Stefano Blando

Getting Started

Sat, 17 Feb 2024 00:00:00 +0000

Quick Start from Template

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Project Structure Configuration Create content

Customizing Hugo

Mon, 01 Jan 0001 00:00:00 +0000

View the full docs at

Project Structure

Mon, 01 Jan 0001 00:00:00 +0000

Folder Structure

There are 4 main folders for Hugo-based sites:

content/ for your Markdown-formatted content files (homepage, etc.)
- _index.md the homepage (Hugo requires that the homepage and archive pages have an underscore prefix)
assets/
- media/ for your media files (images, videos)
  - icons/custom/ upload any custom SVG icons you want to use
config/_default/ for your site configuration files
- hugo.yaml to configure Hugo (site title, URL, Hugo options, setup per-folder page features)
- module.yaml to install or uninstall Hugo themes and plugins
- params.yaml to configure Hugo Blox options (SEO, analytics, site features)
- menus.yaml to configure your menu links (if the menu is enabled in params.yaml)
- languages.yaml to configure your site’s language or to set language-specific options in a multilingual site
static/uploads/ for any files you want visitors to download, such as a PDF
go.mod sets the version of Hugo themes/plugins which your site uses

Hugo File Naming Convention

Hugo gives us two options to name standard page files: as TITLE/index.md or TITLE.md where TITLE is your page name.

The page name should be lowercase and using hyphens (-) instead of spaces.

Both approaches result in the same output, so you can choose your preferred approach to naming and organizing files. A benefit to the folder-based approach is that all your page’s files (such as images) are self-contained within the page’s folder, so it’s more portable if you wish to share the original Markdown page with someone.

The homepage is a special case as Hugo requires the homepage and listing pages to be named _index.md.

The docs navigation is automatically generated based on the content in the docs/ folder and is sorted alphabetically.

The order of pages can be changed by adding the weight parameter in the front matter of your Markdown files.

In the example below, the example.md page will appear before the test.md page as it has a lower weight:

Page example.md:

---
title: My Example
weight: 1
---

Page test.md:

---
title: My Test
weight: 2
---

Configuration

Mon, 01 Jan 0001 00:00:00 +0000

The configuration of your site can be found in config/_default/.

Full Documentation

See

Links are automatically generated from the structure of your content directory. Simply add a folder to nest a page.

Extra Links

Additional links can be added under the sidebar section of your config/_default/menus.yaml:

menu:
 sidebar:
 - name: "Need help?"
 params:
 type: separator
 weight: 1
 - name: "A page"
 pageRef: "/page-filename-here"
 weight: 2
 - name: "An external link ↗"
 url: "https://hugoblox.com"
 weight: 3

A table of contents is automatically generated from the headings your Markdown file.

It can optionally be disabled by setting toc: false in the front matter of a page:

---
title: My Page
toc: false
---

Presented at MARS @ ETAPS 2026

Tue, 14 Apr 2026 00:00:00 +0000

Last week I presented our paper, “Statistical model checking of the Island Model: an established economic agent-based model of endogenous growth”, at MARS @ ETAPS 2026 in Turin.

This was a particularly meaningful milestone for me: it was the first presentation of my first PhD paper, and also my first international conference.

I am very glad the talk went well. Beyond the presentation itself, I really appreciated the opportunity to discuss the work with professors and researchers in the area and to spend a few days in a workshop environment that I found open, stimulating, and genuinely pleasant.

The paper is co-authored with Giorgio Fagiolo, Daniele Giachini, Andrea Vandin, and Ernest Ivanaj, and focuses on how statistical model checking, and in particular MultiVeStA, can support a more rigorous analysis of the Island Model.

📄
👉
📰

Statistical model checking of the Island Model: an established economic agent-based model of endogenous growth

Sun, 12 Apr 2026 00:00:00 +0000

Paper Accepted at MARS @ ETAPS 2026

Fri, 20 Mar 2026 00:00:00 +0000

Our paper, “Statistical model checking of the Island Model: an established economic agent-based model of endogenous growth”, has been accepted at MARS @ ETAPS 2026.

The work is co-authored with Giorgio Fagiolo, Daniele Giachini, Andrea Vandin, and Ernest Ivanaj. The paper shows how statistical model checking and MultiVeStA can be used to make the analysis of the Island Model more rigorous, more automated, and more reproducible, while preserving the economic substance of the original framework.

I presented it in Turin, Italy, on Sunday, April 12, 2026.

📄
👉
🎤

For me, this is one of the clearest examples of the direction I want to push in my PhD work: giving complex simulation models stronger statistical foundations without losing their interpretability.

Multi-Agent Orchestration

Wed, 18 Mar 2026 00:00:00 +0000

This project can be read as a system for real-time economic coordination under changing phases, partial information, and hard timing constraints.

The system is structured as an event-driven multi-agent orchestration layer. It listens to the game through SSE events, keeps a runtime representation of the environment, and switches strategy depending on the current phase of play: policy update, procurement auction, inventory reconciliation, and fulfillment.

What makes the project interesting is not just the use of multiple agents, but the way orchestration is tied to operational robustness. Different capability sets are activated at different stages, while local persistence, metrics, and replay analysis help make decisions more stable under noisy runtime conditions.

In practice, it is a good example of a project where agentic design had to be grounded in execution reliability rather than in generic prompting alone. The deeper pattern is auction-based coordination with inventory constraints and demand handling.

Interactive Explorer

The interactive app focuses on the engineering core of the project: the live event loop, shared runtime state, stylized agent interaction, phase-specific agents, capability partitioning, bounded memory, and KPI replay.

It is intentionally presented as a runtime architecture explorer, not as a fake benchmark dashboard. The goal is to make the orchestration logic legible in the same visual language used for the Island Model and PFSE apps, with emphasis on coordination, auctions, and fulfillment.

RiskSentinel - Agentic Systemic Risk Simulator

Sun, 15 Mar 2026 00:00:00 +0000

RiskSentinel is an agentic systemic risk simulator built around a question I find both practical and conceptually interesting: if a large financial node is hit by a shock, how can we make the propagation of that stress visible, comparable, and explainable in real time?

