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<a href="https://jwuphysics.github.io/blog/2025/07/gnns-galaxy-environments/" rel="permalink">Galaxy environments and graph neural networks </a>
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<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
9 minute read
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<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-07-31T00:00:00+00:00">July 31, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>This post discusses how graph neural networks (GNNs) can model the galaxy–halo connection within its large-scale surroundings. Dark matter structures, which seem to account for most of the mass in the Universe, can be represented as nodes in a cosmic graph. But dark matter—which solely interacts via gravitation—is also much easier to simulate than the messy baryons, whose magnetohydrodynamics are computationally expensive. By exploiting the representational power of GNNs, can we predict galaxies’ <em>baryonic</em> properties purely using simple dark matter-only simulations? Yes we can!
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<a href="/tags/#galaxies" class="tag">galaxies</a> ·
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<a href="/tags/#research" class="tag">research</a>
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<a href="https://jwuphysics.github.io/blog/2025/07/clear-vision/" rel="permalink">Clear Vision, Clear Communications </a>
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3 minute read
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<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-07-10T00:00:00+00:00">July 10, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p><a href="https://okbjgm.weebly.com/uploads/3/1/5/0/31506003/11_laws_of_showrunning_nice_version.pdf">The Eleven Laws of Showrunning</a> by <a href="https://en.wikipedia.org/wiki/Javier_Grillo-Marxuach">Javier Grillo-Marxuach</a> is full of useful advice for management and operations. Nominally, it’s about how to deliver a television show, from ideation to writing to production to postproduction, but there’s a ton of guidance that’s surprisingly relevant for working with large language models (LLMs).
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<a href="/tags/#advice" class="tag">advice</a> ·
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<a href="https://jwuphysics.github.io/blog/2025/06/worlds-we-impose/" rel="permalink">Worlds we impose </a>
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<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
3 minute read
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<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-06-18T00:00:00+00:00">June 18, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>In the book <a href="https://en.wikipedia.org/wiki/Impro:_Improvisation_and_the_Theatre"><strong>Impro: Improvisation and the Theatre</strong></a>, Keith Johnstone recounts a moment between a teacher and a special needs student. The teacher holds up a flower and says, “Look at the pretty flower.” The girl responds, “All of the flowers are beautiful.” Then the teacher gently says, “but this flower is especially beautiful.” The girl proceeds to scream and thrash about violently.
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<a href="https://jwuphysics.github.io/blog/2025/06/graph-neural-networks-in-astrophysics/" rel="permalink">Graph neural networks in astrophysics </a>
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<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
15 minute read
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<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-06-09T00:00:00+00:00">June 09, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Many physical phenomena exhibit relational inductive biases and can be represented as mathematical graphs. In recent years, graph neural networks (GNNs) have been successfully used to model and learn from astronomical data. This post provides an introductory review to GNNs for astrophysics.
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<a href="/tags/#galaxies" class="tag">galaxies</a> ·
<a href="/tags/#graphs" class="tag">graphs</a> ·
<a href="/tags/#review" class="tag">review</a> ·
<a href="/tags/#tutorial" class="tag">tutorial</a>
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<a href="https://jwuphysics.github.io/blog/2025/06/blogging-social-media/" rel="permalink">What a month of blog analytics taught me about social media platforms </a>
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6 minute read
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<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-06-02T00:00:00+00:00">June 02, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>If you’re a blogger or researcher sharing your work online, you’ve probably wondered: is social media actually useful for disseminating your writing? I’ve been asking myself this question since <a href="https://jwuphysics.github.io/blog/2025/04/hello-world-again/">returning to blogging</a> just over a month ago.
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<a href="https://jwuphysics.github.io/blog/2025/05/slow-growth-rabbit-holes/" rel="permalink">The benefits of slow growth, misguided rabbit holes, and painful mistakes </a>
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<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
16 minute read
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<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-05-25T00:00:00+00:00">May 25, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>I am a self-confessed <em>productivity junkie</em>. I hate wasting time. And if you scroll through social media, or even my blog posts, you might think that the typical research or learning process is just a happy, monotonic hill climb, capped off with regular announcements of new discoveries or gained expertise. But what if the most important lessons emerge not from unencumbered progress, but rather from seemingly aimless pursuits and the frustration of doing things badly? This post is a tribute to all those times we got stuck and emerged with nothing to show for it, because those “unproductive” moments lead to some of the most important lessons we can ever learn.
