How can hidden network structure be recovered from limited neural dynamics?
Time series · structure inference · neural connectivity
X(t) → GPERSONAL ACADEMIC SITE · 2026
Jiaqi C.aiAI蔡嘉麒
Neural dynamics.Collective decisions.
Two independent lines of inquiry: inferring neural network structure from dynamics, and understanding judgment, influence, and consensus in large groups.
01 / 05RESEARCH QUESTIONS
SCROLL TO EXPLORE
How can groups reach reliable consensus without losing minority value?
Minority value · trust structure · consensus
Σ wᵢxᵢ → C01 / 02
02 / RESEARCH PROGRAMS
A
COMPUTATIONAL NEUROSCIENCENetwork inference
Network inference
from dynamics
Recovering directed, weighted connectivity from bandwidth-limited neural time series by combining temporal evidence with relational graph context.
B
DECISION SCIENCECollective decisions
Collective decisions
& consensus
Modeling trust, social influence, and preference aggregation to preserve valuable minority alternatives and support adaptive consensus.
03 / PUBLICATIONS
Published
work.
Research on large-scale group decision-making, minority alternatives, consensus, and adaptive aggregation.
01
2025 · APPLIED SOFT COMPUTING · 183FIRST AUTHOR
A method to detect the unpopular but valuable alternatives in large-scale linguistic group decision making
Jiaqi Cai, Xiao Tan, Zaiwu Gong, Wu Tong
DOI · 10.1016/j.asoc.2025.113594
02
2026 · CHINESE JOURNAL OF MANAGEMENT SCIENCE · 34(3)ARTICLE
Group Intelligence Consensus Decision Modeling Based on Reinforcement Learning with the “Structure–Information” Coupled Network
Xiao Tan, Jiaqi Cai, Zaiwu Gong
DOI · 10.16381/j.cnki.issn1003-207x.2024.2237
04 / EDUCATION
Academic
trajectory
Training across management science, data-driven inquiry, systems engineering, and brain-inspired intelligence.
01
M.S.BRAIN-INSPIRED INTELLIGENCE
Management Science and Engineering
National University of Defense Technology · College of Systems Engineering02
B.M.UNDERGRADUATE
Big Data Management and Application
Nanjing University of Information Science & Technology · School of Management Science and EngineeringNANJING → CHANGSHA
JQ / 2026
Jiaqi C.aiAI蔡嘉麒
COMPUTATIONAL NEUROSCIENCE · DECISION SCIENCE
05 / ABOUT
M.S. RESEARCHER · BRAIN-INSPIRED INTELLIGENCE
In computational neuroscience, I frame connectivity recovery as a structural inverse problem, identifying latent edges, directionality, and interaction strength from bandwidth-limited dynamics. In decision science, I study how collective opinions emerge and evolve, with particular attention to minority value and the roles of trust and social influence in information aggregation and consensus.