Team Member
Weiwei Gu

Weiwei Gu

PhD in Systems Science, Beijing Normal University · Associate Professor

Research Interests

His research develops an integrated representation-inference-intervention framework for AI-driven complex systems. Centered on heterogeneous multilayer networks, his work combines graph representation learning, structural-dynamical modeling, causal inference, reinforcement learning, and world models to characterize and regulate complex-system evolution. These methods have been applied to brain networks, collective behavior, and transportation systems, with a focus on resilience and coordinated optimization.

Education

Professional Experience

Selected Work

  1. Deep-learning-aided dismantling of interdependent networks, Nature Machine Intelligence, first author, 2025
  2. Principled approach to the selection of the embedding dimension of networks, Nature Communications, first author, 2021
  3. MWTP: A heterogeneous multiplex representation learning framework for link prediction of weak ties, Neural Networks, first author, 2025
  4. Assessing the robustness and reducibility of multiplex networks with embedding-aided interlayer similarities, Physical Review E, corresponding author, 2025
  5. An Improved Strategy for Blood Glucose Control Using Multi-Step Deep Reinforcement Learning, ICBBT, corresponding author, 2024

Research Projects

  1. NSFC Young Scientists Fund project on topology robustness optimization of multilayer infrastructure networks using representation learning and reinforcement learning
  2. Original exploration project on coastal critical-process identification and early warning using cross-sphere multiscale data assimilation and dynamical modeling
  3. China Postdoctoral Science Foundation project on early signals of venture capital institution failure based on learning dynamics
  4. Industry collaboration project on marine environmental factor analysis and visualization
  5. Participation in NSFC Key Programs, National Key R&D Programs, and Young Scientist Projects

Honors

Recruitment

Postdoctoral researchers, graduate students, and undergraduate interns with backgrounds in computer science, automation, mathematics, physics, statistics, or related fields are welcome to get in touch.

Teaching

Contact & Links