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<a href="https://jwuphysics.github.io/blog/2025/05/foundation-models-in-astronomy/" rel="permalink">Foundation Models in Astronomy </a>
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<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
6 minute read
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<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-05-16T00:00:00+00:00">May 16, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Here’s a casual introduction to foundation models and how they might impact astronomy research in the coming years. I’m writing this on the train back from New York to Baltimore, having just wrapped up the <a href="https://events.simonsfoundation.org/event/0aff2690-f1cb-485f-833a-429b6c7eb7ef/summary?tm=8eYg1qvbYoaoB-i3qiSGVDkdnLEYU8RX4tCGRKsTY_w">Foundation Models in Astronomy</a> workshop at the Flatiron Institute Center for Computational Astrophysics. My co-organizers and I are planning to write up a more comprehensive blog post based on our workshop discussions; in the meantime, you’ll just have to settle for this.
</p></p>
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<a href="/tags/#astronomy" class="tag">astronomy</a> ·
<a href="/tags/#computer-vision" class="tag">computer-vision</a> ·
<a href="/tags/#foundation-models" class="tag">foundation-models</a> ·
<a href="/tags/#llms" class="tag">llms</a>
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<a href="https://jwuphysics.github.io/blog/2025/05/some-recent-talks-i-gave/" rel="permalink">Some recent talks I gave </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
less than 1 minute read
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<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-05-12T00:00:00+00:00">May 12, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>If you’re interested in learning more about my current research, then you should check out my recent talks:
- Astronomy Colloquium at the MIT Kavli Institute on April 15, 2025
- Talk and Q&A for the NASA Galaxies Science Interest Group on May 7, 2025
</p></p>
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<a href="/tags/#academia" class="tag">academia</a> ·
<a href="/tags/#galaxies" class="tag">galaxies</a> ·
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<a href="/tags/#research" class="tag">research</a>
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<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2025/05/accelerate-boring-stuff/" rel="permalink">Accelerate the Boring Stuff with AI </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
4 minute read
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<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-05-06T00:00:00+00:00">May 06, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Need to perform a boring, repetitive task? Even if it can’t be fully automated, you may be able to dramatically speed up your task by <em>partially</em> automating it! Simply use a LLM to code up a throwaway app to help accelerate your mindless task.
</p></p>
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<a href="/tags/#llms" class="tag">llms</a> ·
<a href="/tags/#productivity" class="tag">productivity</a>
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<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2025/05/pope-francis-and-galaxies/" rel="permalink">On Pope Francis and galaxies </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
3 minute read
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<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-05-02T00:00:00+00:00">May 02, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Back in 2014, I was privileged to participate in the Vatican Observatory Summer School (VOSS). Over those four weeks, I formed new friends, made new discoveries, and ate awesome food. But the most unforgettable moment of that trip was meeting Pope Francis.
</p></p>
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<a href="/tags/#galaxies" class="tag">galaxies</a> ·
<a href="/tags/#personal" class="tag">personal</a> ·
<a href="/tags/#politics" class="tag">politics</a>
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<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2025/04/constructing-golden-sample/" rel="permalink">Constructing a golden sample for evaluations </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
13 minute read
</p>
<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-04-30T00:00:00+00:00">April 30, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>To truly know how well a machine learning model performs, you need a reliable evaluation set. This post explains a practical way to create such a high-quality dataset, often called a <em>golden sample</em>, and use it to compute unbiased evaluation metrics.
</p></p>
<p class="page__meta tags">
<strong><i class="fas fa-tags" aria-hidden="true"></i> Tags: </strong>
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<a href="/tags/#evaluation" class="tag">evaluation</a> ·
<a href="/tags/#llms" class="tag">llms</a> ·
<a href="/tags/#machine-learning" class="tag">machine-learning</a>
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<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2025/04/four-ways-i-use-llms/" rel="permalink">Four ways I use LLMs </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
10 minute read
</p>
<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-04-28T00:00:00+00:00">April 28, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Large language models (LLMs) haven’t upped my productivity by 10x, but they have dramatically changed the way that I work. In this post I introduce four ways that I use LLMs every day.
