CSpotlight: Implementing CS and AI to Human Interactions
Why did you choose to pursue a degree in computer science specifically at the University of Minnesota?
The main reason I came to the University of Minnesota is because of the active Human Computer Interactive (HCI) research community. Also, there is a lab called GroupLens focusing on social computing. Being around this multi-disciplinary HCI research community would foster my expertise in HCI research greatly. I also wanted to live and study abroad for several years in the United States to expand my horizons and meet people from different cultural backgrounds.
How did you become interested in computer science? What are your specific interests within the field?
I was inspired to pursue computer science around six years ago when I learned about AlphaGo, a deep-learning computer program that plays a board game. This came out before all the existing popular AI tools such as ChatGPT. AlphaGo is proficient at the board game and can compete with professional human players. I had a sense that artificial intelligence is a promising technology, so I became more curious about it. That is when I started to learn about computer science. After three years of studying computer science and artificial intelligence, I realized that compared to computer algorithms and computation itself, I am more interested in how humans will use, interact with, and behave through this advanced high-level technology, so I shifted towards the human side and focused more on human-computer interaction. Now I am doing human computer interaction research.
What do you hope to contribute to the computer science community at the University?
I can contribute more by connecting people together and becoming more multidisciplinary by including multicultural perspectives in the computer science community here at the University.
Have you been involved with any research on campus?
My research is about how different visualizations would impact people’s perception of the indoor environment and thus their decision-making with AI giving suggestions. To be more concrete, we studied how different building-scale indoor environment visualizations would impact people’s spatial decision-making. We compared augmented reality see-through visualizations and 2D maps and evaluated if humans can utilize AI suggestions appropriately in these visualizations. Lastly, we detected and extracted further design implications for indoor tasks.
What advice do you have for incoming computer science students?
Be brave to try different topics, reach out to different professors and students proactively, and be multidisciplinary without limiting yourself to one major.
What are your plans after graduation?
I am open to both academia, such as becoming a professor, and to industry, such as research scientists. I do not fully have a preference yet.
Are there any additional experiences you did that you would like to highlight in the article?
I am open with all kinds of people, from different disciplines, interests, or research areas. I love to listen to what they think and how they live in their lives.