r/compmathneuro

I just wanted to know how did you start studying category theory and from what background did you come to study it and why was it necessary?

I am from CS and learning it for my thesis as it connects a lots of dots in categorical QM and type theory

Dear all,

I am interested to pursue a PhD in neuroscience or in Computational Neuroscience.

I am specifically interested in pursuing a research topic relevant to speech decoding for the aphasia patients.

I would like to mention that I have BSc Comp science with majors in machine learning and about to complete my MSc in Applied mathematics

My thesis is on the classification of the single-molecule FRET traces with interpretable models

I dont have biology background and I need advice where should I start from I have 4+ years of experience as software engineer and have worked on various projects including mathematical simulations of the cancer cells as Random walk problem with markovian process.

Further, I have mathematical understanding of implementing the cryptographic algorithms and also worked on the implementation of the breaking of the asymmetric cryptographic systems.

I am confused should I pursue PhD in neuroscience or in computational neuroscience which will help me pursue the goal I have mentioned.

Also, I would like to mention I have really bad grades in my MSc as I transitioned form CS to Applied math and due to this my GPA is almost 2,7 German grade. Do I have any chance of getting in.

Hi! I am currently a master's student and hoping to apply for comp neuro phd this up coming fall. I was wondering if I could get some advice about what kind of tier of program I should aim for based on my credentials, which are ...

undergrad:

- top bme program with a minor in math

- mid grades (3.3ish)

- D1 student athlete

- 1 year research experience in comp neuro ish with no publications'

masters:

- top comp neuro program with a well regarded advisor

- conference poster and hopefully a workshop or conference paper. its in the area that i want to do my phd in which is neuro ai and computation through dynamics

- 3.8 gpa

my dream program is gatsby neuro at UCL (with Latham probably) but I know it's really competitive, but if anyone can give me advice if it might be in my reach based on my experience I would really appreciate it!! or if you could point me in another direction too that would be great.

Hi everyone,

I'm currently a medical student with a long-term goal of pursuing a PhD in a top lab working on machine learning applications in translational neuroscience , particularly neurological disorders .

Right now, I know the basics of ML. I've completed a few Coursera courses, implemented some personal projects, and have basic Python experience. However, I'm struggling to figure out how to take the next step. I want to build the kind of skills and portfolio that would make me competitive for world-class research labs.

For those of you working in ML/DL for healthcare, computational neuroscience, or related fields, what would you recommend focusing on? Should I prioritize open source contributions, reproducing papers, Kaggle, research internships, reading papers, or something else?

Also, if anyone here works in this space, I'd love to connect, learn from your experience, and see if there might be opportunities to collaborate on research or open source projects.

Thanks in advance!

Essentially I’m really unsure of my path for undergrad. My goal is a PhD in computational neuroscience and hopefully a top program for it. At my local school (not prestigious) I can graduate in 2 years since I got a lot of credits in high school, but it doesn’t necessarily have computational neuroscience research or BCI research. It’s free though for me. I could try to transfer to a top school, but even then it’s not guaranteed and there’s only a limited amount of top schools that give good enough aid for me. My parents really don’t want to spend much. I’m just really worried that if I graduate from my local school I’ll be cooked with no experience in computational neuroscience research so won’t be able to apply for a PhD and it’s not prestigious.

I really don’t care about the prestige of my undergrad if I can find a way to make it to a top PhD program in computational neuroscience. Is it worth the transfer? Is the prestige even worth it? Is there a path that I’m not seeing?

Think to build my own homemade HPC for computer modeling of proteins such as receptors, membrane proteins, Huntingtin. Want to compute interactions of proteins with neurons.

What you think about hardware?

P.s. absolute zero in AI, do i need hardware for it?

I'm currently a 3rd year undergraduate student studying Data Science with interdisciplinary minors in Business and Humanities. I want to pursue a PhD right after I graduate from undergrad, specifically in Computational Neuroscience. I would really appreciate how viable this track would be for me, given my current focus in academia as an undergrad student. My background is largely Data Science, as mentioned, and I'm currently involved in a project pertaining to Digital Humanities. I am actively on the lookout for research projects that relate to Computational Neuroscience. I'm very interested in this sector of research because of how interdisciplinary it is, and I would love to further immerse myself in simulating neural networks and experimenting with the workings of the brain.