</p></p>
<p class="page__meta tags">
<strong><i class="fas fa-tags" aria-hidden="true"></i> Tags: </strong>
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<a href="/tags/#llms" class="tag">llms</a> ·
<a href="/tags/#productivity" class="tag">productivity</a>
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<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2025/04/lowering-the-barrier-for-writing/" rel="permalink">Lowering the barrier to writing more frequently </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
3 minute read
</p>
<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-04-26T00:00:00+00:00">April 26, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Writing these posts is fun but time-consuming. How can I stay motivated enough to post consistently? <strong>To sustain a habit of writing, I’ll need to create an easier path for my future self.</strong>
</p></p>
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<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2025/04/hello-world-again/" rel="permalink">Hello World (again)! </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
7 minute read
</p>
<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2025-04-25T00:00:00+00:00">April 25, 2025</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Oh hey, it’s me again. Yes, I’m going to try to write more blog posts. Yes, I’ve promised that before. Sorry. This time it’ll be different.
</p></p>
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<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2024/01/two-years-in-the-tenure-track/" rel="permalink">Two Years in the Tenure Track </a>
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<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
18 minute read
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<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2024-01-02T00:00:00+00:00">January 02, 2024</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Reflecting on my journey towards becoming a tenure-track astronomer
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<p class="page__meta tags">
<strong><i class="fas fa-tags" aria-hidden="true"></i> Tags: </strong>
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<a href="/tags/#academia" class="tag">academia</a> ·
<a href="/tags/#advice" class="tag">advice</a> ·
<a href="/tags/#personal" class="tag">personal</a> ·
<a href="/tags/#substack-blog" class="tag">substack-blog</a>
</span>
</p>
<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2021/12/galaxy-gans/" rel="permalink">Astronomical Super-resolution, Part II: GANs </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
7 minute read
</p>
<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2021-12-02T00:00:00+00:00">December 02, 2021</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Generative adversarial networks are magical… when they work.
</p></p>
<p class="page__meta tags">
<strong><i class="fas fa-tags" aria-hidden="true"></i> Tags: </strong>
<span itemprop="keywords">
<a href="/tags/#galaxies" class="tag">galaxies</a> ·
<a href="/tags/#tutorial" class="tag">tutorial</a> ·
<a href="/tags/#computer-vision" class="tag">computer-vision</a> ·
<a href="/tags/#substack-blog" class="tag">substack-blog</a>
</span>
</p>
<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2021/01/galaxy-unets/" rel="permalink">Astronomical Super-resolution, Part I: U-Nets </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
8 minute read
</p>
<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2021-01-12T00:00:00+00:00">January 12, 2021</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Training a U-Net to enhance images of galaxies.
</p></p>
<p class="page__meta tags">
<strong><i class="fas fa-tags" aria-hidden="true"></i> Tags: </strong>
<span itemprop="keywords">
<a href="/tags/#galaxies" class="tag">galaxies</a> ·
<a href="/tags/#tutorial" class="tag">tutorial</a> ·
<a href="/tags/#computer-vision" class="tag">computer-vision</a> ·
<a href="/tags/#substack-blog" class="tag">substack-blog</a>
</span>
</p>
<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2020/12/galaxy-autoencoders/" rel="permalink">What do galaxies look like? Learning from variational autoencoders </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
8 minute read
</p>
<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2020-12-30T00:00:00+00:00">December 30, 2020</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Exploring the latent space of galaxy images with autoencoders.
</p></p>
<p class="page__meta tags">
<strong><i class="fas fa-tags" aria-hidden="true"></i> Tags: </strong>
<span itemprop="keywords">
<a href="/tags/#galaxies" class="tag">galaxies</a> ·
<a href="/tags/#tutorial" class="tag">tutorial</a> ·
<a href="/tags/#computer-vision" class="tag">computer-vision</a> ·
<a href="/tags/#substack-blog" class="tag">substack-blog</a>
</span>
</p>
<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2020/08/visualizing-cnn-attributions/" rel="permalink">Visualizing deep learning with galaxies, part 2 </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
19 minute read
</p>
<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2020-08-27T00:00:00+00:00">August 27, 2020</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>In the previous post, we examined the feature space of galaxy morphological features. Now, we will use the Grad-CAM algorithm to visualize the parts of a galaxy image that are most strongly associated with certain classifications. This will allows us to identify exactly which morphological features are correlated with low- and high-metallicity predictions.
