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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" />
<title>SIMLab – Scientific and Industrial Machine Learning Laboratory</title>
<link rel="preload" as="image" href="assets/banner.webp" fetchpriority="high" />
<style>
:root {
--accent: #2563eb;
--accent-light: #dbeafe;
--text: #1e293b;
--muted: #64748b;
--bg: #f8fafc;
--card-bg: #ffffff;
--border: #e2e8f0;
}
* { box-sizing: border-box; margin: 0; padding: 0; }
body {
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif;
background: var(--bg);
color: var(--text);
line-height: 1.7;
}
/* ── Header ── */
header {
background: #123c4d url('assets/banner.webp') center/cover no-repeat;
color: #fff;
padding: 5rem 1.5rem 4rem;
text-align: center;
}
header .logo {
display: inline-block;
font-size: 0.85rem;
font-weight: 600;
letter-spacing: 0.18em;
text-transform: uppercase;
color: #93c5fd;
margin-bottom: 1rem;
}
header h1 {
font-size: clamp(2rem, 5vw, 3.25rem);
font-weight: 800;
letter-spacing: -0.02em;
line-height: 1.15;
max-width: 820px;
margin: 0 auto 1.25rem;
}
header h1 span { color: #60a5fa; }
p.tagline {
font-size: 1.15rem;
color: var(--accent-light);
max-width: 600px;
margin: 0 auto;
text-align: center;
padding: 1.75rem 1.5rem 0;
}
header .affiliation {
display: inline-block;
background: rgba(255,255,255,0.08);
border: 1px solid rgba(255,255,255,0.15);
border-radius: 2rem;
padding: 0.45rem 1.1rem;
font-size: 0.9rem;
color: #94a3b8;
}
header .affiliation a {
color: #93c5fd;
text-decoration: none;
}
header .affiliation a:hover { text-decoration: underline; }
/* ── Logos ── */
.header-logos {
display: flex;
align-items: center;
justify-content: center;
gap: 2rem;
margin-bottom: 2.5rem;
flex-wrap: wrap;
}
.logo-simlab {
height: 80px;
width: auto;
}
.logo-hevs {
height: 36px;
width: auto;
opacity: 0.9;
filter: brightness(0) invert(1);
}
/* ── Layout ── */
main {
max-width: 1080px;
margin: 0 auto;
padding: 4rem 1.5rem 6rem;
}
/* ── Section headings ── */
.section-label {
font-size: 0.78rem;
font-weight: 700;
letter-spacing: 0.14em;
text-transform: uppercase;
color: var(--accent);
margin-bottom: 0.6rem;
}
h2 {
font-size: 1.85rem;
font-weight: 700;
letter-spacing: -0.01em;
margin-bottom: 1rem;
}
/* ── Intro ── */
.intro {
max-width: 700px;
margin-bottom: 4rem;
}
.intro p {
font-size: 1.1rem;
color: var(--muted);
}
/* ── Research areas grid ── */
.areas-grid {
display: grid;
grid-template-columns: repeat(auto-fill, minmax(300px, 1fr));
gap: 1.25rem;
margin-top: 1.75rem;
}
.card {
background: var(--card-bg);
border: 1px solid var(--border);
border-radius: 12px;
padding: 1.75rem;
transition: box-shadow 0.2s, transform 0.2s;
}
.card:hover {
box-shadow: 0 8px 30px rgba(0,0,0,0.08);
transform: translateY(-2px);
}
.card-icon {
width: 40px;
height: 40px;
border-radius: 10px;
background: var(--accent-light);
display: flex;
align-items: center;
justify-content: center;
margin-bottom: 1rem;
font-size: 1.25rem;
}
.card h3 {
font-size: 1.05rem;
font-weight: 700;
margin-bottom: 0.5rem;
}
.card p {
font-size: 0.9rem;
color: var(--muted);
line-height: 1.65;
}
.card .tools {
margin-top: 0.9rem;
display: flex;
flex-wrap: wrap;
gap: 0.4rem;
}
.tag {
background: var(--accent-light);
color: var(--accent);
font-size: 0.76rem;
font-weight: 600;
padding: 0.2rem 0.6rem;
border-radius: 999px;
text-decoration: none;
transition: background 0.15s;
}
.tag:hover { background: #bfdbfe; }
/* ── Philosophy strip ── */
.philosophy {
margin-top: 4rem;
background: linear-gradient(135deg, #eff6ff, #f0fdf4);
border: 1px solid #bfdbfe;
border-radius: 16px;
padding: 2.5rem 2rem;
display: flex;
align-items: flex-start;
