Siyang Gao
Scholar

Siyang Gao

Google Scholar ID: NK6nQ9YAAAAJ
City University of Hong Kong
simulationstochastic models
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Citations & Impact
All-time
Citations
959
 
H-index
17
 
i10-index
27
 
Publications
20
 
Co-authors
0
 
Contact
Emailsiyangao@cityu.edu.hkCVOpen ↗
Publications
25 items
Learning Propagation Geometry from Message-Passing Feedback
2026
Cited
0
Beyond Site Agreement: Re-estimation for Brain Network Generalization
2026
Cited
0
Data-Efficient Agentic Graph Domain Adaptation via Reliability-Aware Prototype Learning
2026
Cited
0
Explore Before Committing: Hypothesis-Guided Search for Deep Research Agents
2026
Cited
0
Safe-Subspace Pseudo-Label Refinement for Source-Free Graph Domain Adaptation
2026
Cited
0
Unifying Value Alignment and Assignment in Cross-Domain Offline Reinforcement Learning with Heterogeneous Datasets
2026
Cited
0
When Brain Networks Travel: Learning Beyond Site
2026
Cited
0
Learning to Reason with Insight for Informal Theorem Proving
2026
Cited
0
Resume
Academic Achievements
  • Published numerous academic papers in various fields such as automatic control, manufacturing and service operations management, and information and computing. For example:
  • - 'Stochastically constrained best arm identification with Thompson sampling', Automatica, 2025
  • - 'A contextual ranking and selection method for personalized medicine', Manufacturing & Service Operations Management, 2024
  • - 'Asymptotic optimality of myopic ranking and selection procedures', Automatica, 2023
  • and more.
Research Experience
  • Currently an Associate Professor at the Department of Data Science, City University of Hong Kong.
Education
  • Received a B.S. in Statistics and Probability from Peking University in 2009 and a Ph.D. in Industrial Engineering from the University of Wisconsin-Madison in 2014.
Background
  • Research interests include simulation modeling and optimization, large language models, digital twin, machine learning, and healthcare management.