</p></p>
<p class="page__meta tags">
<strong><i class="fas fa-tags" aria-hidden="true"></i> Tags: </strong>
<span itemprop="keywords">
<a href="/tags/#galaxies" class="tag">galaxies</a> ·
<a href="/tags/#visualization" class="tag">visualization</a> ·
<a href="/tags/#tutorial" class="tag">tutorial</a> ·
<a href="/tags/#original-blog" class="tag">original-blog</a>
</span>
</p>
<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2020/07/visualizing-cnn-features-pca/" rel="permalink">Visualizing deep learning with galaxies, part 1 </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
11 minute read
</p>
<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2020-07-27T00:00:00+00:00">July 27, 2020</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Let’s explore the morphological feature space of galaxies represented by a trained CNN. We will use PCA to reduce the dimensionality of the neural network’s latent features, and then visualize these features with matplotlib.
</p></p>
<p class="page__meta tags">
<strong><i class="fas fa-tags" aria-hidden="true"></i> Tags: </strong>
<span itemprop="keywords">
<a href="/tags/#galaxies" class="tag">galaxies</a> ·
<a href="/tags/#visualization" class="tag">visualization</a> ·
<a href="/tags/#tutorial" class="tag">tutorial</a> ·
<a href="/tags/#computer-vision" class="tag">computer-vision</a> ·
<a href="/tags/#original-blog" class="tag">original-blog</a>
</span>
</p>
<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2020/06/healthcare-bias" rel="permalink">Identifying racial bias in health data </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
12 minute read
</p>
<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2020-06-11T00:00:00+00:00">June 11, 2020</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>We are becoming more and more reliant on machine learning algorithms in our everyday lives. But what if these algorithms aren’t fair? In this exploratory data analysis of Obermeyer et al. 2019, we look at how racial biases can creep in to an algorithm’s decision-making process.
</p></p>
<p class="page__meta tags">
<strong><i class="fas fa-tags" aria-hidden="true"></i> Tags: </strong>
<span itemprop="keywords">
<a href="/tags/#tutorial" class="tag">tutorial</a> ·
<a href="/tags/#data-science" class="tag">data-science</a> ·
<a href="/tags/#original-blog" class="tag">original-blog</a>
</span>
</p>
<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2020/05/learning-galaxy-metallicity-cnns/" rel="permalink">Training a deep CNN to learn about galaxies in 15 minutes </a>
</h2>
<p class="page__meta"><i class="fa fa-clock" aria-hidden="true"></i>
22 minute read
</p>
<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2020-05-26T00:00:00+00:00">May 26, 2020</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Let’s train a deep neural network from scratch! In this post, I provide a demonstration of how to optimize a model in order to predict galaxy metallicities using images, and I discuss some tricks for speeding up training and obtaining better results.
</p></p>
<p class="page__meta tags">
<strong><i class="fas fa-tags" aria-hidden="true"></i> Tags: </strong>
<span itemprop="keywords">
<a href="/tags/#galaxies" class="tag">galaxies</a> ·
<a href="/tags/#computer-vision" class="tag">computer-vision</a> ·
<a href="/tags/#tutorial" class="tag">tutorial</a> ·
<a href="/tags/#original-blog" class="tag">original-blog</a>
</span>
</p>
<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/blog/2020/05/exploring-galaxies-with-deep-learning/" rel="permalink">Deep learning with galaxy images </a>
</h2>
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7 minute read
</p>
<p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Published:</strong> <time datetime="2020-05-21T00:00:00+00:00">May 21, 2020</time></p>
<p class="archive__item-excerpt" itemprop="description"><p>Welcome! In this first post to my blog, we will take a deeper look at galaxy images. Why should we bother measuring the metallicities, or elemental abundances, of other galaxies? And why would we use convolutional neural networks? Read more to find out!
</p></p>
<p class="page__meta tags">
<strong><i class="fas fa-tags" aria-hidden="true"></i> Tags: </strong>
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<a href="/tags/#galaxies" class="tag">galaxies</a> ·
<a href="/tags/#computer-vision" class="tag">computer-vision</a> ·
<a href="/tags/#original-blog" class="tag">original-blog</a>
</span>
</p>
publications
<h2 class="archive__item-title" itemprop="headline">
<a href="https://jwuphysics.github.io/publication/2024-02-17-paper-title-number-4" rel="permalink">Paper Title Number 4 </a>
</h2>
<p>Published in <i>GitHub Journal of Bugs</i>, 2024 </p>
<p class="archive__item-excerpt" itemprop="description"><p>This paper is about fixing template issue #693.
</p></p>
<p>Recommended citation: Your Name, You. (2024). "Paper Title Number 3." <i>GitHub Journal of Bugs</i>. 1(3).<br /><a href="http://academicpages.github.io/files/paper3.pdf">Download Paper</a></p>