Expert Seminar on Survival Mixed Membership Blockmodel for Analyzing Time-to-Event in Social Networks
31 March 2026
The Department of Computer Science organized an expert seminar on 31 March 2026. The seminar focused on the topic “Survival Mixed Membership Blockmodel for Analyzing Time-to-Event in Social Networks.” It was held at Hall 2 on the ground floor.
Our guest speaker was Dr. Fangda Song from the School of Data Science at the Chinese University of Hong Kong, Shenzhen. Dr. Song is a renowned scholar focusing on Bayesian statistical modeling and efficient inference algorithms, with his research published in top international academic journals such as JASA and Nature Communications.
The seminar took place from 3:30 pm to 5:30 pm. During his presentation, Dr. Song explored the innovative applications of the Survival Mixed Membership Blockmodel (SMMB). He discussed how to solve the modeling challenges of response times for “node pairs” in social networks and demonstrated how this model can be applied to the famous Enron email corpus to uncover hidden organizational structures and power dynamics.
This seminar was a compulsory session for the Capstone Project (RAI601) and part of the Master of Science in Applied Artificial Intelligence (MSAAI) programme. The insights shared by Dr. Song provided valuable inspiration for the students’ graduation projects and future research directions.
We thank Dr. Song for sharing his deep academic expertise with us. Thanks also to all students and staff who attended the seminar.
