CV

Contact Information

• Name: Jiheng Liang
• Affiliation: School of physics,Sun Yat-sen University, Guangzhou 510275, China
• E-mail Address: liangjh65@mail2.sysu.edu.cn

Education

• Master.Science.
  • School of physics, Sun Yat-sen University, Guangzhou,China
  • 2022 - 2025 (expected)
  • Major: Optics
  • Research Topics: AI4Science, particular on “Innovative Spectral (physical, i.e. Near-Infrared spectrum) Analysis Methods driven by Large Language Model (LLM)”
    
• Bachelor.Science.
  • School of physics, Sun Yat-sen University, Guangzhou,China
  • 2018 - 2022
  • Major: Optoelectronic Information Science and Engineering

Research Experience

• Multimodal Infrared Spectra Analysis through the Integration of Knowledge Graphs and Large Language Model Encoding
  • Apr, 2024 - Present
  • Sun Yat-sen University, Guangzhou, China
  • Advisor: Xiangyang Yu, Ziru Yu
  • We used knowledge graphs to combine spectral experimental data from sample with information from text, graphics and other modalities, and semantically encoded them through LLM to achieve a multi-modal approach to credible spectral analysis
  • Personal contribution：Refinement of research ideas, Construction of knowledge graphs, Design of experimental code
  • Paper (expected): “Enhanced Multimodal Infrared Spectra Analysis through the Integration of Knowledge Graphs and Large Language Model Encoding”

• Spectral Knowledge Q&A System Based on Large Models
  • Sep, 2023 - Jun, 2024
  • Sun Yat-sen University, Guangzhou, China
  • Advisor: Xiangyang Yu, Ziru Yu
  • We collected papers related to spectral detection from 2014-2024. Through information extraction, the papers were converted into specific labels to provide knowledge for LLM as well as to serve as data source for Retrieval Augmented Generation
  • Personal contribution: Refinement of research ideas, Data collection and annotation from theses, Design and implementation of experimental code, Thesis writing
  • Paper (expected): “Quick, trustworthy spectral detection Q&A system based on structured professional literature and driven by Large Language Model”

• Water quality detection based on Ultraviolet and Near-infrared (UV-NIR) spectroscopy
  • Sep, 2022 - Aug, 2023
  • Sun Yat-sen University, Guangzhou, China
  • Advisor: Xiangyang Yu
  • In this project, we acquired water sample data through UV-NIR spectroscopy and used machine learning models and LLM to predict feature indicators
  • Personal contribution: Refinement of research ideas, Collection and analysis of spectral data from water samples, Employing LLM to predict indicators from sample spectrum yields the most optimal outcome, Thesis writing
  • Paper: Information extraction of UV-NIR spectral data in waste water based on Large Language Model

Honors and Awards

• Second-class Scholarship, Sun Yat-Sen University, Sep, 2019
• Outstanding Completion of Innovation Training Program for College Students in Guangdong Province, China, Mar, 2021
• Third-class Award, Challenge Cup in Guangdong, China, Apr, 2021
• First-class Scholarship, Sun Yat-Sen University, Sep, 2022

Publications

Information extraction of UV-NIR spectral data in waste water based on Large Language Model

Liang, J., Yu, X., Hong, W., & Cai, Y. (2024). Information extraction of UV-NIR spectral data in waste water based on Large Language Model. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 124475.

Skills

• Language: proficient in Python
• Computer Science: Macgine Learning, Large Language Model(such as Fine-tune and Deployment), Database processing
• Science Knowledge: Physical laboratory technology, Spectral (Physical) analysis, Optics, Basic Chemistry, Chemometrics analysis
• Competent in Latex, Git