 So, Daniel, what are you doing at Yale these days? How are you spending your time? You're an assistant professor there, and then you sort of double as chief scientist that adapts. I want to go there, but tell me what's going on at Yale. Yeah, sure. So Yale, so we're sort of expanding our group. So there's two faculty who are part of the database group. There's myself, and I got him Avi Silverchat. So he actually wrote one of the most popular textbooks in the Davis industry. So he's a real legend in the field. He's been around for a long time. We came from Texas, and he was a VP at Bell Labs before joining Yale. So between the two of us, we have a very large lab. We have four PhD students. We have something like five, six undergraduates and a couple other students who are sort of floating in and out. So there's a bunch of projects that we have going on. So certainly HadoopDB, that was what Hedat was called before it was commercialized, was a major project. We also have several other projects too, which I think are pretty interesting. One project that we have is a project called Calvin, which is sort of looking at how to scale transactions. So it doesn't really fit so much in the Hadoop world, which is more focusing on data processing and analytics. But there's still one key problem, especially in the NoSQL world, is how do you issue transactions across a thousand machines and scale that up? Today, the key value stores don't really support transactions. If you look at HBase, if you look at Cassandra, really any of the popular NoSQL systems, they allow a ton of corporations on individual keys, but they don't really scale those operations across thousands of nodes. At least not the transaction itself. You can have individual updates in thousands of nodes. You can't make sure that all happens automatically. So one project that we have going on at Yale is sort of trying to fix that problem. And we have one paper ready on that, and we are sort of in the middle of working another one. I think that's a pretty cool project. Another project, which I'm actually going to talk about today here at Hadoop World, I think it's at 3.30 PM, is sort of a project on a graph database system. So how do you basically figure out the relational model? I mean, I think we sort of know how to build data warehouse. We know how to do data processing and scale relational data. And Hadoop is great for unstructured data. But now we have graph data. Graph data is becoming very popular. We have social networks. We have telecoms, companies. We have linked data, which is like semantic web. So there's all kinds of data which are now sort of best represented as graphs. So it seems like one key research through us that's going to have to happen in the database industry is to be able to figure out database systems for graph data. So I have a student, Jerry Wang, who is doing a special thesis on that. And I'm going to present some of that work that we've done together today at Hadoop World. So that would be pretty cool.