Professor Spotlights: Prof. Shannon Ellis

What classes do you teach, and what would you say would be your favorite.

Ah, so I do love all the courses that I get to teach. I teach COGS9: Introduction to Data Science. I teach COGS108: Data Science in Practice, and COGS18: Introduction to Python.

In addition, I also teach a section of DSC 180A and 180B, the Data Science Capstone projects. Hopefully next year be teaching an R based analysis course in the fall. Of those, while I love all of them, my favorite is COGS18. That is because students come in, not across the board but many of them, are a little uncertain in their abilities and sometimes very nervous about the class. Not that I love that they’re scared, but it’s really fun to see those students go from not being so certain to realizing that they can code, and that it maybe wasn’t as scary as they thought, even though sometimes it can still be difficult.

What was the path to getting where you are now and what got you interested in the topic that you’re working in?

I did my undergrad as a Biology undergraduate student and during that I got my first research experience. I really loved doing research and I really loved Genetics, so I was pretty certain at that point that I was going to go to graduate school. I applied to both PhD and MD PhD. I knew I didn’t want to be a physician only, but I thought I would be a good physician and I loved the research, so I applied to both and ended up going for a straight PhD in human genetics. For all of those of you out there, my MCAT scores were not very good so I ultimately got into a handful of PhD programs but only one MD PhD program. And then the school I ended up going to was Johns Hopkins where I went to get my PhD in human genetics. I still really enjoyed research and did lots of research as a graduate student and went on to do a Post-doc. As I was doing my postdoc, I finally admitted to myself how much I loved teaching. And so, I then decided I wanted to go into the teaching route, got some teaching experience, applied to teaching-focused positions and that’s how I ended up at UC San Diego. So, mostly teaching focused now but I still do get to do research, just less so.

Was it through genetics that you got into the data science field?

Again, I’ll try not to be too long winded but as an undergrad, I was working with data and I spent years literally getting these data together and then went to analyze them and there was software that just analyzed it. And I was like, well what happened in there. How did it make decisions? I didn’t understand how this analysis happened. My professor at the time said to me, “If you weren’t graduating this year I would teach you Python.” And I didn’t know what that meant so I went home and googled it, because nobody had ever suggested I learn to code. I never even considered it. I thought it was only for people who wanted to be video game developers, which wasn’t what I wanted. I didn’t write any code prior to graduate school and I went into graduate school with the intention of learning to code. It was there that I was analyzing very large Genetic data sets. And at that point I started using Perl, then R, and then Python to do my research because I was working with lots and lots of data.

Looking back, what would you say what has been the highlight of your career so far?

Oh, that’s a great question. It’s hard to choose, I’ve been really lucky along the way. I’ve had really great mentors and I’ve been lucky that I’ve enjoyed each step of the way. I like school, probably why I became a professor, so I had a really great experience.

You know I think it has to be when I got my job at UC San Diego. I had applied to a lot of different types of jobs. I had myself gone to a small liberal arts college and so initially, that’s where I was thinking I would apply and end up. Nothing against small liberal arts colleges I had a great experience when I was there, but I realized that these students were going to be fine with or without me. It was very small classes, and lots of individual attention and I just felt like it wasn’t the best fit. It probably seems obvious to you all that I should apply to a state school at that point, but it’s like my Pennsylvania, little school mind didn’t think of that. And so, once I saw the job posting at UC San Diego, I looked at that job posting every single day even after I had finally applied, because it just seemed like the job that I really wanted so it was a great fit. I applied and interviewed and then did get that job.

What kind of research do you do and is there a way for undergrads to get involved?

Yes. So, I still do some collaborative more biology-based research, and that isn’t something that there’s really much for undergrads to help out with because what I do there typically involves other labs doing the data collection. They’ve done the experimental design and they’ve got a whole bunch of data and they don’t know what to do with it. So often, that’s when I’ll join them and help them analyze their data, and this is on lots of different topics, but that’s usually me being the add in, and there’s not much for undergrads to do there.

The rest of my work is really trying to understand how to better teach students, how to learn what students actually learn in my classes, and those are the types of projects that I do have undergrads work with me on. I have one student right now who is really, for lack of a better term, kicking butt and he is analyzing all of the former COGS108 (data science in practice) projects to understand what students do, how we could have them improve upon those, how could I improve the teaching. He’s been analyzing literal years of COGS108 projects so that’s one example of what students do across the board and how we should teach better. Those sorts of projects I do work with undergrads on. I have limited capacity, so I usually only work with one to three students every quarter and then a few in the summer. But if students are interested in this, we should chat. Either you know, start by email. Often, it’s by like a quarter or two out. So, if you’re emailing me now for winter, I already am filled, but if you want to chat about next spring or next fall we can usually start chatting and see if your interests align with wanting to do education-based research.

One of the projects that I didn’t mention because it’s in super early stages, is me and a lot of the other professors on campus who teach intro to programming in one capacity or another are getting together to start to try and understand and study. Now of course, we would tell our students that are studying this so we’re not actually studying anybody yet. We’re just thinking and planning, but we want to understand the barriers to coding and how that differs between students who are biology students and students who are computer science students and students who are cognitive science students and how we can best tailor our teaching to the population of students that we have.

What would you say has been the hardest challenge you faced so far?

