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Shahan Ali Memon is a Ph.D student at the iSchool.

When you meet someone who doesn’t know about your research, how do you describe it?

I study how society, politics, and technology shape the way science works. This mostly involves exploring and merging large-scale datasets to understand how scientists collaborate, how social factors such as reputational damage or geopolitical tensions affect these collaborations, and what makes for success or failure in science. More recently, I’ve started studying how AI is changing science, whether it can help mediate scientific discoveries, and whether AI agents can autonomously work together to do scientific research—and perhaps replace me as a PhD student :)

Who is the faculty member working closest with you? What are you learning from them?

I work most closely with Jevin West. He has been instrumental in teaching me the value of public scholarship—the importance of making my research and writing accessible, and relevant to a wider audience. I’ve also learned a great deal from his interpersonal approach. If you have ever interacted with him, you will realize that Jevin has a remarkable energy and positivity, and a rare ability to frame situations constructively. This perspective is something I deeply admire and actively strive to incorporate into my own work and interactions.

Why are you interested in this subject?

Science is fundamental to how we know what we know about the world. But it doesn’t happen in a vacuum—it’s a highly social process. For me, it’s interesting to tease out the social factors influencing science, in order to help improve it. 

What impact do you hope to make in the information field through your research/dissertation?

I aim to humanize our understanding of science, moving past the myth of purely objective “ivory towers.” Science is a human endeavour—carried out by people, not by robots in a bubble. By studying its socio‑technical dynamics, my research hopes to uncover concrete process strengths and flaws. For information science, this means contributing to more reliable knowledge production, formulating better science policies, and a transparent picture of how scientific information and knowledge comes to be.

What surprised you the most when digging into your research?

It is often the nuance hidden beneath the surface. We often lean on means, models, and simplified stories to make sense of data—but underneath, reality is often tangled. The true complexity of any research question always escapes our neat, one‑size‑fits‑all narratives. That’s where information science with its interdisciplinarity shines: by mixing various qualitative, quantitative, and design methods, we get to study things from different angles.

What are your career goals once you graduate?

I love research and teaching, and would love to continue in an academic setting. However, I’m also quite open to roles in research-focused industry positions where I can use information and data science to ask and answer important questions and make a tangible impact.