Members

We are a distributed research collective focused on time series intelligence and pattern discovery in industrial systems and smart systems. This page features our collaborators — researchers, engineers, and developers engaged in joint studies, publications, and software projects.

Collaboration is open and interest-driven: anyone with relevant expertise or curiosity is welcome to join seminars, initiate research, or co-develop tools and methods.

Contributors

• Song Qingqing, PhD (in progress), Belarus

  • Affiliation
    Faculty of Applied Mathematics and Computer Science, Belarusian State University;
    Technology R&D Center, South China Institute of Frontier Science (Guangdong)

  • Research Focus
    Performance Time Series Analysis, Data Pattern Recognition.
  • Contact
    Email: song.qq@scifs.ac.cn | ORCID: 0009-0000-5872-2602

• Zhu Fu, PhD (in progress), China

  • Affiliation
    School of Electronic and Optical Engineering, Nanjing University of Science and Technology.

  • Research Focus
    High speed coherent laser radar signal processing, Short time signal reconstruction.
  • Contact
    Email: zfu_opt@163.com

• He Runhai, PhD (in progress), Finland

  • Affiliation
    Faculty of Medicine, University of Helsinki.

  • Research Focus
    Medical Clinical and Imaging Analysis, Multimodal Data Analysis.
  • Contact
    Email: runhai.he@helsinki.fi | Google Scholar: He Runhai

• Sun Maoran, MSocSc, China

  • Affiliation
    Zhejiang Sci-Tech University;

  • Research Focus
    Systems Science, Data-Driven Inquiry in the Social Sciences, Machine Learning for Social Data.
  • Contact
    Email: sunmaoran0911@163.com

• Zhen Wu, MSc (Economics), MSc in Appl. Math & Inf. (in progress), Belarus

  • Affiliation
    Faculty of Applied Mathematics and Computer Science, Belarusian State University;

  • Research Focus
    Software Development, CNN Training, Economic Data Analysis.
  • Contact
    Email: fpm.uCH@bsu.by | Google Scholar: Wu Zhen

How to Collaborate With Us?

We welcome new collaborators from academia, industry, and clinical practice. If you are working on:

• Time series analysis under nonstationary conditions,
• Interpretable pattern recognition methods,
• Efficient model optimization for edge deployment,
• Re-discovering actionable insights from latent data patterns (e.g., emergent trends, hidden rhythms, or structural anomalies).

👉 You are welcome to reach out to any collaborator listed above to discuss shared research interests or potential collaborations. Our group operates through open dialogue and mutual initiative.

This research collective is self-organized and led by early-career researchers.
While we gratefully acknowledge the academic environments provided by our affiliated institutions.