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<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<meta
name="description"
content="Portfolio of Dr. Robert Adriel Mostoghiu Paun, Data Scientist and Computational Astrophysicist."
/>
<title>Portfolio</title>
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class="profile-img"
alt="Dr. Robert Adriel Mostoghiu Paun"
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<div>
<h1>Dr. Robert Adriel Mostoghiu Paun</h1>
<p class="subtitle">Data Scientist · Computational Astrophysicist</p>
</div>
<p class="bio-short">
Building automated data pipelines and high-fidelity predictive models to make sense of terabyte-scale problems.<br />
<span class="location-tag">Based in Melbourne, AU.</span>
</p>
<div class="skills">
<span class="skill-tag">Python</span>
<span class="skill-tag">R</span>
<span class="skill-tag">C/C++</span>
<span class="skill-tag">SQL</span>
<span class="skill-tag">Machine Learning</span>
<span class="skill-tag">Generative AI</span>
<span class="skill-tag">AI Orchestration</span>
<span class="skill-tag">Bayesian Inference</span>
<span class="skill-tag">Data Pipelines</span>
<span class="skill-tag">HPC</span>
<span class="skill-tag">Azure Databricks</span>
<span class="skill-tag">Docker</span>
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Resume
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</a>
</nav>
<div class="sidebar-contact">
<p class="contact-text">
I'm currently open to new opportunities and collaborations. Whether
you have a question or just want to say hi, feel free to reach out!
</p>
<a href="mailto:robertadriel@gmail.com" class="btn-primary">
Say Hello ↗
</a>
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<div class="sidebar-footer">
<p>
© 2026 Robert Mostoghiu Paun.<br />Built with human creativity
& AI assistance.
</p>
</div>
</aside>
<!-- About -->
<main class="content">
<section class="section">
<div class="section-header">
<span class="section-num">01.</span>
<h2>About</h2>
</div>
<p>
I am a PhD-qualified data scientist and computational astrophysicist who builds
and analyses large-scale predictive models. My research has involved
running high-resolution cosmological simulations to study
alternative dark matter models, galaxy cluster physics, and
large-scale structures. A large part of my day-to-day involves
digging into the numerical quirks of these simulations, using
statistical models to figure out what is a real physical effect and
what is just a computational artefact, and then checking those
results against actual observations.
</p>
<p>
I apply my background in numerical modelling and high-performance
computing (HPC) to broader data science challenges. I manage
end-to-end data pipelines, wrangle terabyte-scale datasets, and use
machine learning to find useful patterns. Lately, I've been focusing
heavily on AI orchestration, leveraging foundational models to automate complex data
workflows and turn months of manual engineering into a single day's work.
Whether I'm optimising legacy C/C++ code for supercomputers or setting up
automated ETL pipelines in Python and SQL, I enjoy tackling tough
quantitative problems and making sure the data is reliable.
</p>
</section>
<!-- Experience -->
<section class="section">
<div class="section-header">
<span class="section-num">02.</span>
<h2>Experience</h2>
</div>
<div class="item">
<div class="item-header">
<span class="item-title"
>Postdoctoral Researcher & Data Scientist</span
>
<span class="item-meta">Feb 2022 – Present</span>
</div>
<div class="item-subtitle">ARC Centre for Dark Matter and Particle Physics, Swinburne University</div>
<div class="stat-grid">
<div class="stat-box">
<span class="stat-number">40%</span>
<span class="stat-label">Improvement in model accuracy</span>
</div>
<div class="stat-box">
<span class="stat-number">98%</span>
<span class="stat-label">Reduction in engineering cycle time</span>
</div>
</div>
<ul class="item-bullets">
<li>
Led international projects to build and validate large-scale predictive models.
</li>
<li>
Built and ran a custom collaboration platform for a 100-member international consortium, replacing a commercial tool and avoiding its ongoing licensing costs entirely.
</li>
<li>
Served on the Swinburne Time Allocation Committee (STACK), reviewing and ranking competing proposals to allocate scarce, high-value observatory time across an international research consortium.
</li>
<li>
Built the SAGE Tree Converter, an AI-driven tool that cut a manual 1–3 month engineering job down to a single day.
</li>
<li>
Wrote custom GIZMO extensions for distributed HPC environments, improving predictive-model accuracy by 40% by finding and fixing systematic errors.
