Welcome to Sustained Attention
An introduction to this newsletter and what to expect.
Why I’m Starting This Newsletter
I’ve spent the last five years living in two worlds.
In one, I’m a PhD candidate at Stanford, running cognitive neuroscience experiments on human attention and memory – measuring pupil dilation, tracking brain activity, trying to understand why we remember some things and forget others. I’ve published research in journals like Current Directions in Psychological Science and built and shipped a handful of open-source tools used by researchers across the globe.
In the other, I’m a software engineer. I started coding at age 12, shipped iOS apps in middle/high school, and most recently spent 5 months at Slack building ML systems and data pipelines that process millions of data points. I care deeply about writing software that actually works – tested, documented, reproducible.
For a long time, I kept these worlds separate. But I’ve realized they’re not that different. Signal processing is signal processing, whether you’re filtering neural data or cleaning event streams. The principles of good engineering apply everywhere – including (especially) in research.
Sustained Attention is where these threads finally converge.
Why Now?
I’m finishing my PhD. It’s a natural inflection point – a moment to synthesize what I’ve learned and share it more broadly.
I’ve also watched too many researchers struggle with the same problems I struggled with: fragile code, irreproducible analyses, tools that work on one machine and nowhere else. And I’ve seen how much better things can be when you take software seriously.
I want to write the resource I wish I’d had when I started grad school.
What to Expect
This newsletter will cover:
The science of attention and memory – what cognitive neuroscience tells us about focus, distraction, and learning, written for curious non-specialists
Building research tools – API design, reproducibility, and making software that scientists actually want to use
The craft of the PhD – navigating academia, writing production-grade code, and building impactful things that last
Signal processing – the neural kind (EEG, pupillometry) and the data engineering kind (streaming, pipelines)
I’ll publish 3-4 times per month – substantial posts, not filler.
Some posts will be technical deep dives. Others will be opinionated essays. All of them will be grounded in real experience building things and doing science.
If you want to go deeper on the technical side, I will also publish extended engineering deep dives on shawnschwartz.com/blog, dev.to/shawntz, and medium.com/@shawntz.
Why Subscribe?
If you’re a researcher trying to level up your software practices, I’ll share hard-won lessons about reproducibility, testing, and building tools that outlive your PhD.
If you’re an engineer curious about cognitive science, I’ll translate the research into practical insights about how humans actually think and learn.
If you’re a PhD student navigating academia, I’ll write honestly about what works, what doesn’t, and what I wish someone had told me earlier.
Free subscribers get every post. Paid subscriptions may come later, but for now, everything is free. If my open-source work or code has been helpful to you, please consider supporting me through a subscription or donation.
If this sounds useful, please subscribe below.
I’d also appreciate it if you shared this with someone who might be interested – a labmate, a colleague, a friend who complains about research code. After all, word of mouth is how newsletters grow. 😉
Thanks for being here.
– Shawn