Data mining

Her research examines machine learning and AI for interactive domains and structured data, looking at how the data points that AI systems are trained on affect their behaviors and how that aligns with what users actually want.

Across that research, she's published more than 130 papers with over 10,000 citations and received honors such as a National Science Foundation Career Award, a spot on IEEE's 10 to Watch in AI list, and best paper awards from the International Conference on Data Mining and the International Conference on Learning Representations.

What amazes me most about Jen's work is her foresight and ability to have a through line that stays consistent as the field of AI develops.

And I'm excited to hear more about how she got to where she is today.

And at that point, I was interested in data, and I was interested in AI.

And I thought a lot, I did a lot of reading.

And what I decided that I wanted to investigate was how to do data mining on web data that was interconnected.

And so that, when I decided that was a question I wanted to work on, I got pointed to a particular faculty member who had just started working in this nascent field at the time that was called statistical relational learning.

conferences.

I just went to KDD in Korea, where Jeff Dean gave a keynote.

And KDD, as you know, traditionally is a sort of knowledge discovery and data mining conference.

And it's been publishing groundbreaking work on data management, data discovery.

But these number of years, it's been pivoting also to some more general AI.