CSpotlight: Mapping the Past

Why did you choose to pursue a degree in computer science, specifically at the University of Minnesota?

I was interested in the research I did in my undergrad, but there isn’t a large research community in Moscow. So I started researching labs, and here I am.

I chose the University of Minnesota because of my advisor, Associate Professor Yao-Yi Chiang. I really like what he’s doing and the directions our lab, the Knowledge Computing Lab, is going. We work with all kinds of spatial and temporal data, and process it in various ways.

How did you become interested in computer science? What are your specific interests within the field?

I have Type 1 diabetes, and when I was younger, my dad came up with the idea of making some kind of device to help me manage it. My father was an engineer, so he was in charge of building it, and I was the programming person. We made a small device to control my insulin pump remotely, so my parents could control it. I thought the experience was quite interesting and was surprised by how you can build something with your own hands.

In undergrad, I started as a math major, but I became more interested in how I could apply math to real-world problems. I shifted into the programming and coding world. I wanted to see the results of my work, which made me interested in geography and GIS systems.

What do you hope to contribute to the computer science community at the University?

My major goal is to strengthen the bond between the computer science department and the geography department. The computer science department is very strong, and there are a lot of great professors who are really dedicated to their research. The same goes for the geography department. I want to promote more interaction between the departments.

Tell us more about your research.

I work with historical maps that are from open data sets. My goal is to extract the road networks for the periods of time we have covered. There are thousands of maps, which are all different styles, scales, and from different sources—and I’m creating a computer-vision approach to process them and extract the underlying road network. This will allow us to know where the roads were and how they changed, which will help us to understand social fluctuations among different regions. Our data set originated around 150 years ago—so it's pretty old. Because of this, we can see the whole timeline of road network changes.

What advice do you have for incoming computer science students?

My obvious advice is not to be afraid of asking questions or talking to your peers. My maybe-not-so-obvious advice is not to be afraid of reading hard research papers because that is where the research originated. Reading is a very important skill, more important than many people may think. Being able to process that level of information is extremely important.

For undergraduates who would like to apply for grad school, I recommend talking not just to potential advisors, but potential lab mates as well. It’s important to understand how your possible future colleagues see their workflow and what is going on in the lab.

What are your plans after graduation?

I know I will stay in research—either it will be industry research or academic research. If I do go into industry, I want to be in the research and development department of companies.