Built for the Microsoft AI Dev Days Hackathon 2026, the project combines three contagion models, topology-aware analytics, and a bounded multi-agent workflow on top of research-grade market network data. The purpose is not only to simulate cascades, but to make them easier to inspect through natural-language interaction, interactive visualization, and model comparison.

What makes the project work is the combination of several layers that are often separated: a proper network simulation engine, an interface that makes the results explorable, and an agentic layer that helps interpret what is happening without pretending to replace the underlying quantitative machinery.

The result is a practical prototype for systemic risk monitoring, sitting between quantitative finance, complex systems, and AI-assisted decision support.

You can explore the project here:

RiskSentinel for Microsoft AI Dev Days 2026

Sun, 15 Mar 2026 00:00:00 +0000

RiskSentinel is the project I built for the Microsoft AI Dev Days Hackathon 2026.

The core idea was to create a system that could make systemic risk more explorable and more tangible: instead of treating contagion as an abstract output in a paper or a notebook, I wanted an interface where shocks could be launched, propagated, compared, and interpreted in real time.

The project combines network science, contagion modeling, and agentic AI on top of research-grade financial network data covering 210 S&P 500 stocks and 3,081 daily snapshots. Under the hood, it integrates three propagation models, interactive network analytics with Streamlit and Plotly, and an agentic workflow built with Microsoft Agent Framework and Azure OpenAI.

What I like most about this project is that it sits exactly at the boundary between my research interests and practical prototyping: financial networks, complex systems, decision support, and AI agents all in the same tool.

👉
GitHub:
App:

Island Model + MultiVeStA — Statistical Model Checking of Economic Growth

Fri, 06 Mar 2026 00:00:00 +0000

This project reproduces and extends the Fagiolo & Dosi (2003) Island Model — a landmark agent-based model of endogenous economic growth — using MultiVeStA, a tool for sequential statistical model checking of stochastic systems.

The paper was accepted at MARS @ ETAPS 2026 (Workshop on Models for Formal Analysis of Real Systems, European Joint Conferences on Theory and Practice of Software).

Work with Giorgio Fagiolo, Daniele Giachini, Andrea Vandin, and Ernest Ivanaj (Scuola Superiore Sant’Anna).

Related pages: , , and .

What the Model Does

The Island Model captures endogenous growth through the interaction of three types of heterogeneous agents operating on a fitness landscape:

Miners exploit their current productive niche, accumulating skills over time
Imitators copy the most successful visible agent, diffusing knowledge across the economy with probability φ
Explorers search for new islands at random, driving innovation and preventing lock-in

The key insight is that the tension between exploitation and exploration — parameterised by ε — generates self-sustaining growth dynamics without requiring exogenous technological progress.

What MultiVeStA Adds

Standard Monte Carlo analysis uses a fixed number of simulation runs with no formal guarantee on estimation quality. MultiVeStA applies sequential statistical model checking: it runs simulations adaptively, stopping only when the 95% confidence interval on E[logGDP] is narrower than δ=0.05 at every time step. This provides a formal precision guarantee — the sample size is determined by the data variance, not by the experimenter.

Our analysis confirms the optimality of moderate exploration (ε ≈ 0.1), reproduces all stylized facts of the original model, and establishes through Welch t-test counterfactual analysis that 6 out of 7 pairwise parameter comparisons yield statistically distinguishable growth trajectories. The single exception (ρ=3.0 vs ρ=5.0) reveals a saturation effect in knowledge locality.

Interactive Explorer

The interactive app lets you explore the model live: watch agents move across the technology landscape, observe imitation cascades and exploration events, run MultiVeStA sensitivity analysis on α, φ, and ρ, and see how the sequential sampling converges.

Robust Portfolio Optimization under Systematic Market Disruptions (PFSE)

Fri, 06 Mar 2026 00:00:00 +0000

This project introduces the Parallel Factor Space Estimator (PFSE), a hybrid framework for robust covariance estimation that resolves a fundamental trade-off in institutional portfolio management: traditional robust estimators (MCD, Tyler) offer strong statistical guarantees but are computationally infeasible for daily rebalancing of 100+ assets, while efficient methods (Ledoit-Wolf, sample covariance) have zero breakdown point against systematic contamination.

PFSE exploits a structural insight: during systematic market disruptions — flash crashes, monetary policy shocks, crisis contagion — extreme movements propagate through common factors, not idiosyncratic components. By concentrating robust estimation in reduced k-dimensional factor space (k=5 versus p=100–1000), PFSE inherits 25% breakdown point from MCD while achieving 32× computational speedup.

Work with Alessio Farcomeni (University of Roma Tor Vergata). Submitted to Computational Economics (Springer), March 2026.

Key Results

Validated through three complementary stages:

Monte Carlo (p=100, ε=10% contamination): PFSE Sharpe 1.42 vs 0.96 for sample covariance — maintains 97% of clean-data performance while sample covariance degrades 31%
S&P 500 backtest (2015–2025): Out-of-sample Sharpe 1.87 vs 1.63 (+14.7%), max drawdown −24.3% vs −34.1% (−29%) during COVID-19, turnover −42%
Five stress scenarios: PFSE rank-1 across all scenarios, average Sharpe 1.67 vs 1.39 (+20%), lowest performance variability (CoV 0.041 vs 0.064)
Economic value: $72M normal-period + $93M stress-period benefits per $1B portfolio, benefit-cost ratio 31:1

Interactive Explorer

The interactive app lets you explore the full results: run the PFSE estimation algorithm live, compare methods under increasing contamination levels, examine computational scalability, and inspect S&P 500 cumulative returns across all four market regimes.

PokéNexus

Wed, 04 Feb 2026 00:00:00 +0000

PokéNexus was born from something very simple: I have loved Pokémon since I was a child, and at some point I wanted to merge that world with the kind of tools and ideas I now enjoy building with.

The result is a Streamlit app that turns the Pokémon universe into an interactive space where graph visualization, game mechanics, and API-driven data come together. I used NetworkX, PyVis, and Plotly to explore relationships between types and entities, while PokeAPI provides the live data layer for creatures, evolutions, and related information.

Instead of being just a static graph, the project grew into a small playable system: teams can be managed, items stored, badges collected, and different progression loops layered on top of the visualization. That mix of structure, exploration, and play is exactly what made the project fun to build.

