Group
Students, and what they built
I advise SDSU Astronomy undergraduate and Master's students, building differentiable models of stars and star clusters. Below: who is in the group, what they worked on, and where they went next.
The group
Graduate students
- Aisling AcunaBridging STARFORGE and SKIRT: A Synthetic Observation Pipeline for High-Fidelity Star Cluster Formation Simulations
Alumni
Graduate
- Surinder Singh ChhabraAstroRAG: Evidence-Aware Scientific Literature Retrieval — a multi-stage retrieval and evidence-summarisation framework for astrophysics literature discovery
Undergraduate
- Victor Del RioSTARTAstro Program (community-college transfer student)
- Edwin SarabiaSTARTAstro Program (community-college transfer student)
- Alex EscamillaBridging Theory and Observation: Synthetic FIR Insights into Star Formation EfficiencyThe Astrophysical Journal 1004, 14 (2026)
- Kate GonzalezInitial developer of the Sim2SKIRT synthetic-observation pipeline with SKIRT
This is the SDSU group. For everyone I've advised — including students at other institutions and before SDSU — see the full advising record.
A question you can actually finish
The Jaxstro ecosystem is deliberately modular. Because each package owns one scientific stage and exposes clean, differentiable interfaces, a single well-scoped question — a new IMF prescription, a dynamical benchmark, a survey systematic, an identifiability test — becomes a self-contained project with a beginning and an end.
That is the point: many compact, finishable contributions rather than a few monolithic ones, on tools you can actually read.
Where to start looking: the explorables to see the models running, the software for what each package does, and the jaxstro and progenax documentation if you want to read the interfaces themselves.
Research interests
Recommended skills
None of this is a checklist you must clear before talking to me. It is what makes the first month go well.
- You can write and debug your own Python — not only run someone else's notebook.
- You are comfortable thinking in arrays: NumPy, or the willingness to learn it quickly.
- A terminal and
git, or no fear of picking them up. - Helpful, not required: modular programming, JAX, matplotlib, LaTeX, any experience on a cluster.
You do not need prior research experience, and you do not need astronomy and physics beyond the introductory sequence. If you have written code for a class or a project and had to make it actually work, that is the relevant experience.
Before you email me
Have a look around first, then tell me three things. Two or three sentences each is plenty. I am not looking for a research proposal — you are not expected to have one yet — just for a sense of who you are and what caught your attention.
- What you're curious about — a topic, a class that clicked, something you read here or elsewhere. It does not have to be a research question.
- Where you are: your year, your major, and which of my courses you've taken, if any.
- Something you've built or debugged — a class project, a script, anything you had to make actually work. It does not have to be astronomy, and it does not have to have gone well.
Please put SDSU-ASTRO in the subject line.
Potential collaborators
The software is open and built to be extended. If you work on star clusters, stellar populations, or survey inference and want to run new models, test a prescription against your own, or design an observing program around what these models predict, I'd like to hear from you — the three items above don't apply.