A student writes on a tablet using a stylus, an everyday example of human-computer interaction
Having facilitated a precept discussion in COS 436: Human-Computer Interaction, I was able to reflect on what it means not just to thoroughly read a research paper, but also to guide my peers through a structured discussion based on common threads reflecting their thoughts and insights. COS 436 explores how technology and design shape human behavior and counts towards computer science degree progress as a fulfillment of the breadth category. Engagement with foundational research papers in the field and a semester-long research project are the core components of the course. Each week, students are responsible for writing discussion posts on assigned research papers and take turns facilitating precept discussions.
David Walker is a Professor of Computer Science at Princeton University whose research focuses on programming languages, formal methods, and computer systems. Known for his commitment to advancing both theoretical and practical understanding in the field, Professor Walker also plays a central role in mentoring students.
As someone who completed my junior independent work under Professor Walker’s guidance last semester, I’ve had the chance to witness his thoughtful mentorship firsthand. In a research culture where both the technical challenge and emotional uncertainty can feel overwhelming, I’ve come to appreciate how crucial the human side of research is—how we learn from and grow with those who guide us. With that in mind, I sat down with Professor Walker to explore how he thinks about mentorship: what it looks like, why it matters, and how he helps students, like me, find their footing in the world of research.
A rainbow at the Fountain of Freedom (colloquially called the “SPIA Fountain”), taken during a break from working on my thesis
Independent research at Princeton offers an incredible opportunity for students to explore their academic interests and gain experience in the research world. This year, I’m working on my Senior Thesis with Professor Aleksandra Korolova, conducting an audit of Google ad delivery optimization algorithms. Specifically, I am studying whether aspects of advertisements—the image, text, links, and so on—impact the demographics of the audience to whom the advertisement is delivered.
In the fall, many people were curious about how my thesis was progressing. The truth was, for a few weeks, I hadn’t started running any experiments, since I first needed my research to be approved by the Institutional Review Board (IRB). Through this experience, I both gained insight into the IRB process and found that many students had never even heard of the IRB. In this article, I share my experience and offer advice for students who are planning to conduct independent research.
Glass brain plots from the data analysis of the project I’m working on with my mentor, who spends a couple hours every week going through the fundamentals of coding in neuroscience with me. When I started working with him, I didn’t even know I could make plots like these. Our weekly meetings paid off.
When I first came to Princeton, already interested in neuroscience research, I kept hearing about all the incredible opportunities available to undergraduates. Professors conducting groundbreaking neuroscience studies, cutting-edge labs filled with brilliant minds—it all sounded amazing. But as a first-year student, I had no idea how to actually get involved. Everyone seemed to know what they were doing, while I was stuck wondering: Where do I even start? Will a professor really take time to mentor someone like me? If I cold-email them, will they even read it?
The Majorana 1 Chip.Photo by John Brecher for Microsoft.
In light of recent discussions in the scientific and engineering community, I wanted to take a closer look at Microsoft’s latest announcement in quantum computing. As someone deeply interested in the intersection of research and innovation, I was curious about what this means for the field. Is this truly a turning point in quantum computing, or is there still more work to be done? As part of Now & Next, a new series dedicated to exploring current events, groundbreaking research, and forward-looking trends in engineering, this post delves into Microsoft’s research, the promise of topological qubits, and how the research community is responding. This could be the dawning age for quantum computing, or another step in a long journey. Let’s dive into what’s going on now and what’s coming next with Microsoft’s quantum computing announcement.
Hailing from Saipan and South Korea, Cevina Hwang is a junior in the Ecology & Evolutionary Biology department. With a longstanding interest in the field of dentistry, she chose to expand upon this passion through her junior work, where she will be exploring the evolution of the human jaw and teeth.
Join me below to read about Cevina’s journey in the junior work process.
You’ve finished a research project and now you’re on to the final step: presenting your work! It’s time to share the incredible work you’ve done with the general public, and one of the best ways to do so is to create a poster conveying the significance and conclusions of your research. This will be an essential skill during your time at Princeton whether for a course or as a part of your junior and senior independent work. If this is your first time creating a poster presentation, check this blog out!
Sara Akiba ‘26 with her poster presentation on “Foraminifera-bound δ13C as a Paleo CO2 Proxy: Methods Testing” for the Geosciences Junior Poster Presentations! If you want a poster as great as hers, continue reading below for some advice.
This could be you working passionately on your funding proposal using the tips in this guide! Photo credit: Glenn Carstens-Peters.
After having discovered a potential funding opportunity, you might be reading the requirements for the application and find that you need to write a “research proposal” as a part of the application. This might be your first time writing a funding proposal. Here are a few tips to assist you in writing your funding proposal!
Example heatmap of pedestrian traffic generated by the author to illustrate some of Matplotlib’s capabilities.
Data is everywhere. Whether it’s to track your music listening habits, analyze stock market trends, or understand scientific research, data is most valuable when it can be easily interpreted. This is where data visualization comes in: to transform raw data into clear, engaging visuals.
The Princeton University Library has a wealth of resources and research guides, including guides tailored specifically to data visualization in programming language R and statistical software Stata (often used in economics courses). However, not as many PUL research guides are currently available on data visualization in Python. If you haven’t heard of Python before, it’s a popular programming language that can tackle a versatile range of applications, including data analysis and artificial intelligence. While Stata and R are both excellent choices for statistical analysis and visualization, Python stands out for its flexibility, interactivity, and seamless integration with web development and machine learning applications.
In this article, I wanted to present a commonly-used Python library for data visualization: Matplotlib. By learning how to use Matplotlib, you’ll be able to take your data and turn it into visuals that communicate your findings effectively—a key skill whether you are analyzing survey results, studying statistics, or working on research projects!
Alexis Wu (author), Jenny Pang ‘24, and Jimmy Hoang ‘24 at the COS 484: Natural Language Processing Spring 2024 poster session.
The end of the semester is often accompanied by deadlines for semester-long projects and final papers (including the infamous Dean’s Date deadline, which past correspondent Ryan Champeau has amazing advice on!). For some classes, students may be asked to create an academic or research poster and present their work to their peers in a poster session. A couple of courses I have taken where I produced a final research paper were COS 484: Natural Language Processing and ASA 238: Asian-American Psyches.
In ASA 238, the department provided funding so that all students in the class could have their poster printed through Princeton Print & Mail Services. However, this option typically is not free-of-charge to students. Moreover, since this process typically takes 4-5 business days after the proof is approved to be printed, course instructors may set conservatively early deadlines so that all students’ posters may be printed on time. With more deadlines in other classes, this can create additional stress.
The great news is, this stress can be avoided with a free, straightforward alternative: utilizing the Makerspace’s Large Format Printer. The Princeton University Library (PUL) Makerspace is a creative space on the A-level of the Lewis Science Library open to current students, faculty, and staff. If you’ve never used the space before, it might be daunting, but I hope this article will clarify the process and assuage any fears you may have!
