Networks are all around us. As such, network science is crucial for our understanding of many applications of high societal relevance (e.g., social and technological networks, epidemics, biological networks). Our research focuses on developing new machine learning methods to discover complex interactions and collective behaviors that determine how various types of events and behaviors in social networks are generated and propagated. In particular, we are interested in developing new approaches for social sensing that are relevant to the immediate concerns around pandemic detection and mitigation.
In: Workshop on Network Interpretability for Deep Learning@ AAAI Conf. on Artificial Intelligence (AAAI), Honolulu, 2019.
Bot Detection in Reddit Political Discussion Inproceedings
In: Proceedings of the Fourth International Workshop on Social Sensing, pp. 30–35, 2019.
In: ACM Transactions on Embedded Computing Systems (TECS), vol. 18, no. 5s, pp. 1–22, 2019.
In: Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 102–114, Springer, Cham 2018.
In: Scientific reports, vol. 8, no. 1, pp. 1–14, 2018.
In: arXiv preprint arXiv:1807.08039, 2018.