Snow-capped mountains

Kalina Duncheva

Class of 2027
a headshot picture of Kalina in a blue top
Bio 

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.

Academic Program 

Neuroscience and Computer Science

Favorite Thing Right Now 

My baby sister

Hometown 

Sofia, Bulgaria

Pronouns 

she/her

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Kalina's D-Plan

What's a D-Plan?

    • FallHanover, NH

      Favorite Class: HUM 1: Dialogues with the Classics

      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.

    • WinterHanover, NH

      Favorite Class: PSYC 6: Introduction to Neuroscience

      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.

    • SpringHanover, NH

      Favorite Class: ENGL 6: Journalism

      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.

    • FallHanover, NH

      Favorite Class: PSYC 40: Introduction to Computational Neuroscience

      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.

    • WinterHanover, NH

      Favorite Class: COSC 30: Discrete Math for Computer Science

      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.

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