My main worry as of now is that my academic background doesn't have a heavy biology emphasis. I've only taken a limited amount of Behavioral Neuroscience courses, and they were rather surface-level. I was thinking of doing another minor in Biology, but that would delay my graduation time.

To those who are already in Computational Neuroscience or are involved in something of an adjacent, I would really appreciate it if you could answer some of my questions:

1. How hefty of a portfolio do you need to have in order to get accepted into a Computational Neuroscience PhD program? What kind of requirements do I need to fulfill?
2. Which schools within California are best suited to pursuing Computational Neuroscience as a PhD? (I'm familiar with UCI's cognitive science program, but I would like to stack more schools on my list to ensure I'm not putting all eggs in one basket))
3. What should I start doing now in order to increase my chances of getting into this PhD track?
4. Would mentorship/additional research projects buff my chances, given that my academic background doesn't have much of a biology focus?

I would appreciate your insight!

Hey y'all,

I'm a med student (in Iraq), just finished my second year. I’m not really into the clinical side of medicine, especially the disease focused part. What really interests me is biology as a system, how living systems are built from basic physical components, how they interact with their environment, and how something like intelligence can emerge from "dumb" atoms following some rules. So because of that I decided to aim toward computational neuroscience.

I started seriously around 7 months ago with Gilbert Strang’s linear algebra textbook. I've finished 5 and a half chapters (now I'm at eigenvalues/vectors). Also finished about a chapter and a half from Boyce & DiPrima’s differential equations book.

During this time I’ve also been filling gaps in calculus beyond what I learned in school. So my next plan for the next 2-3 years is roughly like this:

1. Finish core linear algebra, especially eigenvalues/eigenvectors, diagonalization, symmetric matrices, positive definite matrices, and eventually SVD/PCA.

2. Move deeper into ODEs and dynamical systems: phase spaces, equilibria, stability, numerical solving.

3. Study vector calculus and fields: gradient, divergence, curl, flux, diffusion intuition.

4. Then numerical methods, probability/statistics, stochastic processes, PDEs, and finally neural modeling more directly.

I’m posting here because I want feedback from people who are already in or near this field.
What do u think?
Does this path make sense?
Am I overemphasizing any topic too early?

and when should I start reading actual compneuro papers or books, even if I don’t understand everything yet?
Also, what would be a realistic first project for someone at my current level?

my final goal is to become strong enough to apply for a funded master's program in compneuro somewhere with a serious research environment (definitely not Iraq)

n thanks. I’d really appreciate serious criticism.

I’m approaching 22, graduating college this Sep, and currently working as a Product Owner.

My undergrad is in International Business, which is a plot twist since I came from a STEM background and competed in national-level Physics competitions in high school:)

I worked on a mental health project for about 2 years that I was really passionate about, and it made me care a lot more about things like metacognition, neuroplasticity, behavior change, etc. Based on feedback I’ve gotten from coworkers, friends, and mentors... I’ve realized that a lot of my strengths sit around understanding people, systems, behavior, and ambiguity. That’s why I got interested in product management in the first place. This job got me even think more about questions like: why do users behave this way? what are they really trying to do? how do we understand their decision-making, friction, motivation and mental models?

Recently, I’ve been wondering whether cogsci, computational neuroscience, neuroAI, or something adjacent might be a better long-term direction for me. I’ve watched some UC Berkeley lectures in cogsci to get a feel for the field, and I’ll be joining Neuromatch’s Computational Neuroscience program this July. Before this, I don't have much research experience during college, except for my graduation thesis.

My question is:

1/ How should I approach Neuromatch as a way to test whether this is just an interest or an actual career direction? I don’t just want to finish the course and say something like that was interesting. I want to use it to figure out whether my next step should be staying in industry and continuing to build product experience, or seriously considering grad school / a more academic transition into a field related to cognitive science or neuroscience.

2/ For people who have navigated multiple possible career paths, how did you know an interest was worth pursuing seriously? And how did you measure progress during the messy exploration stage?

3/ Any advice, personal experience, frameworks, warnings, or even questions I should be asking myself would be really appreciated.

I am currently pursuing Btech in biotechnology and want to further pursue neuroinformatics or computational neuroscience. Where should I apply, which university, I am also thinking about masters phd integrated programme. Can anybody suggest something to me. I am actually very scared I just read about the mental stress and abuse in academia. Is it even worth it ?

