Amy Harris

What is your major?

 I am majoring in Computational Modeling & Data Analytics, with a Computer Science minor and a Statistics minor. Given the courses I have taken, I can tack on a Mathematics minor as well, but I haven’t officially added that yet.  I probably will not add it because I like to remind myself that the education is more important than all the labels and credentials coming with it.

What kind of art did you study? 

I am an abstract painter. When I graduated from high school, I knew I wanted to pursue art in some way. I wasn’t certain if it would turn into a career, but I loved it and needed to know more. I have had amazing art teachers and professors over the years. My passion for art is so strong because they helped me discover how the whole journey of humanity is engrained within the field. In a way, art has taught me what it is to be human. 

What drew you to Virginia Tech initially to pursue a degree in art?

In 2009, I chose Virginia Tech because I enjoyed my interactions with the School of Visual Arts recruiters and administrators. I also felt really comfortable in Blacksburg and had two older sisters here at the time; it was nice to have family nearby during the college transition.

When did you change your major to CMDA? And what drew you to the CMDA program?

I never actually changed my major. I graduated in 2013 with a Studio Art degree and Art History minor (labels!). Then I returned home to Ashland, Virginia to chase my future as an artist.  I worked in human resources and retail to make ends meet financially as I painted at night and on weekends. I was living at home as well, trying to save what little money I was making.  But after a year and a half, I needed a change.

My parents were really supportive of me returning to school to get another degree. Eventually, I realized that was what I wanted as well.  After some research to figure out how I could enter the math or science field while investigating the type of questions I loved, I found that data science and visualization seemed like a really interesting option.  It was serendipitous that Virginia Tech was just about to officially launch the Computational Modeling and Data Analytics program in January 2015.  I had started looking into schools in October 2014, and I inquired with Virginia Tech if I would need to go through the application process again; thankfully, I did not. So I could immediately enroll for courses in the spring semester.

Do you see connections between Art and CMDA? How has your education in studio art influenced the way in which you approach questions in CMDA – and vice versa?

Data Analytics and Art are very similar, conceptually. That is what drew me to this field in the first place.  With art - the way I approach art - you are trying to discover more about yourself and your world through creation. Data Analytics takes massive amounts of data to try to discover some interesting feature or trend. Both are very fluid investigations since your identity, like the data of the world, is constantly growing and changing. We create mathematical models and artworks that are representative of their time of creation. But both may seem very outdated years from now. 

I feel like art has shaped how I approach CMDA rather than CMDA changing my approach of art.  I came from a very right-brain world of creativity and intuition and entered the left-brain world of true/false and analysis.  It can be a hard adjustment, but as you excel in these technical programs, your right brain can help you find beauty in the equations and algorithms, while not defining your life by them.  CMDA has given me new tools to help the world, but art reminds me what the world is and why it matters.

What about the program has exceeded your expectations?

 I didn’t really know what to expect on the technical side when beginning this program. What I have most enjoyed is the breadth of skills we learn. When I came back to school, I started over with calculus again, as it had been six years since I tackled my last math endeavor: the AP exam. From there, the courses dove into statistics and then coding. Now, all of those skills are being melded together everyday in our work. It’s exciting. But it is very important to have a firm understanding of all of those areas of study to be able to properly find solutions.

Anything surprised you?

I was most surprised by the number of older students in CMDA. I thought I would be the only one. Yet I have met many amazing peers who are older than the typical undergraduate student, either because they returned (like me), or they changed majors a few times to find their passion, or they took time away from school to discover more about themselves.  It’s a good sign that so many people who are not fresh out of high school can be excited about this field.

Can you describe an experience you had in the program that stands out?

On the academic side, my favorite experiences have been feeling the brain make connections.  I love it when a concept clicks and I can relate foundational material to a more complex problem.  It brings me a lot of joy to see other people learn as well. I’ve also met other students who know how to truly communicate with people and have bright futures as professors. It always makes me smile to find those intelligent humans who are fortunate enough to effectively share their knowledge and passion.Socially, my favorite moments have been meeting and interacting with people outside of class. You really get to see the life behind the brain in those scenarios, and that’s where true connections begin for me.

