By Claire Chang & Austin Froelich

Can you introduce yourself to the Mudd community?

This is my second year here at Mudd. Immediately before this, I worked as a data scientist for Microsoft for roughly a year, and immediately before that, I was a PhD student at Carnegie Mellon University, where I received a degree in machine learning. My research interests are in that same area, looking at what makes machine learning work “under the hood” and trying to understand it from an information theoretic/search perspective.

Also, I’m a father; I have three little kids who keep me plenty busy at home, ages seven, five, and one-and-a-half almost now. I grew up here in the Inland Empire, down the road, in Ontario, so coming here to Mudd has been almost like a homecoming for me.

How do you like Mudd so far?

I’m much happier here at Mudd than I was in industry. I didn’t feel that the work I was doing in industry really mattered all that much, whereas here, I can see every day when I interact with students the impact I’m having on them. I remember I went to the new faculty orientation and they had a panel of students, and I was so excited… I remember asking “when I get here, I really want the students to know that I want to get to know them and spend time with them. How do I do that in a way that doesn’t creep them out immediately?” I remember one of the students told me that I think the students will pick up on this. Still, I have open space in my schedule every Friday called “social hours” where students will come. We’ll eat snacks, play Monopoly Deal or charades, just hang out, and talk and get to know one another.

What classes are you teaching this semester?

This semester, I’m teaching CS181P, Machine Learning, Information Theory, and Search, which aligns well with my research focus because I wanted to teach a class that would give students the tools they need to do the kind of work that I do. The other class that I taught last semester that I’ll be teaching again very shortly is Computability and Logic, which is CS81. I like that class because it allows me to expose students to the idea that computation isn’t just something you can do with silicon and metal, but it’s a very abstract and almost mathematical idea.

We see people walking around campus with these “AMISTAD” shirts. Do you know what that’s about?

AMISTAD is an acronym which stands for Artificial Machine Intelligence = Search Targets Awaiting Discovery. Because my view of machine learning and AI is very search oriented, there’s a play on that because I think AI and machine learning and all that is reducible to search. But also, there are these questions that we don’t know the answers to yet, and they’re waiting for us to actively go and seek the answers to them. Above and beyond that, “amistad” means friendship in Spanish, and so the kind of lab culture that I want to develop is one where the students are very comfortable and it’s a safe place to try very risky things. Ultimately, I want to give the students an opportunity to work on the sorts of things they would work on in grad school, but without all the stress and pressure.

Did your grad school experience inspire you to help others through that process?

My overall experience in grad school was the most difficult thing I’ve ever gone through in my life. I remember thinking “I’m not going to make it to the end.” There’s a scene in the Lord of the Rings movies where Sam and Frodo get to the Black Gate of Mordor. They think, “we’ve gone through this long journey and now we’re at this gate, but there’s no way in.” I felt like that at points in grad school, where the gate was between me and graduation. I felt like there was no way I could ever get there. But I remember, you find a way around and get through it. In grad school, you’re taking some of the smartest people in the world and putting them in one place, and that’s a difficult thing to deal with if you’ve always felt like you were a smart person without really trying, or even if you have to try, but now it gets stepped up—this is a very elite environment to be around. For a lot of students, they let that pressure get to them, and they see it as a competition with other students. I want my students to not have to go through that. Instead, I want them to have the good experience that I also had in doing the work, and hopefully if they do that here in a safe place they build up their confidence to the point where when they get to grad school, it won’t be as challenging for them.

We hear you used to rap! How did you get into music?

I started doing music when I was in high school, and this became a really big hobby for me when I was in undergrad, and after I graduated. I was teaching myself music production, sound engineering. I had a small business that I ran out of my house. I built a recording studio, and I would record and produce for local acts here in the Inland Empire. It was a good side hustle in college. For myself, I produced three albums worth of material, and I stopped actively doing music about the same time when I went back to grad school for the first time. I realized I couldn’t do both really well, and I chose to do the machine learning thing. Now, I have small kids and I spend all my free time with them. When they get older, I’m hoping I’ll be able to go back to it as a hobby. Occasionally, I beatbox with my kids, and sometimes I freestyle with them, although it’s silly since they’re all little.

What’s your favorite food at the Hoch?

Mac n’ cheese bar! They don’t have it that often, so when they do it’s a special thing. The regular thing they have that I like is pho, but the line is kind of crazy long, so unless I get there in time, sometimes I have to miss out.

Any last things you want the Mudd community to know about yourself?

I guess one thing I would like them to know is that if you’re a student here at Mudd, and you haven’t had a chance to take a class with me or get to know me, I’m still more than happy to get to know you. I think that this is one thing that surprises some students. If you see me eating by myself in the Hoch, then you can come sit with me and we can chat!