CS Senior Spotlight: Julian Baldwin

For Julian Baldwin, who graduates this month with a combined BS/MS degree in computer science, his Northwestern Engineering experience reinforced why he chose the field. Computer science, he said, perfectly blends his passion for math with his desire to create, build, and approach projects with a design eye.

A member of the Northwestern Security and AI Lab (NSAIL), Baldwin applies that enthusiasm to machine learning research. He has contributed to papers studying game-playing artificial intelligence and building more interpretable strategic planning systems, and is currently working on improving deepfake detection.

Baldwin also served as a peer-study group leader for the Engineering Analysis sequence of the McCormick School of Engineering core curriculum for first-year students. In addition, he is a former president of Effective Altruism Northwestern, a student group that leads fellowships and discussions focused on maximizing positive impact.

We asked Baldwin, who was recently named among 12 ‘outstanding CS seniors’ for academic excellence and contributions to Northwestern CS, about his experiences at Northwestern Engineering, opportunities for impactful collaborations, and his advice for current students.

Why did you decide to pursue the combined BS/MS degree in computer science at McCormick?

I became interested in computer science in my last two years of high school. It combined much of what I enjoy about math — the clear logical systems and satisfaction of understanding and solving complex problems — with my desire to be able to build and create.

Computer science is underrated for the opportunity it gives to be creative, and you can iterate more quickly than almost any other discipline. I was particularly excited to study CS in an engineering environment at McCormick because I felt it would give me a chance to develop design thinking and work on interesting projects.

How did the McCormick curriculum help build a balanced, whole-brain ecosystem around your studies?

The core general engineering courses gave a solid foundation. The Design Thinking and Communication series was particularly useful because it provided experience working on longer-term projects than typical coursework and a view into interacting with real stakeholders.

I’ve also appreciated being able to branch out into neighboring fields, such as statistics or linguistics, and see how CS topics are approached from different perspectives. For example, I really enjoyed learning about natural language processing techniques both through machine learning courses and computational linguistics courses or studying probability through industrial engineering as well as algorithms courses.

What are some examples of collaborative or interdisciplinary experiences at Northwestern that were impactful to your education and research?

One standout experience was a special section of COMP_SCI 338: Practicum in Intelligent Information Systems that collaborated with the Knight Lab in the Medill School of Journalism. This was a project course in which each team was made up of a mix of CS and journalism students and each team built unique prototypes or tools at the intersection of AI and journalism. It was a great experience working on a more domain-specific project and benefitting from the perspectives of journalism majors.

What skills or knowledge did you learn in the undergraduate program that you think will stay with you for a lifetime?

I’m grateful for the research skills I’ve built. Obviously, courses are excellent for developing technical skills, but beyond that I feel that being able to work on many different teams has also massively improved my ability to communicate, present my ideas, and see projects to completion. I’ve gotten a lot of value from interacting with people from different backgrounds and areas of study.

What's next? What are your short- and long-term plans/goals in terms of graduate studies and/or your career path?

I’m preparing to apply to PhD programs focusing on machine learning research. My long-term hope is to contribute to the advancement of AI while ensuring systems are built and deployed safely through better interpretability and evaluation.

What advice do you have for current Northwestern CS students?

Research is much more accessible than most students think. I’ve learned so much through working in the NSAIL lab and being advised by Professor V.S. Subrahmanian in parallel to my classes — I wish I had tried to get involved earlier. In my experience, most professors are approachable and willing to support students.

In a similar vein, I found the most value in taking project classes and trying to dive beyond just the class material. The best learning experiences can happen when you engage with something very deeply, so take advantage of these opportunities.