I get this question a lot and I struggle to answer it. The reason is, I was kind of set up for success along the way so let me explain. I have parents who both graduated from college. My mom has an advanced degree she’s an attorney. It was never in question; I was certainly going to college. I grew up in a not well-off area but as a family that was comfortable, so all along the way I knew my path. We didn’t struggle financially. I wound up with great mentors at college. I had great mentors as a PhD student and as a Post-doc and I am still bugging them all the time. So that’s not to say there weren’t tough times or tough days or things that didn’t work out. I failed constantly but you know, that’s what science is all about. You get much better at it. I was rejected from my dream school as an undergrad, I was rejected for most of my MD PhD programs. When I applied to jobs, I got rejected from lots of those and that’s par for the course, but I wouldn’t say those are struggles beyond what everybody goes through. So, I’m going to kind of punt on this one, I think my students end up going through a lot more than I do and so I try to keep that in mind, knowing just how lucky I was kind of every step of the way.

What would you do differently if you could go back in time?

Oh, I love this question! I don’t think about this a ton in that respect. I do think about how every time I came to a decision point- deciding where to go to college, deciding where to go to graduate school, deciding what postdoc to do, deciding where to apply for jobs- I had a few options. For most of these, I look back and I’m like, okay, what if I had gone to University of Pennsylvania, this prestigious school that would have cost me a lot more money, versus King’s College where I went for free. And it’s okay, I probably still would have gone, and it would have been fine, and it would have been different. So I can’t say I have tons of regrets on any of those decisions, I just think it would have been different. The one thing I do regret is that I did not study abroad as an undergrad and I regret that. It was because I was an athlete, and I was in a Division 3 school playing two sports. So, I would have had to pick one not to play and that was ultimately why I didn’t study abroad but looking back I wish I had.

What is the weirdest thing you’ve witnessed in your field?

Oh, this is a tough one. Let me think. This is like the first one that popped in my head, but it’s something that stuck out. It was during Graduate school and I was in a Human Genetics based Graduate program. We had people doing lots of related work but with different skill sets. Some people were better at pipetting and doing experiments at the bench and some people were more computational writing code. I was the second half of that so often, the people who were more experimental would come to people in my lab and ask us about their code and how they can improve it or how to analyze their data better. One time somebody came in, somebody I respect a ton and to this day he and I are still very good friends. He brought me code with an example and a dataset that he was trying to work out. And this is so trivial, but it sticks out in my mind, hopefully, you’ll see why. He was plotting some data and running some statistical tests, and all of a sudden, I’m looking through his code and I see that the outliers were just thrown out of the code that they visualized, and they left it in for their statistical analysis. I was then thinking back to all of the plots I’ve ever seen from that lab and I realized they never have outliers in them because they’ve been sharing this code, passing it down from one person to the next, and it just by default removes all outliers. They never display outliers, and their argument was that it’s fine we use them in the stats we just don’t show them and I was like, you can’t just not show the outliers, it doesn’t matter that you leave them in when you run the stats. And that ability for code to perpetuate bad decisions, was not necessarily like weird or bizarre but it’s something that has stuck with me that I try to teach especially in my data science classes. You’ve got to get it right early on. You’ve got to document well because if not these things can happen. I don’t know how long this was going on in that lab, but for a while, it seems. It’s not that anybody had mal-intent. One person sat down and was like, “oh yeah we don’t have to display outliers” and then just shared that code in perpetuity. Even when you have good intentions, bad things could happen and I try to convey that to students.

Do you have any advice for undergrads at UCSD or any students in general?

The first is to take actions with intention and don’t compare yourself to others. So, for example, if you in the future want to get into a certain industry, start thinking about what that path would be in the beginning and take steps in direction of that path. Whether that’s applying to a whole bunch of internships and getting one, because you need internships to ultimately be the next step, do that. If you want to go on a research path, try to do some research early on and don’t worry if all your friends are doing something different. Or if you get rejected a whole bunch, try with intention. Know that it’s probably not going to work out exactly the way you planned it, but you’ll learn along the way and you’ll make progress as long as you’re moving with intention while not comparing yourself to others. UCSD is filled with a lot of really smart students. That means you are also one of them, and so are all of your classmates. It can be tough to not compare yourself to others but I’m going to caution you against that. Figure out your path, and then make steps in that direction. So this was for students in general.

The second piece of advice is mainly for students who are maybe first-gen or don’t have a ton of role models who have blazed this path before. The simplest is, you won’t know until you ask. Yes, I get a lot of emails and yes, I get a little frustrated if students are asking the same question over and over again that I feel like I’ve already addressed. But if you don’t ask, you’ll never know. Yes maybe you’ll get an annoyed response every now and then but trust me if you think other people aren’t asking, they are. If you want to get to know a professor better to get a recommendation letter, get to know that Professor better and ask them for the req letter. If you need an extension, ask for it. They might say no, but you’ll definitely not get one if you don’t ask and know that your classmates are asking. And that applies across the board, but I think it’s particularly helpful for students who don’t realize that everybody else is asking. I try to make that clear to students, but I think sometimes I don’t make it as explicit.

Beyond undergraduate, do something that you want to do most days of your life. I try to tell my students that you can learn to code, but if you hate it by the end of the class, don’t try and go down a career path that you need to code. There are other career paths, it’s not the only one. You don’t have to love it, you can learn it, and then you can go in a direction that you actually do love for whatever course it may be.