Sorry if this is a common question around here but with how the AI industry is advancing I’m wondering a few things about comp. neuroscience career prospects. To preface I’m 23, I haven’t done any formal education yet for reasons I won’t get into here but I’ve always been passionate about subjects revolving around mathematics, astrophysics, engineering, programming, neuroscience & it’s adjacent fields.

When I was a child I was shown a complicated neurosurgical process on YouTube by my aunt in the early 2000s, in all honesty it was probably meant to freak me out but it did quite the opposite and I’ve been intrigued by neuroscience & things like the philosophy of mind ever since.

For along time it was mostly background interest and some self study on certain topics but as I’ve gotten older and I’ve started to try & define a career path for myself I feel like pursuing something related to computational neuroscience and mind machine interfacing is where my life trajectory is headed.

I‘d even like to start a foundation or company someday revolving around that (which is lofty for someone who at 23, hasn’t even begun the formal education process yet).

My main question is, is it too late for me to jump into the formal education process and eventually meaningfully contribute to the field? It feels kind of daunting, especially because some of my more well positioned peers will have already graduated with their bachelors and be well ahead of me career wise.

My goal is to pursue a career involving comp. neuroscience & mind-machine interfacing both on the theoretical & engineering side of things with some mix of bioethics.

thanks in advance for advice about this dilemma.

I recently got accepted into a neuroscience PhD. The project itself is very ML-heavy and my background is math and CS. The research direction feels pretty well-aligned with the dream goal of landing at top industry labs (DeepMind, Anthropic, etc.)
(I also really like the project!)

However, the university is ranked below 500. And my supervisor has a strong name but more in cognitive neuroscience, no connection to AI.

I did a LinkedIn deep-dive on researchers at these labs and it's almost exclusively MIT, Stanford, UCL, etc., which is pretty discouraging.

I am now considering declining and reapplying to somewhere like UCL instead. Would really appreciate any honest input. Thanks.

Hi everyone,

We just open-sourced NeuraDock Visual Cognitive Load Agent, a local-first EEG agent that turns EEG data into a real-time cognitive-load API for AI agents, BCI prototypes, HCI/XR systems, and adaptive interfaces.

The idea is simple:

Instead of treating EEG as just offline signal analysis, we want to make it usable as a local API:

EEG file / synthetic replay / NeuraDock hardware
        ↓
preprocessing + signal quality gating
        ↓
alpha dynamics + visual cognitive-load estimation
        ↓
local dashboard + API endpoint
        ↓
AI agents / XR / HCI / neurofeedback apps

A few things we wanted to make clear:

• No hardware required to start: you can run the agent with synthetic replay or example EEG data.

​

git clone https://github.com/Neuradock/eeg-workstation-agent.git
cd eeg-workstation-agent
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
neuradock-agent serve --port 8765
# open http://127.0.0.1:8765

• Works with hardware too: if you have NeuraDock EEG hardware, it can run as a real-time closed-loop cognitive-load monitor.
• Full toolchain is open-source: data loading, preprocessing, quality control, cognitive-load analysis, dashboard, and API.
• Local-first design: the core signal processing runs locally; the LLM layer is optional and receives summarized outputs rather than raw dense EEG streams.
• Developer-oriented: the goal is to make EEG usable by AI developers, BCI builders, HCI/XR researchers, and open-source hardware communities.

We also wrote a short paper/tutorial explaining the architecture and design choices.

GitHub:
https://github.com/Neuradock/eeg-workstation-agent

Article / tutorial:
https://arxiv.org/html/2606.26518v1

Short demo video:
https://www.youtube.com/shorts/9MWe_rCnWNY

.exe applications:

https://github.com/Neuradock/eeg-workstation-agent/releases/tag/Neuradock_Cognitive_Load_Agent

I’d love feedback from people working on EEG, BCI, neurotech, AI agents, XR/HCI, or adaptive interfaces.

A few questions we’re thinking about:

1. What would be the most useful “killer app” for a real-time cognitive-load API?
2. Would you use this more as a research tool, a developer API, or a hardware demo platform?
3. What integrations would make this more useful: OpenClaw, Claude Code/Codex workflows, Unity, Unreal, browser extension, VS Code, or something else?

Happy to hear criticism too. We’re trying to make EEG more accessible and useful for developers, not just for offline neuroscience analysis.