Steven was born and raised in Harbin, China, and moved to Toronto in 2019 at the age of 16 to attend high school. After four years, he began his undergraduate studies at the University of Toronto in 2023. He is now entering his third year, pursuing a double major in Computer Science and Statistics. He enjoys reading theoretical works and solving puzzles in his academic life, while outside of school he likes playing video games and exploring music.
What made you decide to participate in SURP?
As a student majoring in Statistics, I have developed a strong interest in working with data and exploring the theoretical foundations behind statistical methods. The research conducted in Astrophysics aligns closely with these interests, as it often involves analyzing complex datasets and applying advanced statistical techniques to uncover meaningful patterns. During my first year, I had the opportunity to attend several astronomy lectures with friends, which sparked my interested in the field of astronomy and astrophysics. Participating in SURP offers me the chance to gain hands-on research experience, and further develop the skills I hope to carry forward in my academic and in my preparation for a master to PhD degree.
What is your favourite thing about SURP?
My favourite part of SURP was the opportunity to actively contribute to addressing a research question that has challenged astrophysicists for quite some time. Under the guidance of my supervisor, I worked on transforming complex datasets into meaningful visualizations. This process not only allowed me to apply my statistical and computational skills but also gave me the chance to think critically about how each plot or graph could provide new insights into our work. I especially enjoyed our discussions during meetings, where we evaluated different visualizations and considered their potential significance in shaping our understanding of the problem. What I found most rewarding was the exploratory nature of the research — testing out different approaches, analyzing results, and iterating on ideas to gradually get closer to an answer. I also learned a great deal about astrophysics throughout these discussions and discoveries. I began the program with no background in the field, but over time I developed a solid understanding of my specific research work and its broader context. This growth from a complete beginner to someone who could meaningfully engage with astrophysics was both exciting and rewarding.
Can you tell us about your research project?
Our project focuses on probing local magnetic fields around radio galaxies through the study of an astrophysical phenomenon called Faraday Rotation. This effect measures how much polarized radio waves rotate as they travel through magnetized plasmas, and the degree of rotation is directly related to the strength of the magnetic fields encountered along their path.
One major challenge we faced is that the observed rotation measure is a cumulative effect from multiple sources along our line of sight. Several intervening media, including our own Milky Way, can contribute to the measurement and make it difficult to isolate the influence of the radio galaxy’s local environment.
To address this, we initially tested for correlations between the rotation measure of a radio source and its intrinsic properties, such as its total intensity — essentially, how “bright” the source appears. Since intervening media are physically distant from the source, they do not affect intrinsic properties like intensity. Interestingly, we found that many sources with high rotation measures showed correlations between intensity and rotation measure.
Building on this, we systematically ruled out contributions from other potential foreground effects at different frequencies, such as H II regions (ionized hydrogen), Hα emission, and microwave background. Our results suggest that the high rotation measures we observed are likely caused by something local to the source itself. Going forward, we aim to gather more compelling evidence to support the conclusion that these are indeed source-local measurements of magnetic fields.
Can you explain how SURP has been different from your undergrad work?
Most of my undergraduate coursework has been guided closely by professors. Typically, we are given structured questions with clear guidelines, and by carefully answering smaller parts, we gradually build toward solving a larger, more significant problem. In contrast, SURP began with a very broad research question, requiring me to explore different paths, propose potential solutions, and actively discuss ideas with my supervisor. This greater degree of freedom introduced new challenges, but it also encouraged creativity and allowed me to learn far more throughout the process.
What are your plans for the future?
I would love to continue deepening my knowledge in data science, particularly in the area of machine learning. I am excited by the potential of these methods to uncover patterns in complex datasets and to solve problems across a wide range of disciplines. Through my studies and research, I hope to build a strong foundation in both the theoretical and practical aspects of machine learning, and I am eager to carry these skills forward into my future career. My goal is to apply my specialties not only to advance research but also to contribute to innovative, data-driven solutions in real-world settings.
Tell us something fun about yourself unrelated to SURP!
- I used to play drums a lot and I once played on provincial TV in China.
- In my free time, I read a lot of papers related to new data science techniques and machine learning models.
The Dunlap Institute for Astronomy and Astrophysics at the University of Toronto is an endowed research institute with over 80 faculty, postdocs, students, and staff, dedicated to innovative technology, ground-breaking research, world-class training, and public engagement.
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