Dachun Sun

Dr. Dachun Sun serves as an Assistant Teaching Professor in the Department of Computer Science at Worcester Polytechnic Institute (WPI), with additional affiliations in the Data Science and Artificial Intelligence programs. Based in Unity Hall 452, he contributes to WPI's academic mission through both teaching innovation and computational social science research.

His educational foundation was built entirely at the University of Illinois Urbana-Champaign:

• Ph.D. in Computer Science
• M.S. in Computer Science
• B.A. in Music Technology
• B.S. in Computer Science

Dr. Sun's research sits at the critical intersection of artificial intelligence and societal impact, specializing in computational social science through graph neural networks, large language models, and retrieval-augmented generation. His work analyzes polarization in online communities to detect ideological positions and model responses to real-world events, with direct applications in influence campaign detection and crisis response systems. He simultaneously pioneers the integration of AI tools into computer science education while fostering critical awareness of their ethical implications.

His 2023-2024 publications reveal a strong trajectory in temporal reasoning, polarized social graph analysis, and human activity recognition—appearing in top venues like ACM SIGIR and ICCCN. These works demonstrate consistent innovation in knowledge graph reasoning, multimodal representation, and practical AI applications for societal challenges.

Dr. Sun actively mentors students through hands-on research opportunities in his computational social science group, emphasizing collaborative problem-solving for real-world issues. His funded projects directly translate research into tools for crisis response planning and misinformation mitigation.

Though no formal lab name is specified, his research collective focuses on bridging AI methodology with social analysis, maintaining strong industry and academic connections as evidenced by his multi-institutional publications and upcoming CIKM 2024 tutorial on temporal graph learning.