gap: 1.5rem;
}
.philosophy .icon {
font-size: 2rem;
flex-shrink: 0;
}
.philosophy h3 {
font-size: 1.15rem;
font-weight: 700;
margin-bottom: 0.4rem;
}
.philosophy p {
font-size: 0.95rem;
color: var(--muted);
}
/* ── Footer ── */
footer {
text-align: center;
padding: 2rem 1rem;
font-size: 0.85rem;
color: var(--muted);
border-top: 1px solid var(--border);
}
footer a {
color: var(--accent);
text-decoration: none;
}
footer a:hover { text-decoration: underline; }
@media (max-width: 600px) {
.philosophy { flex-direction: column; gap: 0.75rem; }
}
/* ── DB sections shared ── */
.db-section {
margin-top: 5rem;
}
/* ── Badges ── */
.badges { display: flex; flex-wrap: wrap; gap: 0.4rem; }
.badge {
font-size: 0.72rem;
font-weight: 700;
letter-spacing: 0.04em;
text-transform: uppercase;
padding: 0.2rem 0.65rem;
border-radius: 999px;
}
.badge-status.ongoing { background: #dcfce7; color: #166534; }
.badge-status.completed { background: #f1f5f9; color: #475569; }
/* ── Projects list ── */
.proj-list {
display: flex;
flex-direction: column;
gap: 1rem;
margin-top: 1.75rem;
}
.proj-card {
background: var(--card-bg);
border: 1px solid var(--border);
border-radius: 12px;
padding: 1.5rem 1.75rem;
transition: box-shadow 0.2s;
}
.proj-card:hover { box-shadow: 0 6px 24px rgba(0,0,0,0.07); }
.proj-header {
display: flex;
align-items: flex-start;
justify-content: space-between;
gap: 1rem;
flex-wrap: wrap;
margin-bottom: 0.5rem;
}
.proj-header h3 {
font-size: 1.05rem;
font-weight: 700;
flex: 1;
}
.proj-meta {
font-size: 0.83rem;
color: var(--muted);
margin-bottom: 0.6rem;
}
.proj-meta .partners {
color: var(--muted);
}
.proj-desc {
font-size: 0.9rem;
color: var(--muted);
line-height: 1.65;
margin-bottom: 0.75rem;
}
.proj-link {
font-size: 0.83rem;
font-weight: 600;
color: var(--accent);
text-decoration: none;
}
.proj-link:hover { text-decoration: underline; }
.proj-link-sep { color: var(--border); }
.collab-link {
font-size: 0.83rem;
font-weight: 600;
color: var(--accent);
text-decoration: none;
}
.collab-link:hover { text-decoration: underline; }
.collab-links { margin-top: 0.5rem; }
/* ── Alumni list ── */
.alumni-list {
display: flex;
flex-wrap: wrap;
gap: 0.6rem 1rem;
margin-top: 1.5rem;
padding: 0;
list-style: none;
}
.alumni-list li {
background: var(--card-bg);
border: 1px solid var(--border);
border-radius: 999px;
padding: 0.45rem 1.1rem;
font-size: 0.9rem;
}
.alumni-list a {
color: var(--text);
text-decoration: none;
font-weight: 600;
}
.alumni-list a:hover { color: var(--accent); text-decoration: underline; }
.alumni-list span { color: var(--text); font-weight: 600; }
/* ── Collaborators grid ── */
.collab-grid {
display: grid;
grid-template-columns: 1fr;
gap: 1.25rem;
margin-top: 1.75rem;
}
.collab-card {
background: var(--card-bg);
border: 1px solid var(--border);
border-radius: 12px;
padding: 1.5rem;
display: flex;
gap: 1.1rem;
align-items: flex-start;
transition: box-shadow 0.2s;
}
.collab-card:hover { box-shadow: 0 6px 24px rgba(0,0,0,0.07); }
.collab-avatar {
width: 110px;
height: 110px;
border-radius: 50%;
background: linear-gradient(135deg, #2563eb, #7c3aed);
color: #fff;
font-size: 1.4rem;
font-weight: 700;
display: flex;
align-items: center;
justify-content: center;
flex-shrink: 0;
}
.collab-photo {
width: 110px;
height: 110px;
border-radius: 50%;
object-fit: cover;
flex-shrink: 0;
border: 2px solid var(--border);
}
.collab-body {
min-width: 0;
}
.collab-body h3 {
font-size: 1rem;
font-weight: 700;
margin-bottom: 0.2rem;
}
.collab-body h3 a {
color: inherit;
text-decoration: none;
}
.collab-body h3 a:hover { color: var(--accent); }
.collab-subtitle {
font-size: 0.8rem;
