Keywords: Proton conduction, Molecular dynamics, Computer simulation
    Session: Day 2, 9:20–11:20, Paper ID: PB201
    Location: Katsushika Campus, Tokyo University of Science
    Conference Program

🔬 Research Experience

  • 2024.05 - Present, Research Assistant, Tokyo Institute of Technology

    • Working under Professor Ishikawa’s guidance on material discovery.
    • Running molecular dynamics simulations to analyze diffusion behavior in advanced materials.
    • Developing and fine-tuning neural network potentials (NNPs) for accurate property predictions.
    • Collaborating with team members on computational chemistry studies and preparing technical reports.

  • 2024.09 - Present, Research Collaboration with Fujitsu Research Computing Lab

    • Participated in joint research projects focusing on molecular dynamics simulations for material discovery.
    • Worked on optimizing neural network potentials for simulation efficiency.
    • Supported the development of computational models for advanced material properties.

  • 2021.12 - 2022.04, Undergraduate Researcher, China University of Petroleum

    • Conducted a research project using machine learning techniques to analyze energy efficiency datasets.
    • Preprocessed and visualized experimental data for predictive modeling.
    • Built a prototype system for energy factor analysis and presented findings at the university symposium.

💻 Internships

  • 2024.09 - Present, Fujitsu, Japan Department: Computing Research Institute

    • Conducted above hull energy calculations to assess the thermodynamic stability of materials under various conditions.
    • Analyzed phase stability and formation energy to evaluate candidate materials for advanced applications.
    • Implemented computational methods for high-throughput screening of material stability in different environments.
    • Collaborated with researchers to refine computational workflows and machine learning models for predicting material behaviors.

  • 2024.08 - 2024.08, Rakuten, Japan Department: Communications & Marketing (CM) Division

    • Contributed to the development of a disaster volunteer web application during a summer internship.
    • Developed backend functionality using Python (FastAPI) and managed SQLite databases.
    • Integrated APIs to enable communication between government, volunteers, and hotels.
    • Led database design discussions and collaborated effectively in a cross-cultural team environment.

🎖 Honors and Awards

  • 2024.11, Fujitsu Research Internship Certification, successfully achieved certification for outstanding performance in the internship program.
  • 2024.05 - Present, Research Assistant, Tokyo Institute of Technology
    • Contributing to a project on molecular dynamics simulations and neural network potentials.
  • 2021.10, University First-Class Scholarship, awarded for outstanding academic performance during undergraduate studies at China University of Petroleum.
  • 2020.10, University First-Class Scholarship, awarded for outstanding academic performance during undergraduate studies at China University of Petroleum.
  • 2019.09, Second Prize, Asia-Pacific Mathematical Modeling Contest
    • Recognized for analyzing regional economic vitality using Python, statistical methods, and machine learning.

🛠 Skills

Programming Languages

  • Python, Go, Java, React, C, SQL, HTML, CSS, JavaScript

Tools and Software

  • Simulation and Computational Tools: VASP, ASE, LAMMPS, VESTA
  • Development Tools: FastAPI, Flask, Django, Git, GitHub, Docker, VS Code, Jupyter Notebook, LaTeX, Anaconda
  • Database Management: SQLite, MySQL
  • Machine Learning and Data Analysis: Pytorch, scikit-learn, Matplotlib, Excel

Research Skills

  • Molecular dynamics simulations, neural network potentials, Density Functional Theory (DFT) calculations
  • Phase stability and energy calculations, high-throughput materials screening
  • Machine learning models for materials discovery, statistical analysis, regression modeling

Languages

  • English: Fluent
  • Japanese: Business-level
  • Chinese: Native