It is not a research project, and it is not meant to be. It is a personal experiment where a childhood passion meets the way I now think about networks, interfaces, and interactive Python applications.

Master Graduation

Fri, 23 Jan 2026 00:00:00 +0000

I am proud to share that on Monday, February 2, 2026, I was awarded the II Level Master in Customer Experience, Statistics, Machine Learning and Artificial Intelligence (CESMA) at the University of Rome Tor Vergata, with a final grade of 110/110 cum laude.

The Thesis

My thesis, titled “Network Topology Analysis and Machine Learning Techniques for Systemic Risk Prediction in U.S. Equity Markets”, explores the application of Graph Neural Networks and complex network theory to identify early warning signals in financial markets.

This work is directly connected to my ongoing research. You can explore the technical details and code in the dedicated sections of this portfolio:

👉
📄

The master provided a strong foundation in advanced statistical methods and AI, which I am now applying to my PhD research at Scuola Superiore Sant’Anna.

A Multi-Method Validation Framework for Large-Scale Multilingual Text Analytics

Thu, 15 Jan 2026 00:00:00 +0000

Network Topology Analysis and Machine Learning Techniques for Systemic Risk Prediction in U.S. Equity Markets

Thu, 15 Jan 2026 00:00:00 +0000

Network Topology Analysis for Systemic Risk Prediction

Sat, 10 Jan 2026 00:00:00 +0000

This project corresponds to my CESMA thesis on systemic risk prediction in U.S. equity markets. The underlying question is simple but important: can network topology say something useful about market stress before standard indicators do?

Using daily data from 210 S&P 500 constituents (2013-2025), the project combines dynamic correlation networks with machine learning models ranging from gradient boosting to Graph Neural Networks such as GraphSAGE and GAT. The goal is not just classification accuracy, but economic usefulness under realistic validation and backtesting constraints.

The most interesting result is that network-derived signals appear to carry genuine early-warning information, especially around severe and structurally fragile market states. In the strongest configurations, the framework improves both timing and trading performance relative to simpler baselines.

This project is paired with the related thesis page, where the same work is presented as a publication entry.

NLP & Semantic Network Analysis

Sat, 10 Jan 2026 00:00:00 +0000

This project is the technical implementation behind the publication “A Multi-Method Validation Framework for Large-Scale Multilingual Text Analytics” (JADT 2026, in review). It operationalizes the full analytical workflow used in the paper, from data preparation to cross-method validation and result comparison.

The pipeline combines R and Python modules over a large multilingual review corpus, including: preprocessing and TF-IDF, LDA topic modeling, LSA and Correspondence Analysis, lexicon- and model-based sentiment analysis, clustering, and co-occurrence network analysis. The repository also includes cross-platform validation scripts to compare method outputs and check structural stability across implementations.

The central objective is methodological robustness: verifying which findings remain consistent when methods, model families, and language-specific components vary. In this sense, the project is not a generic NLP demo, but a reproducible research pipeline designed for quantitative validation of text-analytic conclusions.

Advanced Recommender System

Fri, 20 Jun 2025 00:00:00 +0000

This project was developed within the CESMA Master’s program in collaboration with TIM. Instead of framing the problem as a standard classification task, the system was designed as a learning-to-rank pipeline for next-best-action recommendation.

That shift in framing matters because ranking is closer to the actual business decision: not just whether an action is good or bad, but which action should come first for a given user.

The pipeline combines careful validation, Bayesian optimization, and ensemble ranking strategies. The end result is a substantial improvement over baseline performance on NDCG@5, making the project a solid example of applied machine learning under realistic evaluation constraints.

Performance summary:

Stage	NDCG@5 Score	Improvement vs Baseline
Baseline Model	0.5030	–
Best Single Model	0.6838	+35.94%
Best Ensemble	0.6852	+36.23%

Overall, it is one of the clearest examples in the portfolio of taking a familiar ML task and reformulating it in a way that is better aligned with the actual decision problem.

High-dimensional Robust Portfolio Optimization Under Contamination: A Factor-Analytic Approach

Fri, 04 Apr 2025 00:00:00 +0000

Real Estate AI Agent

Wed, 05 Mar 2025 00:00:00 +0000

This project explores how an AI agent can be used as a practical layer on top of a more traditional predictive workflow. In this case, the domain is real estate: price estimation, market analysis, and user interaction around property-related questions.

The project combines valuation models with an LLM-based interface for natural-language interaction and task-level orchestration. The interesting part is not just the agent wrapper itself, but the attempt to connect predictive models with a more usable front-end for exploration and decision support.

Lightweight Fine-Tuning with PEFT & LoRA

Wed, 20 Nov 2024 00:00:00 +0000

This project focuses on a practical question in NLP: how much useful adaptation can you obtain from a pretrained model without paying the full cost of fine-tuning everything?

Using LoRA on distilbert-base-uncased for sentiment analysis, the pipeline shows that a very small trainable subset of parameters can still deliver a strong performance jump over the zero-shot baseline. That makes the project less about squeezing out maximum benchmark accuracy and more about understanding the trade-off between performance and efficiency.

Built with the Hugging Face ecosystem, the implementation covers evaluation, LoRA configuration, training, and inference in a lightweight setup that remains accessible on modest hardware.

Gas Network Risk Forecasting

Fri, 01 Nov 2024 00:00:00 +0000

This project was developed for the Hera Group Hackathon, where it earned 2nd place. The task was to detect gas leak risk in a setting dominated by imbalance, sparse events, and operational uncertainty.

The pipeline combines geospatial-temporal feature engineering with synthetic data augmentation through CTGAN and TimeGAN, then uses SHAP to keep the final model interpretable rather than purely predictive.

What I still like about this project is its balance between pragmatism and method: it is a hackathon project, but it already reflects an approach I use often, namely trying to make difficult prediction problems more robust without giving up explainability.

AI Photo Editor with SAM & SDXL

Sun, 10 Mar 2024 00:00:00 +0000

This project explores the intersection of precise computer vision and generative image editing by combining Segment Anything (SAM) with Stable Diffusion XL.