color: var(--muted);
margin-top: 0.4rem;
margin-bottom: 0.4rem;
}
.collab-interests {
display: flex;
flex-wrap: wrap;
gap: 0.3rem;
margin-top: 0.35rem;
margin-bottom: 0;
}
.interest-tag {
font-size: 0.71rem;
font-weight: 500;
background: var(--accent-light);
color: var(--accent);
padding: 0.15rem 0.55rem;
border-radius: 99px;
}
.collab-bio {
font-size: 0.85rem;
color: var(--muted);
line-height: 1.6;
margin-top: 0.5rem;
margin-bottom: 0;
}
.collab-bio-list {
font-size: 0.85rem;
color: var(--muted);
line-height: 1.6;
margin: 0.5rem 0 0 1.1rem;
padding: 0;
}
.collab-bio-list li { margin-bottom: 0.2rem; }
.collab-bio a,
.collab-bio-list a {
color: var(--accent);
text-decoration: none;
}
.collab-bio a:hover,
.collab-bio-list a:hover { text-decoration: underline; }
</style>
</head>
<body>
<header>
<div class="header-logos">
<img src="assets/logo-simlab.png" alt="SIMLab" class="logo-simlab" />
<img src="assets/logo-hevs.svg" alt="HES-SO Valais-Wallis" class="logo-hevs" />
</div>
<h1>Scientific and Industrial<br><span>Machine Learning</span> Laboratory</h1>
<p class="tagline">
Developing and applying machine learning techniques to solve complex real-world problems.
</p>
</header>
<main>
<!-- About -->
<section class="intro">
<div class="section-label">About</div>
<h2>Who we are</h2>
<p>
SIMLab works in close collaboration with academic and industrial partners, with a strong emphasis
on practical applications and ensuring the real-world impact of our research.
</p>
</section>
<!-- Research areas -->
<section>
<div class="section-label">Research</div>
<h2>Core Areas</h2>
<div class="areas-grid">
<div class="card">
<div class="card-icon">∂</div>
<h3>Differential Programming</h3>
<p>
We heavily rely on general differentiable programs, enabling the integration of domain knowledge
and complex structures into learning models.
</p>
<div class="tools">
<a class="tag" href="https://jax.readthedocs.io/en/latest/" target="_blank" rel="noopener">JAX</a>
<a class="tag" href="https://flax.readthedocs.io/en/latest/" target="_blank" rel="noopener">Flax</a>
</div>
</div>
<div class="card">
<div class="card-icon">⚡</div>
<h3>Advanced Data Processing</h3>
<p>
Handling large-scale and complex datasets using state-of-the-art technologies, scaling pipelines
to very large-scale datasets.
</p>
<div class="tools">
<a class="tag" href="https://pola.rs" target="_blank" rel="noopener">Polars</a>
</div>
</div>
<div class="card">
<div class="card-icon">⚗️</div>
<h3>Hybrid Modeling</h3>
<p>
Combining data-driven approaches with traditional simulations using differential programming
methods, leveraging the strengths of both for more accurate and reliable predictions.
</p>
</div>
<div class="card">
<div class="card-icon">~</div>
<h3>Uncertainty Quantification</h3>
<p>
Developing techniques to assess and manage uncertainty in machine learning models, enhancing
their robustness and reliability in real-world deployments.
</p>
</div>
<div class="card">
<div class="card-icon">〰</div>
<h3>Dynamical Systems</h3>
<p>
Developing methods for analyzing, modelling, and forecasting complex dynamical systems, with
applications in energy and environmental monitoring.
</p>
<div class="tools">
<a class="tag" href="https://docs.kidger.site/diffrax/" target="_blank" rel="noopener">Diffrax</a>
<a class="tag" href="https://optax.readthedocs.io/en/latest/" target="_blank" rel="noopener">Optax</a>
</div>
</div>
<div class="card">
<div class="card-icon">🔍</div>
<h3>Explainable AI (XAI)</h3>
<p>
Developing machine learning models that are transparent and interpretable, allowing users to
understand and trust the decisions made by these models.
