New Faculty Spotlight: Lin Yan

March 5, 2024
News

Meet Lin Yan, our new Assistant Professor of Computer Science. She started in February of 2024.  She received her BS and MS from Shanghai Jiao Tong University in 2010 and 2013, respectively. She received her Ph.D. in computing from the University of Utah in 2022, under the supervision of Prof. Bei Wang Phillips. She was a postdoctoral fellow at the Environmental Science & Mathematics and Computer Science Division at Argonne National Laboratory from 2022-2023. 

Her research interests include topological data analysis and visualization. Her recent work focuses on problems involving large and complex forms of data by combining topological and statistical data analysis, machine learning, and visualization techniques.

"I am impressed by the computing resources, friendly faculty, and promising prospect to work in ISU. However, I think the most exciting part of being an assistant professor is to be an advisor of Ph.D. students. I have many scientific ideas that I cannot try by myself. I would like to work with students, which increases the productivity in research as well as teaching."

What drew you to the Department of Computer Science at Iowa State?

The Department of Computer Science at Iowa State looked for a researcher in visualization, which is a great opportunity for me since I didn't see many universities emphasizing the need for visualization researchers. The Department of Computer Science at Iowa State has a large amount of resources for both students and faculty members, which is a also great collaborative opportunity for me.

What are you most excited about?

I am impressed by the computing resources, friendly faculty, and promising prospect to work in ISU. However, I think the most exciting part of being an assistant professor is to be an advisor of Ph.D. students. I have many scientific ideas that I cannot try by myself. I would like to work with students, which increases the productivity in research as well as teaching.

What attracted you to working in your area of research?

I did signal processing during my M.S. and found data science attractive. After becoming a Ph.D. student, I found data analysis with both machine learning and visualization techniques to be even more attractive.

Please tell us about your research. What are some key questions you aim to address?

I tackle problems involving large and complex forms of data that require rich structural descriptions. My first question to motivate my research is “How to get scientific insight, such as key features, from large-scale data?”. My second question is “How to make data transfer faster for visualization?”. And the third one could be “How to understand the sensitivities and uncertainties of scientific simulations?”.

What do you see as some possible applications of your research?

I have used my techniques in cyclone tracking, ocean eddy detection, and cosmic void finding. I want to improve TROPHY, a tropical cyclone tracking framework, which has seen promising results compared with other state-of-the-art cyclone tracking frameworks.

Outside of your role as a computer scientist, what is one activity that you enjoy doing?

Cooking.

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