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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>Teaching — Emile Djohi</title>
<link rel="stylesheet" href="css/style.css"/>
</head>
<body>
<nav>
<div class="nav-inner">
<a href="index.html" class="nav-brand">Emile <span>Djohi</span></a>
<ul class="nav-links">
<li><a href="index.html">Home</a></li>
<li><a href="research.html">Research</a></li>
<li><a href="talks.html">Talks</a></li>
<li><a href="teaching.html" class="active">Teaching</a></li>
<li><a href="cv.html">CV</a></li>
</ul>
<div class="hamburger"><span></span><span></span><span></span></div>
</div>
</nav>
<div class="page-hero">
<div class="page-hero-inner">
<div class="section-label">Pedagogy</div>
<h1>Teaching Experience</h1>
<p>Teaching assistant roles and course support in quantitative economics, econometrics, and computational methods at the African School of Economics.</p>
</div>
</div>
<section>
<div class="section-inner">
<div class="section-label">African School of Economics</div>
<h2 class="section-title">Courses <em>Taught</em></h2>
<p class="section-sub">Supported instruction across graduate and advanced undergraduate courses in mathematics, economics, and computational methods. Assisted students with empirical research design, data analysis, and reproducible workflows.</p>
<div class="teaching-grid fade-up">
<div class="teaching-card">
<div class="teaching-card-head">
<h3>Quantitative Economics</h3>
<span>Summer 2023, 2024</span>
</div>
<div class="teaching-card-body">
Thomas Sargent, John Stachurski & Matt McKay. Covered Python-based computational economics, dynamic programming, and quantitative modeling techniques used in modern macroeconomics research.
</div>
</div>
<div class="teaching-card">
<div class="teaching-card-head">
<h3>Computational & Algorithmic Methods (R)</h3>
<span>Fall 2023, Spring 2024</span>
</div>
<div class="teaching-card-body">
Gabor Nyéki (Princeton) & Zimé Songbian. Algorithmic problem-solving and statistical computing in R, including data wrangling, simulation, and reproducible workflow design for applied social science research.
</div>
</div>
<div class="teaching-card">
<div class="teaching-card-head">
<h3>Computational & Algorithmic Methods (Python)</h3>
<span>Fall 2023, Spring 2024</span>
</div>
<div class="teaching-card-body">
Python-based algorithmic methods covering data structures, numerical computation, and applications to economic modeling, statistical inference, and geospatial analysis.
</div>
</div>
<div class="teaching-card">
<div class="teaching-card-head">
<h3>Econometrics</h3>
<span>2024</span>
</div>
<div class="teaching-card-body">
Tamoghna Hader. Applied econometric theory and practice: OLS, IV, panel data, difference-in-differences, and causal inference methods. Supported lab sessions in Stata and R.
</div>
</div>
<div class="teaching-card">
<div class="teaching-card-head">
<h3>Numerical Analysis</h3>
<span>Spring 2023</span>
</div>
<div class="teaching-card-body">
Guy Degla. Numerical methods for mathematics and economics: root-finding, interpolation, numerical integration and differentiation, and optimization algorithms with applications in economics.
</div>
</div>
<div class="teaching-card">
<div class="teaching-card-head">
<h3>Mathematics for Economics</h3>
<span>Fall 2023</span>
</div>
<div class="teaching-card-body">
Guy Degla. Mathematical foundations for economic analysis: real analysis, topology, optimization, and fixed-point theorems, with applications to consumer and producer theory.
</div>
</div>
<div class="teaching-card">
<div class="teaching-card-head">
<h3>Linear Algebra</h3>
<span>Spring 2023</span>
</div>
<div class="teaching-card-body">
Jonas Doumate. Linear algebra for economics and statistics: vector spaces, linear transformations, matrix decompositions (eigenvalues, SVD), and applications to econometrics and optimization.
</div>
</div>
</div>
<div style="margin-top: 4rem; padding: 2.5rem; border: 1px solid var(--border); background: var(--white);">
<div class="section-label" style="margin-bottom:1rem">Teaching Philosophy</div>
<p style="font-size:0.95rem; color:var(--text-muted); line-height:1.8; max-width:700px;">
I believe rigorous quantitative training should be grounded in real empirical problems. My approach emphasizes reproducible workflows, intuition-building alongside formal methods, and close mentoring of students through their own research designs — particularly in data-scarce contexts where methodological choices carry significant weight.
</p>
</div>
</div>
</section>
<footer>© 2026 Emile Honaminto Virgile Djohi · University of Pennsylvania</footer>
<script src="js/main.js"></script>
</body>
</html>