</p>
<div class="tools">
<a class="tag" href="https://shap.readthedocs.io/en/latest/" target="_blank" rel="noopener">SHAP</a>
</div>
</div>
</div>
</section>
<!-- Philosophy -->
<div class="philosophy">
<div class="icon">🎯</div>
<div>
<h3>Real-world impact first</h3>
<p>
We bridge the gap between cutting-edge ML research and industrial practice. Every project
we undertake is driven by the goal of delivering measurable, practical impact for our partners.
</p>
</div>
</div>
<!-- BEGIN:projects -->
<section class="db-section" id="projects">
<div class="section-label">Projects</div>
<h2>Research Projects</h2>
<div class="proj-list">
<div class="proj-card">
<div class="proj-header">
<h3>AI4SWEng – AI-Driven Software Engineering</h3>
<div class="badges"><span class="badge" style="background:#dbeafe;color:#1d4ed8">Horizon</span><span class="badge badge-status ongoing">ongoing</span></div>
</div>
<div class="proj-meta"><span>2025–2028</span></div>
<p class="proj-desc">European research project investigating how large language models and AI agents can
assist and automate software engineering tasks, from requirements analysis and code
generation to testing and maintenance. SIMLab contributes expertise in hybrid modelling
and uncertainty quantification for AI-assisted development pipelines.</p>
<a class="proj-link" href="https://ai4sweng.eu/" target="_blank" rel="noopener">Project website →</a>
</div>
<div class="proj-card">
<div class="proj-header">
<h3>CAPIA – AI-Based Cutting Tool Precision Control</h3>
<div class="badges"><span class="badge" style="background:#fef3c7;color:#92400e">Innosuisse</span><span class="badge badge-status ongoing">ongoing</span></div>
</div>
<div class="proj-meta"><span>2026–2027</span> · <span class="partners">Eskenazi SA</span></div>
<p class="proj-desc">Contrôle Autonome de la Précision des outils de coupe par Intelligence Artificielle.
Innosuisse project with Eskenazi SA developing real-time machine-learning models for
in-process monitoring and automatic correction of cutting-tool precision, reducing scrap
rates and improving surface quality in high-precision machining.</p>
<a class="proj-link" href="https://www.eskenazi.ch" target="_blank" rel="noopener">Project website →</a>
</div>
<div class="proj-card">
<div class="proj-header">
<h3>JAXifer – Groundwater Level Forecasting</h3>
<div class="badges"><span class="badge" style="background:#f3f4f6;color:#374151">Etat du Valais</span><span class="badge badge-status ongoing">ongoing</span></div>
</div>
<div class="proj-meta"><span>2023–2025</span></div>
<p class="proj-desc">A JAX-based framework for 5-day groundwater level prediction from meteorological and
weather forecast data. Uses differentiable hybrid models combining physics-based priors
with data-driven components, enabling uncertainty-aware forecasts at regional scale.</p>
<a class="proj-link" href="https://github.com/simlab-vs/jaxifer" target="_blank" rel="noopener">GitHub →</a>
</div>
<div class="proj-card">
<div class="proj-header">
<h3>ML4HYDRO – Machine Learning for Hydroelectric Turbine Simulations</h3>
<div class="badges"><span class="badge" style="background:#f3e8ff;color:#6b21a8">HES-SO</span><span class="badge badge-status ongoing">ongoing</span></div>
</div>
<div class="proj-meta"><span>2026</span></div>
<p class="proj-desc">Domain-informed machine learning for the simulation of hydroelectric turbines. The
project develops physics-constrained surrogate models that accurately replicate
high-fidelity CFD simulations at a fraction of the computational cost, enabling rapid
turbine optimisation and digital-twin applications for Swiss hydropower operators.</p>
</div>
<div class="proj-card">
<div class="proj-header">
<h3>Sovereign Spearphishing Detection</h3>
<div class="badges"><span class="badge" style="background:#fef3c7;color:#92400e">Innosuisse</span><span class="badge badge-status ongoing">ongoing</span></div>
</div>
<div class="proj-meta"><span>2026–2027</span> · <span class="partners">Infomaniak</span></div>
<p class="proj-desc">Innosuisse project with Infomaniak developing a sovereign, open-source solution for
automated spearphishing detection. The system combines large language models with
behavioural analysis to identify highly targeted email attacks without relying on
third-party cloud infrastructure, addressing privacy and data-sovereignty requirements