</li>
<li>
Built end-to-end Python and SQL ETL pipelines to process terabyte-scale raw simulation data.
</li>
<li>
Used A/B testing, feature engineering, and statistical diagnostics to tell genuine signals apart from computational noise in terabyte-scale simulation outputs.
</li>
<li>
Followed that up with the Spurious Halo Classifier, swapping a hand-tuned cutoff for scikit-learn and PyTorch models trained on independently labelled data, with experiment tracking (MLflow), model explainability (SHAP), and CI for reproducible results.
</li>
<li>
Mentored 3 undergraduate and 2 postgraduate researchers and gave regular progress updates to a cross-disciplinary team across astrophysics, physics, and engineering.
</li>
</ul>
</div>
<div class="item">
<div class="item-header">
<span class="item-title">PhD Researcher</span>
<span class="item-meta">Sep 2016 – Nov 2020</span>
</div>
<div class="item-subtitle">Universidad Autónoma de Madrid</div>
<div class="stat-grid">
<div class="stat-box">
<span class="stat-number">TB+</span>
<span class="stat-label">Scale of datasets standardised</span>
</div>
<div class="stat-box">
<span class="stat-number">Multi-HPC</span>
<span class="stat-label">International facility integration</span>
</div>
</div>
<ul class="item-bullets">
<li>
Developed Python workflows and R notebooks leveraging NumPy/Pandas to integrate and standardise terabyte-scale HPC datasets across international facilities.
</li>
<li>
Conducted complex statistical benchmarking of modelling architectures to isolate physical signals from computational artefacts.
</li>
<li>
Communicated technical insights across 9 peer-reviewed publications and 6 international conferences.
</li>
</ul>
</div>
</section>
<!-- Projects -->
<section class="section">
<div class="section-header">
<span class="section-num">03.</span>
<h2>Projects</h2>
</div>
<div class="item">
<div class="item-header">
<span class="item-title"
>Spurious Halo Classifier
<span class="status-badge">
<span class="pulse-dot"></span>
Ongoing
</span>
</span>
</div>
<div class="project-tags">
<span class="skill-tag">Python</span>
<span class="skill-tag">Machine Learning</span>
<span class="skill-tag">PyTorch</span>
<span class="skill-tag">MLflow</span>
<span class="skill-tag">CI/CD</span>
</div>
<ul class="item-bullets">
<li>
Built a classifier (scikit-learn, PyTorch) to replace a hand-tuned cutoff, training it on independently labelled data for more reliable, repeatable results.
</li>
<li>
Organised the workflow around a Databricks-inspired medallion data architecture, with MLflow for experiment tracking and SHAP for explaining model decisions.
</li>
<li>
Added CI so training and validation stay reproducible as the models evolve.
</li>
</ul>
</div>
<div class="item">
<div class="item-header">
<span class="item-title"
>Statistical Data Processing Workflow</span
>
</div>
<div class="project-tags">
<span class="skill-tag">Python</span>
<span class="skill-tag">SQL</span>
<span class="skill-tag">ETL</span>
<span class="skill-tag">Machine Learning</span>
<span class="skill-tag">Power BI</span>
</div>
<ul class="item-bullets">
<li>
Built end-to-end Python and SQL ETL pipelines to clean and standardise terabyte-scale datasets for distributed HPC environments.
</li>
<li>
Used data science techniques like A/B testing and feature engineering to spot anomalies and separate real signals from noise.
</li>
<li>
Built interactive Power BI/Fabric dashboards to share modelling results with non-technical stakeholders.
</li>
</ul>
</div>
<div class="item">
<div class="item-header">
<span class="item-title"
>Custom Physics Module for GIZMO
<span class="status-badge">
<span class="pulse-dot"></span>
Actively Maintained
</span>
</span>
</div>
<div class="project-tags">
<span class="skill-tag">C/C++</span>
<span class="skill-tag">Python</span>
<span class="skill-tag">HPC</span>
<span class="skill-tag">Numerical Analysis</span>
<span class="skill-tag">CI/CD</span>
</div>
<ul class="item-bullets">
<li>
Wrote custom C/C++ extensions for the GIZMO framework (GIZMO-PBHEF) to model complex system dynamics on distributed HPC.
</li>
<li>
Developed and tested new simulation methods, improving accuracy by 40% by tracking down systematic errors across terabyte-scale models.