Have you interned anywhere? If so, where did you work? Can you describe your experience?

 I interned with the Washington Post this past summer. It was a great experience, and I had the opportunity to work with an amazing team in the Big Data & Personalization division.  My main project was automating some work done by the editors for book-related articles. Besides the technical aspects of the job, I was grateful to have had the opportunity to meet all of those amazing people – both the employees and the other interns from Virginia Tech and various schools.

Was there a skill (or a prospective/approach to problem solving) you learned in CMDA that you found particularly useful to the work you did in your internship?

My internship was more coding-based than data science.  At the time of my application, I felt I had more computer science skills than real analytics skills, so I leaned towards programming internships. I found out that my manager was known for hiring coders over statisticians as well. So the programming skills enabled me to get that position.

Have you participated in undergraduate research or the CMDA capstone project?

 I have not done any undergraduate research, and that will be a regret of mine when I graduate in the spring. I have my capstone project this semester, and that has been a very positive and challenging experience. My team is working with the accelerometer data from Goodwin Hall. We are trying to find ways to filter building noise from events. It is very different from working with a team on a small project. It has been just as difficult technically as it has been organizationally with planning meetings and collaborating with others. Thankfully, I am part of an exceptional team that works well together.

Can you speak to your experience in CMDA as it has shaped the way in which you approach problem solving?

It is difficult for me to pin down how my brain has learned and changed over the years.  As I have discovered new ways to solve different types of problems, I’ve realized how there are always multiple solutions to a problem, and giving up is certainly the worst solution.  Perhaps my approach to problems has become a little more formulaic.  With any new question, I start by figuring out what I know, what I want to know, and then what I need to bridge the gap. I don’t know if that is something my brain does naturally or if it is due to my CMDA education. It works though!

What are your plans for the near future?

 I definitely want to begin my career in the workforce. A master’s degree is a possibility down the road.  Sometimes I even think I might go back for my MFA (Master’s of Fine Arts) one day. But I also think I’d like to end my career teaching.  I like helping people understand concepts, so I think I would do well instructing foundation courses in programming or analytics or perhaps a visualization route to use art with the technical skills.

Barring any and all obstacles, what impact do you ultimately hope to have on the world?

Whatever happens, I hope I make a positive impact on the world.  I don’t yet know where I will begin my career, but I imagine myself experiencing several jobs over my lifetime, getting a taste of the different ways data is being used. Then, I hope I can pass on what I’ve learned. Sometimes I think about finding a better solution for employing art graduates. My fear is that people will stop studying the arts in attempt to earn these technical degrees. The arts have so much to offer though! When those graduates are entering the job market, they can appreciate history, culture, people, and passions. But the job hunt is painful and hard.  I’d like to find a way to make the employment process easier or help people like me realize other ways to use their skills earlier on in their educational journey.

What has been the highlight of your Hokie career so far?

My Hokie highlight was this past weekend when my entire family went to the VT v. UVA football game. It was my parents’ first game. My dad attended Virginia Tech when my mom and he were married. He was also an older student, and they were starting their family, so football was not the priority. He then sent three daughters here, but was never able to attend a football game.  This year, we finally had the whole family at a game. And it was a great one!

Anything else you would like to add…

Some of my favorite words of advice are: Never be afraid to change your mind.  If you are unhappy with a certain path, try another way. Even if it doesn’t work out, it will be an experience to remember.

 

AMB2 Events
Amy's capstone project involved filtering data captured by the 200+ accelerometers in Goodwin Hall. To validate the filtering methods, her team used clustering, which you can see by the colors in the following plot. Amy: "When I first saw these visualizations, I was reminded of my paintings, many of which have an abstracted grid structure. I often use the linearity of horizontal and vertical marks to maintain compositional balance. I've enjoyed the conceptual parallels between art and data analytics, but it was a fun surprise to see the visual similarity between my two passions as well! "
Harris Presenting