for Swiss organisations.</p>
</div>
<div class="proj-card">
<div class="proj-header">
<h3>TrunX – Domain-Informed Tree Growth and Mortality Modelling</h3>
<div class="badges"><span class="badge" style="background:#d1fae5;color:#065f46">SNSF</span><span class="badge badge-status ongoing">ongoing</span></div>
</div>
<div class="proj-meta"><span>2026</span></div>
<p class="proj-desc">SNSF Spark project developing domain-informed system-dynamics models of tree growth and
mortality under changing climatic conditions. Combines differentiable mechanistic
representations of carbon allocation and hydraulic failure with observational data to
produce interpretable, uncertainty-aware forecasts of forest dynamics.</p>
<a class="proj-link" href="https://github.com/simlab-vs/trunx" target="_blank" rel="noopener">GitHub →</a>
</div>
</div>
</section>
<!-- END:projects -->
<!-- BEGIN:collaborators -->
<section class="db-section" id="team">
<div class="section-label">People</div>
<h2>Team</h2>
<div class="collab-grid">
<div class="collab-card">
<img class="collab-photo" src="https://www.gravatar.com/avatar/1404483460349bbf8ed2f55cfcee2c64?s=200&d=mp" alt="GM" />
<div class="collab-body">
<h3><a href="https://gregorymermoud.ch" target="_blank" rel="noopener">Prof. Dr. Gregory Mermoud</a></h3>
<div class="collab-interests"><span class="interest-tag">Hybrid Modeling</span><span class="interest-tag">Differential Programming</span><span class="interest-tag">Uncertainty Quantification</span><span class="interest-tag">Dynamical Systems</span></div>
<div class="collab-subtitle">Director</div>
<p class="collab-bio">Gregory Mermoud is a professor at HES-SO Valais-Wallis and director of SIMLab. His research focuses on the intersection of physics-based modeling and machine learning, with an emphasis on developing interpretable and uncertainty-aware models for real-world engineering problems.</p>
<div class="collab-links"><a class="collab-link" href="https://gregorymermoud.ch" target="_blank" rel="noopener">Website →</a> · <a class="collab-link" href="https://scholar.google.com/citations?hl=en&user=HzVpPHwAAAAJ" target="_blank" rel="noopener">Portfolio →</a></div>
</div>
</div>
<div class="collab-card">
<div class="collab-avatar">CT</div>
<div class="collab-body">
<h3><a href="https://cedrictravelletti.github.io/" target="_blank" rel="noopener">Dr. Cedric Travelletti</a></h3>
<div class="collab-interests"><span class="interest-tag">Gaussian Processes</span><span class="interest-tag">Spatial Statistics</span><span class="interest-tag">Inverse Problems</span><span class="interest-tag">Geosciences</span></div>
<div class="collab-subtitle">Senior Scientist</div>
<p class="collab-bio">Cedric Travelletti is a senior scientist at SIMLab specialising in probabilistic machine learning and spatial statistics. His work addresses inverse problems in geosciences, with a focus on scalable Gaussian process methods and uncertainty quantification for large-scale environmental applications.</p>
<div class="collab-links"><a class="collab-link" href="https://cedrictravelletti.github.io/" target="_blank" rel="noopener">Website →</a></div>
</div>
</div>
<div class="collab-card">
<img class="collab-photo" src="https://www.gravatar.com/avatar/92e4f311a9403e027f54a26c88434194?s=200&d=mp" alt="GM" />
<div class="collab-body">
<h3>Dr. Glory Mary Givi</h3>
<div class="collab-interests"><span class="interest-tag">Machine Learning</span><span class="interest-tag">Explainable AI</span><span class="interest-tag">Scientific Computing</span><span class="interest-tag">Dynamical Systems</span></div>
<div class="collab-subtitle">Post doctoral researcher</div>
<p class="collab-bio">Glory is a postdoctoral researcher developing domain-informed machine learning models to predict tree growth and mortality under changing climatic conditions. Her work integrates ecological, physiological, and remote sensing data within differentiable modeling frameworks to capture complex, non-linear interactions between climate stressors and forest ecosystems.</p>
<div class="collab-links"><a class="collab-link" href="https://scholar.google.com/citations?user=ujG151oAAAAJ&hl=en" target="_blank" rel="noopener">Portfolio →</a></div>
</div>
</div>
<div class="collab-card">
<img class="collab-photo" src="https://www.gravatar.com/avatar/c12f3f4cc84869eece32ecd88d54a0d9?s=200&d=mp" alt="MG" />