</li>
<li>
Used CI/CD to manage the full build and deployment cycle, keeping parallelised builds stable and reliable.
</li>
</ul>
</div>
<div class="item">
<div class="item-header">
<span class="item-title"
>SAGE Universal Merger Tree Converter
<span class="status-badge">
<span class="pulse-dot"></span>
Ongoing
</span>
</span>
</div>
<div class="project-tags">
<span class="skill-tag">Python</span>
<span class="skill-tag">AI Orchestration</span>
<span class="skill-tag">LLMs</span>
<span class="skill-tag">CLI</span>
<span class="skill-tag">System Architecture</span>
</div>
<ul class="item-bullets">
<li>
Built an AI-assisted CLI that uses LLMs to convert complex hierarchical simulation outputs into standard formats on its own.
</li>
<li>
Used an adapter design pattern and a persistent knowledge base to keep token usage low and make the tool easy to extend.
</li>
<li>
Turned a manual 1–3 month job into a single-day process, a 98% cut in turnaround time.
</li>
</ul>
</div>
</section>
<!-- Publications -->
<section class="section">
<div class="section-header">
<span class="section-num">04.</span>
<h2>Publications</h2>
</div>
<p>
I've contributed to several peer-reviewed astrophysics papers,
mostly focusing on large-scale statistical modelling and galaxy
formation.
</p>
<div class="stat-grid">
<div class="stat-box">
<span class="stat-number">5</span>
<span class="stat-label">First-Author Papers</span>
</div>
<div class="stat-box">
<span class="stat-number">16</span>
<span class="stat-label">Total Publications</span>
</div>
</div>
<p>
Latest publication: <em>On the redshift evolution of the spin parameter in cosmological simulations, Riera et al. 2026, PASA, 43, e063</em>.
</p>
<div class="ads-library-link">
<a
href="https://ui.adsabs.harvard.edu/user/libraries/IPRUqRaDSnCsOrF4077b2Q"
target="_blank"
class="text-link"
>
View full ADS Library ↗
</a>
</div>
</section>
<!-- Professional Development -->
<section class="section">
<div class="section-header">
<span class="section-num">05.</span>
<h2>Professional Development</h2>
</div>
<div class="item">
<div class="item-header">
<span class="item-title">Commercialisation Training Program for Medical Researchers</span>
<span class="item-meta">Sep 2025 – Dec 2025</span>
</div>
<div class="item-subtitle">AAMRI VIC</div>
<p class="item-desc">
Selected for a competitive 20-person cohort to develop commercialisation pathways for cross-sector digital health projects. Wrapped up the program with an investor pitch night, presenting technical research as a commercial proposition to an industry panel.
</p>
</div>
<div class="item">
<div class="item-header">
<span class="item-title">Research Translation & Design Thinking</span>
<span class="item-meta">Jul 2025</span>
</div>
<div class="item-subtitle">IdeaSquare, CERN</div>
<p class="item-desc">
Selected for an intensive program focused on re-framing technical research for real-world applications through commercial literacy and visual storytelling. Developed capabilities in creative problem-solving and translating complex technical knowledge for non-specialised audiences.
</p>
</div>
</section>
<!-- Education -->
<section class="section">
<div class="section-header">
<span class="section-num">06.</span>
<h2>Education</h2>
</div>
<div class="item">
<div class="item-header">
<span class="item-title">PhD in Computational Astrophysics</span>
<span class="item-meta">Nov 2020</span>
</div>
<div class="item-subtitle">Universidad Autónoma de Madrid</div>
<p class="item-desc">
Graduated Summa Cum Laude. Awarded Doctorate Honourable Mention in
2022.
</p>
</div>
<div class="item">
<div class="item-header">
<span class="item-title">MSc in Cosmology and Particle Physics</span>
<span class="item-meta">Jun 2016</span>
</div>
<div class="item-subtitle">Universidad Autónoma de Madrid</div>
<p class="item-desc">
Awarded general enrolment funding and academic stipend by the Spanish Ministry of Education.
</p>
</div>
<div class="item">
<div class="item-header">
<span class="item-title">BSc in Physics</span>
<span class="item-meta">Jun 2015</span>
</div>
<div class="item-subtitle">Universidad Autónoma de Madrid</div>
<p class="item-desc">
Awarded general enrolment funding and academic stipend by the Spanish Ministry of Education.
</p>
</div>
</section>
</main>
</div>
</body>
</html>