Sijing Tu

Sijing Tu is a doctoral student and researcher at the Division of Theoretical Computer Science, KTH Royal Institute of Technology, supervised by Professor Aristides Gionis. Their research focuses on algorithmic solutions for challenges in online social networks, including information propagation, opinion formation, and diversity maximization. They have contributed to designing approximation algorithms for computational problems in social network analysis, supported by the ERC Advanced Grant REBOUND.

Research Interests

• Formulating societal problems in social networks as computational models
• Designing provable approximation algorithms for graph mining
• Opinion dynamics and influence modeling in digital environments
• Increasing information diversity in online platforms

Recent Publications

Recent works span sequential diversification, adversarial behavior in opinion models, co-exposure optimization, and graph refinement algorithms. Key conferences include KDD, WWW, CIKM, and WSDM.

Academic Roles

• Researcher, Division of Theoretical Computer Science, KTH (2025)
• Course assistant for Advanced Algorithms, Algorithms and Complexity, and Machine Learning courses