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!
A student working in a lab, potentially on a research project for their senior work that would greatly benefit from funding! Photo credit: Nick Donnoli.
You’ve brainstormed a great idea for your research project. You have the details of your topic all figured out, but you need some assistance with figuring out the logistics of the financial aspects that come with your great idea.
If that’s you, here’s a quick guide on one way of securing funding as a Princeton student!
The Princeton Index of Medieval Art used to be a physical register, much like this one.
Many academic disciplines engage with visual art, whether from the standpoint of art history, material culture, or even paleography. The Princeton Index of Medieval Art is a unique database well-suited to the needs of researchers across various fields. Whether history, comparative literature, art, or classics, the index gathers a vast amount of information on Late Antique and Medieval Artworks, neatly sorted in an accessible way.
What is research? Perhaps we can ask the Internet…
If you’re anything like me, you first thought that “research” essentially amounted to surfing the Internet. Back in the glory days of middle school, “research” meant the rewarded privilege of getting to use the laptop carts, productively using class time on googling information about our various project topics (and definitely not secretly playing games). Now, as the mature, worldly college student you now are, perhaps you think you know better. “True” academic research, the clever reader now knowingly tells themselves, is historians dusting through archival documents and scientists mixing frothy chemicals in the lab.
Yet there’s a missing part here: a crucial element that takes us back to our elementary and middle days of excited googling. To make any significant intellectual contribution to any field, one first has to understand the current state of knowledge in that same field. To borrow the term favored by the Writing Program, we need to understand the scholarly conversation. How do we know if we’re making a contribution to something, if we don’t understand what that something is? Understanding the current state of research in a given field is a crucially important skill—really, a prerequisite—for conducting your own effective research in that field.
Jake Snell is a DataX postdoctoral researcher in the Department of Computer Science at Princeton University, where he develops novel deep learning algorithms by drawing insights from probabilistic models. He is currently serving as a lecturer for SML 310: Research Projects in Data Science.
As I dive deeper into my computer science coursework, I’ve found myself engaging increasingly with statistics and machine learning (hereafter abbreviated as SML). Opportunities to conduct SML research are abound at Princeton: senior theses, junior independent work, research-based courses such as SML 310: Research Projects in Data Science, joining research labs, and much more. There is such a wide variety of research opportunities, and so many nuanced pathways that students can take while exploring SML research. So, for this seasonal series, I wanted to speak with professors and researchers who are more advanced in their research journeys to share their insight and advice to undergraduate students.
Group Photo of the AST251 students with Precision Assembly Specialist John Teifert all geared up in the cleanroom!
The structure of a “standard” Princeton course usually includes a mix of lectures, precepts, or seminars which likely have a midterm and final. While some of these courses may have “lab” components where you spend a couple hours once a week doing a hands-on assignment, there exist many courses at Princeton which are instead entirely focused on conducting hands-on, lab-based research with a small team that works closely with professors who provide mentorship as you work on an original research project. If you’ve ever wanted to take a class that is far different from anything else at Princeton by teaching you hands-on skills and giving the opportunity for a new project, these types of courses might be for you!
Some of these courses are year-long sequences like AST250 Space Physics Lab I and AST251 Space Physics Lab II, which I took during the 2022-2023 academic year. This was one of my favorite course experiences at Princeton and was certainly the most engaging. The skills we learned were invaluable, and as we worked closely with the professors and each other, our year-long project became an unforgettable experience.
Claire F. Gmachl stands at the forefront of groundbreaking research in mid-infrared photonics as the Eugene Higgins Professor of Electrical Engineering at Princeton University and the Head of Whitman College. She also serves as the Associate Chair of the Department of Electrical and Computer Engineering. With her expertise in semiconductor devices and photonics, Professor Gmachl delves into the realms of quantum-cascade lasers and beyond.
As a student surrounded by peers working on their junior papers or senior theses, as well as constantly hearing about groundbreaking faculty research, I came to seek a way to better engage with the research around me, and to synthesize current research and processes to bring insights to others. I decided to create a series of research insights, interviewing faculty and students, to learn more about their research topics, their personal research process and interests, as well as the potential implications from their findings.
In this article, I’m excited to have had the opportunity to interview Professor Claire Gmachl, who has also previously taught me inEGR 151: Foundations of Engineering: Mechanics, Energy, and Waves, the first physics course in the Engineering Sequence. In our interview, Professor Gmachl graciously shared insights into her research journey, shedding light on the multifaceted landscape of mid-infrared photonics and semiconductor devices.