<div class="collab-body">
<h3><a href="https://gillioz.github.io/" target="_blank" rel="noopener">Dr. Marc Gillioz</a></h3>
<div class="collab-interests"><span class="interest-tag">Physics-Informed ML</span><span class="interest-tag">Time Series</span><span class="interest-tag">Industrial Applications</span></div>
<div class="collab-subtitle">Senior scientist</div>
<p class="collab-bio">Marc is a senior scientist applying machine learning solutions to problems that involve physics. His background is in high-energy physics, with a stint in software engineering. At the HES-SO, he has worked mainly on electrical grids and hydroelectric power production.</p>
<div class="collab-links"><a class="collab-link" href="https://gillioz.github.io/" target="_blank" rel="noopener">Website →</a></div>
</div>
</div>
<div class="collab-card">
<img class="collab-photo" src="https://www.gravatar.com/avatar/53f0f2a281f7b52a95434be912019135?s=200&d=mp" alt="AV" />
<div class="collab-body">
<h3>Alexandre Veuthey</h3>
<div class="collab-interests"><span class="interest-tag">Machine Learning</span><span class="interest-tag">Computer Vision</span><span class="interest-tag">Computer Graphics</span></div>
<div class="collab-subtitle">Research Engineer</div>
<p class="collab-bio">Alexandre Veuthey is a research engineer whose work at HES-SO and SIMLab focuses on the practical applications of Machine Learning for Computer Vision, particularly at the intersection of the 2D and 3D vision modalities. His prior experience in an industrial context enables data-driven solutions for vision tools based on cameras and other sensors.</p>
</div>
</div>
<div class="collab-card">
<div class="collab-avatar">MR</div>
<div class="collab-body">
<h3>Marta Rende</h3>
<div class="collab-subtitle">Assistant</div>
</div>
</div>
<div class="collab-card">
<img class="collab-photo" src="https://www.gravatar.com/avatar/ddc70699c7c2f1b05b3ea69ff0b10836?s=200&d=mp" alt="FR" />
<div class="collab-body">
<h3>Dr. Francesco Rubbo</h3>
<div class="collab-interests"><span class="interest-tag">Applied ML</span><span class="interest-tag">ML for Cell Biology</span><span class="interest-tag">Representation Learning</span><span class="interest-tag">Hierarchical Modeling</span></div>
<div class="collab-subtitle">Scientific Collaborator</div>
<div class="collab-links"><a class="collab-link" href="https://scholar.google.com/citations?hl=en&user=iPfDBYkAAAAJ" target="_blank" rel="noopener">Portfolio →</a></div>
</div>
</div>
<div class="collab-card">
<img class="collab-photo" src="https://www.gravatar.com/avatar/1ee41740c3713060def27a649cdd7550?s=200&d=mp" alt="AT" />
<div class="collab-body">
<h3>Ambrus Tóth</h3>
<div class="collab-interests"><span class="interest-tag">Programming Language Design (memory safety)</span><span class="interest-tag">Compilers</span><span class="interest-tag">Tool Development.</span></div>
<div class="collab-subtitle">Research Assistant</div>
<div class="collab-links"><a class="collab-link" href="https://scholar.google.com/citations?hl=en&user=ap5D9IUAAAAJ" target="_blank" rel="noopener">Portfolio →</a></div>
</div>
</div>
<div class="collab-card">
<img class="collab-photo" src="https://www.gravatar.com/avatar/a2170c5a7e006bac1419b7a7ef6be632?s=200&d=mp" alt="LT" />
<div class="collab-body">
<h3>Dr. Lucien Troillet</h3>
<div class="collab-interests"><span class="interest-tag">ML techniques for environmental issues</span></div>
<div class="collab-subtitle">Scientific Collaborator</div>
<p class="collab-bio">Lucien is a researcher focusing on using ML techniques to environmental problems. His Master is in Environmental Science and his PhD is in AI applied to games. He has also worked in Medical Information Science. In HES-SO, Lucien first worked for the Sustainable Energy Territory Team before joining the SIMLab team in August 2026.</p>
</div>
</div>
</div>
</section>
<!-- END:collaborators -->
<!-- BEGIN:alumni -->
<section class="db-section" id="alumni">
<div class="section-label">People</div>
<h2>Alumni</h2>
<ul class="alumni-list">
<li><a href="https://dionosmani.vercel.app/" target="_blank" rel="noopener">Dion Osmani</a></li>
<li><a href="https://www.linkedin.com/in/hiten-goel-003599250/" target="_blank" rel="noopener">Hiten Goel</a></li>
</ul>
</section>
<!-- END:alumni -->
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