Spring 2026 Quarter Class Review

Summary: Overloaded with classes, research, and my general exam

Note: I’ve not taken any substantive classes since Spring 2025, so I’ve been skipping on this.

The Reviews

• A+ : ☆☆ CSE 528: Computational Neuroscience (Probably got an A+ - famous last words) Some research credits, seminar classes, and masters thesis credits that shouldn’t really factor in.

Other Commitments:

Prepping for my general exam. I’ll probably write another blog post at some point about my reading process and my Obsidian template, but for now know that I was extremely busy.

Retrospective

Classes

It’s funny that during my last blog post, Spring 2025, I mentioned that I was done with classes and that I hoped by the next quarter I’d be done with classes… That was a lie, because life gets in the way.

CSE 528: The reason why I took another class after swearing off them was that this class was taught by the esteemed Adrienne Fairhall and Rajesh Rao; I’ve wanted to take this class since I first joined back in 2023. It was easily a 10/10 class in terms of material, but I do have some overall comments (obviously). The class pacing was fantastic and was an excellent peek into how computational neuroscientists think about problems. However, I wish that it improved on two things: (1) even though I was in class for most of the lectures, when I reviewed the notes I felt like I was completely lost; the notes are not made for self-study and I had to refer to the textbook, Theoretical Neuroscience: Computational And Mathematical Modeling of Neural Systems, constantly; (2) the homeworks felt… messy? The prompts were long with lots of, IMO, small deliverables spread throughout. A convention that they followed was the tasks they wanted you to do would be in the last paragraph, but earlier paragraphs in the prompt would also ask you to plot things. I ended up having to make checklists to ensure I caught everything.

*It’s hilarious that I see Neuronal Dynamics From single neurons to networks and models of cognition said to be more mathematically challenging because I found that significantly more approachable - but maybe that’s because it was presented in more digestible chunks.

Grad Student Life

Every quarter I say that it was the hardest one for me, but this one was truly the hardest. The computational neuroscience class ate up a chunk of my time (time well spent, mind you) and I had to prep for my general exam. If I had to do it again, I’d definitely have taken my notes differently, and instead of starting with the harder, more dense texts, I would have interspersed them with the more approachable texts. One of my readings was Simple memory: a theory for archicortex, which was honestly a slog until something seemed to click; I realized that I didn’t need to understand everything; I needed a gestalt understanding. Once this concept clicked, the rest of my readings flew by - I’m taking the approach of “I don’t need to remember everything; I just need to know more-or-less where to look and what the common links between the papers are.”

This quarter I was given the opportunity to be the keynote speaker at the Shenoy Undergraduate Research Fellowship in Neuroscience (SURFiN) symposium, which was an absolute blast. I loved sharing my journey from academia to industry and back. From what I’ve heard, the talk was also extremely well received, which was a relief 😎

Misc.

Going back to CSE 528: Last quarter I began working on compartment-rs, which got me more interested in the biomechanics and deep neuroscience concepts underpinning the work; I had approached everything as an abstract graph or machine learning problem up to now - I couldn’t even describe action potential transmission in a neuron… Good thing I started working on that project and this class when I did, or I’d be boned for my generals.