Update week-07.md with guest speaker info

_modules/week-07.md

@@ -1,7 +1,7 @@
 ---
 title: Week 7 - Topic Modeling
 ---
-Topic modeling is a useful tool for exploring large collections of text. It can be used to identify themes in a corpus, to identify outliers, and to explore the relationships between different texts. It is a form of unsupervised machine learning, which means that it does not require a human to provide a training set of labeled data. During the first session of this week, we will look at how the sieving out of topics works, and how to interpret the results. In the second session, we will use [jsLDA](https://mimno.infosci.cornell.edu/jsLDA/) to build a topic model of our own.
+Topic modeling is a useful tool for exploring large collections of text. It can be used to identify themes in a corpus, to identify outliers, and to explore the relationships between different texts. It is a form of unsupervised machine learning, which means that it does not require a human to provide a training set of labeled data. During the first session of this week, we will look at how the sieving out of topics works, and how to interpret the results. In the second session, [Laure Thompson](https://cdh.princeton.edu/people/laure-thompson/) will visit our class and we'll use [jsLDA](https://mimno.infosci.cornell.edu/jsLDA/) to build a topic model of our own.
 
 <details>
   <summary class="session-summary">