The core idea is straightforward: segmentation provides exact control over what should be changed, while diffusion-based inpainting provides the generative flexibility to actually change it. That makes the system useful not only as a demo, but as a concrete example of how discriminative and generative models can be combined inside the same workflow.

Built in Python with PyTorch, Diffusers, and Gradio, the project supports interactive masking, object replacement, and background generation while keeping the pipeline lightweight enough to run on consumer hardware with the right optimizations.

Custom Chatbot with RAG

Thu, 15 Feb 2024 00:00:00 +0000

This project uses a deliberately small but structured domain to explore a larger idea: how to make language-model outputs more reliable by grounding them in retrieved context.

The chatbot is built around a curated dataset of fictional characters and uses a full RAG pipeline with embeddings, retrieval, and prompt conditioning. The dataset is playful, but the methodological point is serious: retrieval changes the behavior of the model from generic completion to context-bounded reasoning.

Because the underlying data is semantically rich, the system can handle not only question answering but also character comparison, recommendation, and trait-based exploration. That makes it a useful compact example of retrieval-driven NLP design.

Example Talk: Recent Work

Mon, 01 Jan 2024 00:00:00 +0000

Example Talk

Dr. Alex Johnson · Meta AI

Research Overview

Multimodal LLMs
Efficient training
Responsible AI

Code & Math

def score(x: int) -> int:
 return x * x

$$ E = mc^2 $$

Dual Column Layout

Left Column

Point A
Point B
Point C

Right Column

Detail 1
Detail 2
Detail 3

Main Content (2/3 width)

This column takes up twice the space of the right column.

def example():
 return "code works too"

Note
Key points in smaller column

Image + Text Layout

Results

95% accuracy
10x faster inference
Lower memory usage

Breakthrough!

Speaker Notes

Press S to open presenter view with notes!

This slide has hidden speaker notes below.

Note:

This is a speaker note (only visible in presenter view)
Press S key to open presenter console
Perfect for remembering key talking points
Can include reminders, timing, references
Supports Markdown formatting too!

Progressive Reveals

Content appears step-by-step:

First point appears Then the second point Finally the conclusion This one can be highlighted!

Note: Use fragments to control pacing and maintain audience attention. Each fragment appears on click.

Diagrams with Mermaid

graph LR A[Research Question] --> B{Hypothesis} B -->|Valid| C[Experiment] B -->|Invalid| D[Revise] C --> E[Analyze Data] E --> F{Significant?} F -->|Yes| G[Publish] F -->|No| D

Perfect for: Workflows, architectures, processes

Note: Mermaid diagrams are created from simple text. They’re version-controllable and edit anywhere!

Research Results

Model	Accuracy	Speed	Memory
Baseline	87.3%	1.0x	2GB
Ours (v1)	92.1%	1.5x	1.8GB
Ours (v2)	95.8%	2.3x	1.2GB

Key Finding: 8.5% improvement over baseline with 40% memory reduction

Note: Tables are perfect for comparative results. Markdown tables are simple and version-control friendly.

Custom Backgrounds

This slide has a blue background!

You can customize:

Background colors
Background images
Gradients
Videos (yes, really!)

Use {{< slide background-color="#hex" >}}

There’s more content below! ⬇️

Press the Down Arrow to see substeps.

Note: This demonstrates Reveal.js’s vertical slide feature. Great for optional details or deep dives.

Substep 1: Details

This is additional content in a vertical stack.

Navigate down for more, or right to skip to next topic →

Substep 2: More Details

Even more detailed information.

Press Up Arrow to go back, or Right Arrow to continue.

Citations & Quotes

“The best way to predict the future is to invent it.”

— Alan Kay

Or reference research:

Recent work by Smith et al. (2024) demonstrates that Markdown-based slides improve reproducibility by 78% compared to proprietary formats¹.

Media: YouTube Videos

Note: Embed YouTube videos with just the video ID. Perfect for demos, tutorials, or interviews.

Media: All Options

Embed various media types with simple shortcodes:

YouTube: {{< youtube VIDEO_ID >}}
Bilibili: {{< bilibili id="BV1..." >}}
Local videos: {{< video src="file.mp4" controls="yes" >}}
Audio: {{< audio src="file.mp3" >}}

Perfect for demos, interviews, tutorials, or podcasts!

Note: All media types work seamlessly in slides. Just use the appropriate shortcode.

Interactive Elements

Try these keyboard shortcuts:

→ ← : Navigate slides
↓ ↑ : Vertical navigation
S : Speaker notes
F : Fullscreen
O : Overview mode
/ : Search
ESC : Exit modes

Hidden Slide Demo (Inline Comment)

This slide is hidden using the  comment method.

Perfect for:

Speaker-only content
Backup slides
Work-in-progress content

Note: This slide won’t appear in the presentation but remains in source for reference.

Thanks

Questions?

🌐 Website:
🐦 X/Twitter:
💬 Discord:
⭐ GitHub:

All slides created with Markdown • No vendor lock-in • Edit anywhere

Note: Thank you for your attention! Feel free to reach out with questions or contributions.

🎨 Branding Your Slides

Add your identity to every slide with simple configuration!

What you can add:

Element	Position Options
Logo	top-left, top-right, bottom-left, bottom-right
Title	Same as above
Author	Same as above
Footer Text	Same + bottom-center

Edit the branding: section in your slide’s front matter (top of file).

📁 Adding Your Logo

Place your logo in assets/media/ folder
Use SVG format for best results (auto-adapts to any theme!)
Add to front matter:

branding:
 logo:
 filename: "your-logo.svg" # Must be in assets/media/
 position: "top-right"
 width: "60px"

Tip: SVGs with fill="currentColor" automatically match theme colors!

📝 Title & Author Overlays

Show presentation title and/or author on every slide:

branding:
 title:
 show: true
 position: "bottom-left"
 text: "Short Title" # Optional: override long page title

 author:
 show: true
 position: "bottom-right"

Author is auto-detected from page front matter (author: or authors:).

📄 Footer Text

Add copyright, conference name, or any persistent text:

branding:
 footer:
 text: "© 2024 Your Name · ICML 2024"
 position: "bottom-center"

Tip: Supports Markdown! Use [Link](url) for clickable links.

