The speaker of the talk gave the presentation of her project of event detection leveraging attention based approach. Nowadays a large amount of event data are out there in many domains such as social media, health record, and e-commercial webs. The understanding of past events may help us to anticipate future events. The problem and challenge here are that, given a sequence of events, how do we predict the type and time of future events. One existing mathematical tool for modeling sequences is point process, but it has the drawback of strong assumption on the generative process that may not reflect the reality. In this talk, the speaker presented an RNN based model with an attention layer to automatically learn the underlying dependencies among events from the event sequence history. By giving results from real-world data, the speaker fully demonstrated the potential of the model.