I'm Kalina, a '27 from Sofia, Bulgaria. I love books (I love reading and writing them), and I particularly love fantasy (i.e., I'm an expert on Middle Earth and Hogwarts studies). I'm fascinated by the human brain and the real-world magic of science. I also love hiking, bird-watching, climbing, and em dashes.
Instead of taking a normal Writing 5 course, I decided to fulfill my first-year writing requirement by taking HUM 1. This course helped me strengthen my relationship to literature and writing. It changed the way in which I thought about classics, both books and movies (we saw Wall-E, by the way). And it also changed the way I thought about academic writing and literary criticism. A third of the course was made up of lectures by professors from different departments, while the other two thirds were discussions with a single professor and a small group of 15 students.
Intro to Neuroscience was the first course I was truly excited about. It wasn't an easy course; we had a weekly quiz of ten to thirteen questions covering the lectures from the past few days, but it was very interesting and also very funny (Professor Winter's humor is legendary). We learned about the human brain at the level of individual cells. We also studied it at the level of different systems, from the olfactory system to the parasympathetic nervous system. And last, we learned about cognition: learning, attention, language. We saw a real human brain with formaldehyde dripping from it. We saw a real sheep's brain. And a rat's brain. And we pocked each other with paper clips to determine the sensitivity of our touch receptors.
Journalism with Professor Alexis Jetter was an enjoyable class, sometimes challenging but very satisfying. We covered a lot of US history through the lens of the media, and we started every class with a discussion of the current news and events (thanks to these discussions, I feel like a real adult now—not so lost when the conversation turns toward politics). Several guest lecturers—from former students of Professor Jetter who're now journalists to a New York Times war correspondent—brought us real stories from the field. In the middle of the term, each of us had to find someone over 30 years old in the Upper Valley, spend a day with them, and write a profile.
SummerSofia, Bulgaria
I'm spending my first summer back home, helping my family care for my newborn sister. In my free time (changing diapers takes a lot of time!), I'm doing research for the cognitive neuroscience lab FINN Lab, preparing for my classes in the fall, and working on a new book.
Computational Neuroscience with Professor Richard Granger is a multidisciplinary course taught by a multidisciplinary professor and designed for multidisciplinary thinkers. The class covered brain anatomy and physiology and the biology of learning; it covered linear algebra and the architectures and characteristics of several neural networks. Last, we had a module on "brain engineering"—how some brain circuits function and how we can get inspired by them as engineers.
The first focus of Discrete Math for Computer Science was learning to think like a mathematician: how do we use logic to find proofs to problems and our solutions? Next, we learned how to apply this thinking in computer science contexts — how do you prove that a recursive program works? How do you prove what its run-time is going to be? These were the kind of skills we were building in preparation for the next course in the theoretical computer science sequence: Algorithms. Before we can build algorithms, we need to know how to think about the steps we need to take to solve problems with the rigor of mathematical logic.
Behind the Scenes of CS 70: Intro to Applied Computer Science
This term, Winter 2025, I took COSC 70 Introduction to Applied Computer Science. The course covers the foundations of linear algebra and some probability and shows students where those topics in mathematics come in really handy in computer science. CS 70 is a prerequisite for many of the applied computer science courses available at Dartmouth (for example: robotics, machine learning, artificial intelligence, computational linguistics). In this blog post, I'll tell you about my favorite part of the course: the programming assignments.
CS 70 had us practice a lot of linear algebra problems, but after each theory assignment, there was a practice assignment–and those were, even if they took a lot of time to complete, my favorite. First, I remember, I had to figure out a way to write a Python program to compute matrix multiplication (you need to do it "by hand," not use Python's built-in functions). This was a fun brain teaser, as I, personally, know how to do multiply matrices–now the question is, how do I explain it, elegantly and concisely, to the computer, so that it can do it, too?
Another exciting practice assignment taught us how to copy and paste one picture into the background of another picture. Imagine a photo of a snowy slope–like this photo below, of me and my close friend Yana. Now imagine a photo of a penguin on the snow. We want to paste the penguin photo onto the photo of me and Yana, to the right. To do so seamlessly, we're going to change the color gradient of the pixels of the penguin photo so that those pixels match the color gradient of the original image's background. This is called Poisson blending.
Me and Yana, plus our guest. Now give the two photos to the program and - voila! - a penguin is standing next to us as we skied in Vitosha, Bulgaria.
The very last programming assignment we had to do for this course was based on robotics–how do we make the "joints" and "bones" of an arm move and go where we want them to go? You'll have to come to Dartmouth and take CS 70 to find out.
Note: I created the penguin-blend picture specifically for this blog post.
I sat down with Aarushi Jain '25, a coxswain on the women's rowing team, to learn more about the opportunities to study abroad as an athlete at Dartmouth!
Once you are here, Dartmouth ensures that you have the tools you need to thrive, regardless of where you start. Read on to discover some of Dartmouth's lesser-known resources!