🔇 Hiding Branding Per-Slide

Sometimes you want a clean slide (title slides, full-screen images).

Add this comment at the start of your slide content:

<!-- no-branding -->
## My Clean Slide

Content here...

☝️ This slide uses  — notice no logo or overlays!

🔇 Selective Hiding

Hide just the header (logo + title):

<!-- no-header -->

Or just the footer (author + footer text):

<!-- no-footer -->

☝️ This slide uses  — footer still visible below!

✅ Quick Reference

Comment	Hides
`<!-- no-branding -->`	Everything (logo, title, author, footer)
`<!-- no-header -->`	Logo + Title overlay
`<!-- no-footer -->`	Author + Footer text

☝️ This slide uses  — logo still visible above!

🚀 Get Started

Copy this example’s front matter as a starting point
Replace logo with yours in assets/media/
Customize positions and text
Use  for special slides

Pro tip: Set site-wide defaults in config/_default/params.yaml under slides.branding!

Smith, J. et al. (2024). Open Science Presentations. Nature Methods. ↩︎

Embed Media

Tue, 24 Oct 2023 00:00:00 +0000

is designed to give technical content creators a seamless experience. You can focus on the content and the HugoBlox Kit which this template is built upon handles the rest.

Embed videos, podcasts, code, LaTeX math, and even test students!

On this page, you’ll find some examples of the types of technical content that can be rendered with Hugo Blox.

Video

Teach your course by sharing videos with your students. Choose from one of the following approaches:

Youtube:

{{< youtube w7Ft2ymGmfc >}}

Bilibili:

{{< bilibili id="BV1WV4y1r7DF" >}}

Video file

Videos may be added to a page by either placing them in your assets/media/ media library or in your , and then embedding them with the video shortcode:

{{< video src="my_video.mp4" controls="yes" >}}

Podcast

You can add a podcast or music to a page by placing the MP3 file in the page’s folder or the media library folder and then embedding the audio on your page with the audio shortcode:

{{< audio src="ambient-piano.mp3" >}}

Try it out:

Test students

Provide a simple yet fun self-assessment by revealing the solutions to challenges with the spoiler shortcode:

{{< spoiler text="👉 Click to view the solution" >}}
You found me!
{{< /spoiler >}}

renders as

👉 Click to view the solution

You found me 🎉

Math

HugoBlox Kit supports a Markdown extension for $\LaTeX$ math. You can enable this feature by toggling the math option in your config/_default/params.yaml file.

To render inline or block math, wrap your LaTeX math with {{< math >}}$...${{< /math >}} or {{< math >}}$$...$${{< /math >}}, respectively.

Note

We wrap the LaTeX math in the Hugo Blox math shortcode to prevent Hugo rendering our math as Markdown. This callout now uses the standard Markdown alert syntax!

Example math block:

{{< math >}}
$$
\gamma_{n} = \frac{ \left | \left (\mathbf x_{n} - \mathbf x_{n-1} \right )^T \left [\nabla F (\mathbf x_{n}) - \nabla F (\mathbf x_{n-1}) \right ] \right |}{\left \|\nabla F(\mathbf{x}_{n}) - \nabla F(\mathbf{x}_{n-1}) \right \|^2}
$$
{{< /math >}}

renders as

$$\gamma_{n} = \frac{ \left | \left (\mathbf x_{n} - \mathbf x_{n-1} \right )^T \left [\nabla F (\mathbf x_{n}) - \nabla F (\mathbf x_{n-1}) \right ] \right |}{\left \|\nabla F(\mathbf{x}_{n}) - \nabla F(\mathbf{x}_{n-1}) \right \|^2}$$

Example inline math {{< math >}}$\nabla F(\mathbf{x}_{n})${{< /math >}} renders as $\nabla F(\mathbf{x}_{n})$ .

Example multi-line math using the math linebreak (\\):

{{< math >}}
$$f(k;p_{0}^{*}) = \begin{cases}p_{0}^{*} & \text{if }k=1, \\
1-p_{0}^{*} & \text{if }k=0.\end{cases}$$
{{< /math >}}

renders as

$$ f(k;p_{0}^{*}) = \begin{cases}p_{0}^{*} & \text{if }k=1, \\ 1-p_{0}^{*} & \text{if }k=0.\end{cases} $$

Code

HugoBlox Kit utilises Hugo’s Markdown extension for highlighting code syntax. The code theme can be selected in the config/_default/params.yaml file.

```python
import pandas as pd
data = pd.read_csv("data.csv")
data.head()
```

renders as

import pandas as pd
data = pd.read_csv("data.csv")
data.head()

Inline Images

{{< icon name="python" >}} Python

renders as

python Python

Experience

Tue, 24 Oct 2023 00:00:00 +0000

Create Beautiful Presentations with Markdown

Sun, 01 Jan 2017 00:00:00 +0000

🎯 Why Markdown Slides?

True Presentation Freedom

Unlike PowerPoint or Keynote, your presentations are future-proof, portable, and completely under your control. No proprietary formats, no vendor lock-in, no subscription fees.

The Problem with Traditional Slides

PowerPoint & Keynote:

💸 Expensive licenses or subscriptions
🔒 Proprietary file formats (.pptx, .key)
💻 Platform-specific (Windows/Mac only)
📦 Large binary files
🚫 Difficult to version control
😰 Lost formatting when sharing

Google Slides:

☁️ Requires internet connection
🔐 Data stored on Google’s servers
📱 Limited offline editing
🎨 Formatting breaks when exporting
🔗 Dependency on Google’s platform

The Hugo Blox Solution

Markdown Changes Everything

Write your presentations in simple, human-readable Markdown. Edit anywhere, present anywhere, own forever.

✨ What You Get

🎨 Professional Design, Zero Effort

15+ Built-in Themes — Black, white, sky, league, and more
Syntax Highlighting — Beautiful code blocks with 50+ languages
Math Support — LaTeX equations render perfectly: $E = mc^2$
Responsive — Looks great on any screen size

📝 Write in Plain Text

## My Slide Title

- Point one
- Point two
- Point three

```python
def hello():
 return "World!"
```

---

That’s it! No complex UI, no formatting headaches.

🔄 Edit Anywhere, Anytime

Zero Lock-In

Your slides are just Markdown files. Edit them in:

Lore Studio — Visual editing with live preview
VS Code — With Markdown extensions
Obsidian — Note-taking app that speaks Markdown
Typora — Minimal distraction writing
Any text editor — Even Notepad works!

Try Lore Studio

🎯 Advanced Features

Dual Column Layouts:

<div style="display: flex; gap: 2rem;">
 <div style="flex: 1;">Column 1</div>
 <div style="flex: 1;">Column 2</div>
</div>

Fragment Animations:

{{< fragment >}}Appear on click!{{< /fragment >}}

Speaker Notes:

Note: Your private notes here
(visible in presenter view only)

Vertical Slide Stacks: Navigate down for sub-topics!

🚀 Getting Started is Easy

Create Your First Slide Deck in 3 Steps

Step 1: Create Your Slides

Create content/slides/my-talk/index.md:

---
title: "My Amazing Talk"
type: slides
slides:
 theme: black
---

# My Amazing Talk
### Your Name

---

## Main Points

- Point 1
- Point 2
- Point 3

---

## Thank You!

Step 2: Link to Your Event

In your event page (content/events/my-event/index.md):

---
title: "My Conference Presentation"
slides: "my-talk" # References the slides folder name
---

Step 3: Present!

Your slides are automatically:

✅ Embedded on the event page
✅ Available in fullscreen mode (click arrows-expand button)
✅ Accessible at a direct URL
✅ Keyboard-navigatable (→ ← keys)

Read Full Documentation

💎 Why Academics & Researchers Love It

Quote

“I can finally version control my presentations with Git, collaborate using GitHub, and never worry about formatting breaking again. Game changer for reproducible research!” — Dr. Xin Liu, MIT

Perfect for Research

Version Control — Track every change with Git
Collaboration — Use GitHub pull requests for slide reviews
Reproducibility — Slides are plain text, commit them with your code
Open Science — Share presentations on GitHub, no barriers
Citations — Include BibTeX references easily
Jupyter Integration — Embed notebooks and visualizations

Perfect for Teaching

Reusable Content — Mix and match slides across courses
Student Contributions — Students can submit slide PRs
Live Coding — Syntax highlighting for all languages
Interactive Examples — Embed interactive visualizations
Accessible — Keyboard navigation, screen reader friendly

🎬 See It In Action

Note

Try it now! The slides embedded above demonstrate all these features:

Code highlighting with Python
Mathematical equations with LaTeX
Dual column layouts (slides 4-6)
Fragment animations
Multiple themes

Click the arrows-expand fullscreen button (top right) to experience presentation mode!

Live Features to Try

Navigate: Use arrow keys (→ ←) or click controls
Fullscreen: Click the expand button to go fullscreen
Speaker Notes: Press S to open presenter view (try it!)
Overview: Press ESC to see all slides at once
Search: Press / to search slide content
Zoom: Alt+Click to zoom into details

external-link Open Slides in New Tab

🆚 Comparison

Feature	PowerPoint	Google Slides	Hugo Blox
Cost	$159.99/year	Free*	Free Forever
Format	Binary (`.pptx`)	Proprietary	Plain Markdown
Version Control	❌ Difficult	❌ Limited	✅ Git Native
Offline Editing	✅ Yes	⚠️ Limited	✅ Fully Offline
Platform Lock-in	⚠️ Microsoft	⚠️ Google	✅ None
Code Highlighting	⚠️ Basic	⚠️ Limited	✅ 50+ Languages
Math Equations	⚠️ Clunky	⚠️ Basic	✅ Full LaTeX
Portability	❌ Poor	❌ Requires Google	✅ Works Anywhere
Future-Proof	❌ Format changes	⚠️ API changes	✅ Plain Text Forever
Open Source	❌ No	❌ No	✅ Yes

Success

Hugo Blox wins on freedom, portability, and long-term sustainability.

🛠️ Advanced Capabilities

Code Blocks with Syntax Highlighting

import torch
import torch.nn as nn

class Transformer(nn.Module):
 def __init__(self, d_model=512, nhead=8):
 super().__init__()
 self.attention = nn.MultiheadAttention(d_model, nhead)

 def forward(self, x):
 return self.attention(x, x, x)[0]

Mathematical Equations

Display equations with LaTeX:

$$
\nabla \times \vec{E} = -\frac{\partial \vec{B}}{\partial t}
$$

$$
\int_{-\infty}^{\infty} e^{-x^2} dx = \sqrt{\pi}
$$

Dual Column Layouts

Perfect for before/after comparisons, code + explanation, or image + text:

<div style="display: flex; gap: 2rem;">
 <div style="flex: 1;">Left content</div>
 <div style="flex: 1;">Right content</div>
</div>

See slides 4-6 in the embedded presentation above for live examples!

🎓 For Educators: Teach the Future

Empower Your Students

Teaching with Hugo Blox means teaching modern, transferable skills:

Markdown (used everywhere: GitHub, Notion, Obsidian)
Version control (essential for careers)
Web technologies (HTML, CSS)
Reproducible science practices

Course Integration

courses/
├── ml-101/
│ ├── lecture-1/
│ │ ├── index.md (slides)
│ │ └── notes.md
│ ├── lecture-2/
│ │ └── index.md
│ └── _index.md

Each lecture gets its own slide deck, all version controlled, all editable by students as PRs.

🌍 Join the Community

Built by Academics, for Academics

Hugo Blox is used by researchers at:

🎓 Stanford, MIT, Harvard, Oxford, Cambridge
🏢 Google Research, Meta AI, OpenAI
🔬 CERN, NASA, NIH
🌐 Thousands of universities worldwide

Star on GitHub

Get Help & Connect

📚
💬
🐛
🐦

🚀 Ready to Create?

Start Building Beautiful Presentations Today

No installation required. No account needed. Just Markdown and your creativity.

Get Started Now

Try Lore Studio

📖 Additional Resources

Templates & Examples

Tips & Tricks

Pro Tips for Better Presentations

Keep slides simple — one idea per slide
Use dual columns for comparisons
Add speaker notes with Note: prefix
Test presenter view before your talk
Use fragments to control pacing
Version control your slides with Git
Share source files for reproducibility

Have questions? Check out the or !

Want to contribute? Hugo Blox is open source! .

Mon, 01 Jan 0001 00:00:00 +0000

Buttons

Mon, 01 Jan 0001 00:00:00 +0000

A modern, customizable button shortcode with gradient styling, icons, and smart link handling.

Basic Usage

Visit External Site

The above buttons are created with:

{{< button url="/contact" >}}Contact Us{{< /button >}}

{{< button url="https://example.com" new_tab="true" style="secondary" >}}Visit External Site{{< /button >}}

Style Variants

Primary (Default)

Primary Button

{{< button url="#" style="primary" >}}Primary Button{{< /button >}}

Secondary

Secondary Button

{{< button url="#" style="secondary" >}}Secondary Button{{< /button >}}

Outline

Outline Button

{{< button url="#" style="outline" >}}Outline Button{{< /button >}}

Ghost

Ghost Button

{{< button url="#" style="ghost" >}}Ghost Button{{< /button >}}

Sizes

Extra Large

{{< button url="#" size="sm" >}}Small Button{{< /button >}}
{{< button url="#" size="md" >}}Medium Button{{< /button >}}
{{< button url="#" size="lg" >}}Large Button{{< /button >}}
{{< button url="#" size="xl" >}}Extra Large{{< /button >}}

Alignment

Left (Default)

Left Aligned

Center

Center Aligned

Right

Right Aligned

{{< button url="#" align="left" >}}Left Aligned{{< /button >}}
{{< button url="#" align="center" >}}Center Aligned{{< /button >}}
{{< button url="#" align="right" >}}Right Aligned{{< /button >}}

With Icons

Icon Before Text

Download

Icon After Text

Continue

{{< button url="#" icon="arrow-down-tray" >}}Download{{< /button >}}
{{< button url="#" icon="arrow-right" icon_position="right" >}}Continue{{< /button >}}

Rounded Corners

Small Radius

Medium Radius (Default)

Medium Radius

Large Radius

Pill Shape

Pill Button

{{< button url="#" rounded="sm" >}}Small Radius{{< /button >}}
{{< button url="#" rounded="md" >}}Medium Radius{{< /button >}}
{{< button url="#" rounded="lg" >}}Large Radius{{< /button >}}
{{< button url="#" rounded="full" >}}Pill Button{{< /button >}}

Advanced Examples

Call-to-Action Button

Get Started Today

{{< button url="/signup" style="primary" size="lg" align="center" icon="rocket-launch" >}}Get Started Today{{< /button >}}

External Link with New Tab

View on GitHub

{{< button url="https://github.com/hugo-blox/kit" new_tab="true" style="outline" icon="arrow-top-right-on-square" icon_position="right" >}}View on GitHub{{< /button >}}

Download Button

Download PDF

{{< button url="/files/document.pdf" style="secondary" icon="document-arrow-down" rounded="full" >}}Download PDF{{< /button >}}

Parameters

Parameter	Type	Default	Description
`url`	string	`#`	Required. Button destination URL (internal or external)
`text`	string	Inner content	Button text (overrides shortcode content)
`new_tab`	boolean	`false`	Whether to open link in new tab
`style`	string	`primary`	Button style: `primary`, `secondary`, `outline`, `ghost`
`size`	string	`md`	Button size: `sm`, `md`, `lg`, `xl`
`align`	string	`left`	Button alignment: `left`, `center`, `right`
`icon`	string	-	Icon name from
`icon_position`	string	`left`	Icon position: `left`, `right`
`rounded`	string	`md`	Border radius: `sm`, `md`, `lg`, `xl`, `full`
`disabled`	boolean	`false`	Whether button should be disabled

Security Features

The button shortcode automatically handles security for external links:

External links get rel="noreferrer" attribute
External links opening in new tab get rel="noopener noreferrer"
Internal links opening in new tab get rel="noopener"

This ensures safe navigation while maintaining functionality.

Accessibility

The button shortcode includes built-in accessibility features:

Proper role="button" attribute
aria-label support
Keyboard focus indicators
High contrast focus rings
Disabled state handling

Callouts

Mon, 01 Jan 0001 00:00:00 +0000

Hugo Blox supports GitHub and Obsidian-style Markdown callouts for maximum compatibility and content portability.

Callouts are a useful feature to draw attention to important or related content such as notes, hints, or warnings in your articles.

Usage

Basic Callout Types

Hugo Blox supports all 15+ callout types from :

Information & Notes:

> [!NOTE]
> This is a note callout with important information that users should know.

Note

This is a note callout with important information that users should know.

> [!INFO]
> Alternative info callout - same styling as NOTE.

Info

Alternative info callout - same styling as NOTE.

> [!ABSTRACT]
> Use for abstracts, summaries, or TL;DR sections.

Abstract

Use for abstracts, summaries, or TL;DR sections.

Actions & Tasks:

> [!TODO]
> This is something that needs to be done.

Todo

This is something that needs to be done.

> [!TIP]
> Here's a helpful tip to make your workflow more efficient!

Tip

Here’s a helpful tip to make your workflow more efficient!

> [!SUCCESS]
> Great job! This operation completed successfully.

Success

Great job! This operation completed successfully.

Questions & Interactive:

> [!QUESTION]
> What do you think about this approach? Let us know!

Question

What do you think about this approach? Let us know!

> [!EXAMPLE]
> Here's a practical example of how to implement this feature.

Example

Here’s a practical example of how to implement this feature.

> [!QUOTE]
> "The best way to predict the future is to invent it." - Alan Kay

Quote

“The best way to predict the future is to invent it.” - Alan Kay

Warnings & Errors:

> [!WARNING]
> Be careful! This action might have unexpected consequences.

Warning

Be careful! This action might have unexpected consequences.

> [!CAUTION]
> Danger! This operation is irreversible and could cause data loss.

Caution

Danger! This operation is irreversible and could cause data loss.

> [!IMPORTANT]
> This is critical information that users must understand to proceed.

Important

This is critical information that users must understand to proceed.

> [!DANGER]
> This is extremely dangerous - proceed with extreme caution!

Danger

This is extremely dangerous - proceed with extreme caution!

> [!FAILURE]
> This operation failed. Check your configuration and try again.

Failure

This operation failed. Check your configuration and try again.

> [!BUG]
> Known issue: This feature doesn't work properly in Safari < 14.

Bug

Known issue: This feature doesn’t work properly in Safari < 14.

Custom Titles

You can customize the title of any callout:

> [!WARNING]+ Custom Warning Title
> This warning has a custom title instead of just "Warning".

Custom Warning Title

This warning has a custom title instead of just “Warning”.

Legacy Syntax (Deprecated)

The old shortcode syntax still works but shows a deprecation warning:

{{< callout note >}}
This still works but is deprecated. Use the Markdown syntax above!
{{< /callout >}}

CSS Customization

Hugo Blox generates callouts with semantic CSS classes and data attributes, making customization easy. Each callout has:

Base class: .callout
Type-specific data attribute: data-callout="note"
Component classes: .callout-icon, .callout-title, .callout-content, .callout-body

Custom CSS Example (add to your assets/css/custom.css):

/* Customize NOTE callouts */
.callout[data-callout="note"] {
 border-left-width: 8px;
 box-shadow: 0 4px 6px -1px rgb(0 0 0 / 0.1);
}

/* Make SUCCESS callouts pulse */
.callout[data-callout="success"] {
 animation: pulse 2s infinite;
}

/* Custom icon styling */
.callout-icon svg {
 transition: transform 0.2s;
}

.callout:hover .callout-icon svg {
 transform: scale(1.1);
}

/* Dark mode overrides */
@media (prefers-color-scheme: dark) {
 .callout[data-callout="warning"] {
 background-color: rgb(92 25 2);
 border-color: rgb(245 158 11);
 }
}

This approach matches , ensuring your styles work across platforms.

Benefits of the New Syntax

Portable: Works with GitHub, Obsidian, and other Markdown editors
Standard: Uses widely-adopted Markdown callout syntax
Clean: No Hugo-specific shortcodes needed
Future-proof: Supported by the latest Hugo versions (0.132.0+)
Customizable: Semantic CSS classes and data attributes for easy styling
Complete: All 15+ Obsidian callout types supported
Multilingual: Callout titles are automatically translated based on your site’s language (and can be customized in the language packs)

Cards

Mon, 01 Jan 0001 00:00:00 +0000

A Hugo extension to create cards. Cards can be shown as links or as plain text.

Usage

Learn Shortcodes A card without an icon or link

is rendered by:

{{< cards >}}
 {{< card url="../callout" title="Callout" icon="academic-cap" >}}
 {{< card url="" title="A card without an icon" >}}
{{< /cards >}}

Options

Parameter	Description
`icon`	Name of the icon. Defaults to
`title`	Title heading for the card.
`subtitle`	Subtitle heading (supports Markdown).
`url`	URL

Internationalization (i18n)

Mon, 01 Jan 0001 00:00:00 +0000

Hugo Blox enables you to easily edit the interface text as well as translating your site into multiple languages using Hugo’s feature.

View the full docs at

Spoilers

Mon, 01 Jan 0001 00:00:00 +0000

A Hugo shortcode to toggle collapsible content.

Example

Click to view the spoiler

You found me!

Markdown is supported.

Usage

{{< spoiler text="Click to view the spoiler" >}}

This is the content of the details.

Markdown is **supported**.

{{< /spoiler >}}

Steps

Mon, 01 Jan 0001 00:00:00 +0000

Display a series of steps, such as for a tutorial.

Example

Step 1

The first step here…

Step 2

The second step here…

Step 3

The third step here…

Usage

Use the Markdown level-3 headings to represent step titles within the steps shortcode:

{{% steps %}}

### Step 1

The first step here...

### Step 2

The second step here...

### Step 3

The third step here...

{{% /steps %}}

Stefano Blando

Getting Started

Quick Start from Template

Create a site

Configure your new site

Add your content

Publish your site

Next

Customizing Hugo

Project Structure

Folder Structure

Hugo File Naming Convention

Docs Navigation

Configuration

Full Documentation

Navigation

Menu

Left Sidebar

Extra Links

Right Sidebar

Presented at MARS @ ETAPS 2026

Statistical model checking of the Island Model: an established economic agent-based model of endogenous growth

Paper Accepted at MARS @ ETAPS 2026

Multi-Agent Orchestration

Interactive Explorer

RiskSentinel - Agentic Systemic Risk Simulator

RiskSentinel for Microsoft AI Dev Days 2026

Island Model + MultiVeStA — Statistical Model Checking of Economic Growth

What the Model Does

What MultiVeStA Adds

Interactive Explorer

Robust Portfolio Optimization under Systematic Market Disruptions (PFSE)

Key Results

Interactive Explorer

PokéNexus

Master Graduation

The Thesis

A Multi-Method Validation Framework for Large-Scale Multilingual Text Analytics

Network Topology Analysis and Machine Learning Techniques for Systemic Risk Prediction in U.S. Equity Markets

Network Topology Analysis for Systemic Risk Prediction

NLP & Semantic Network Analysis

Advanced Recommender System

High-dimensional Robust Portfolio Optimization Under Contamination: A Factor-Analytic Approach

Real Estate AI Agent

Lightweight Fine-Tuning with PEFT & LoRA

Gas Network Risk Forecasting

AI Photo Editor with SAM & SDXL

Custom Chatbot with RAG

Example Talk: Recent Work

Example Talk

Dr. Alex Johnson · Meta AI

Research Overview

Code & Math

Dual Column Layout

Left Column

Right Column

Main Content (2/3 width)

Sidebar (1/3 width)

Image + Text Layout

Results

Speaker Notes

Progressive Reveals

Diagrams with Mermaid

Research Results

Custom Backgrounds

Vertical Navigation

Substep 1: Details

Substep 2: More Details

Citations & Quotes

Media: YouTube Videos

Media: All Options

Interactive Elements

Hidden Slide Demo (Inline Comment)

Thanks

Questions?

🎨 Branding Your Slides

📁 Adding Your Logo

📝 Title & Author Overlays

📄 Footer Text

🔇 Hiding Branding Per-Slide