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# Curriculum vitea

I am currently a postdoctoral researcher at the KERMIT (knowledge-based systems) and Biobix (bioinformatics) groups at Ghent University. Machine intelligence and living systems fascinate me. In my research, I develop intelligent techniques to understand, predict, and control biological systems, large and small. My main toolbox involves a mix of machine learning, optimization, bioinformatics, and graph theory. I use these methods to predict how plants, animals, microorganisms, and molecules interact with each other. Much of my work involves working together with others, translating biological problems as mathematical or computational ones. Every year, I try to engage students in projects and theses, doing cool things such as making a beer classifier or designing new proteins. During my years as a teaching assistant, I taught various courses on data analytics and computational intelligence, including statistics, probability theory, and machine learning. Now, I am the responsible teacher for the class *Selected Topics in Mathematical Optimization*, teaching master students of bioinformatics how to solve concrete problems. Throughout all my activities, I value creativity and collaborating with people from different fields to develop highly innovative ideas.
I am currently an assistant professor at the KERMIT (knowledge-based systems) and Biobix (bioinformatics) groups at Ghent University. Machine intelligence and living systems fascinate me. In my research, I develop intelligent techniques to understand, predict, and control biological systems, large and small. My main toolbox involves a mix of machine learning, optimization, bioinformatics, and graph theory. I use these methods to predict how plants, animals, microorganisms, and molecules interact with each other. Much of my work involves working together with others, translating biological problems as mathematical or computational ones. Every year, I try to engage students in projects and theses, doing cool things such as making a beer classifier or designing new proteins. During my years as a teaching assistant, I taught various courses on data analytics and computational intelligence, including statistics, probability theory, and machine learning. Now, I am the responsible teacher for the *Differential Equations* courses for bioscience engineers. Throughout all my activities, I value creativity and collaborating with people from different fields to develop highly innovative ideas.

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<h1 id="curriculum_vitea"><a href="#curriculum_vitea" class="header-anchor">Curriculum vitea</a></h1>
<p>I am currently a postdoctoral researcher at the KERMIT &#40;knowledge-based systems&#41; and Biobix &#40;bioinformatics&#41; groups at Ghent University. Machine intelligence and living systems fascinate me. In my research, I develop intelligent techniques to understand, predict, and control biological systems, large and small. My main toolbox involves a mix of machine learning, optimization, bioinformatics, and graph theory. I use these methods to predict how plants, animals, microorganisms, and molecules interact with each other. Much of my work involves working together with others, translating biological problems as mathematical or computational ones. Every year, I try to engage students in projects and theses, doing cool things such as making a beer classifier or designing new proteins. During my years as a teaching assistant, I taught various courses on data analytics and computational intelligence, including statistics, probability theory, and machine learning. Now, I am the responsible teacher for the class <em>Selected Topics in Mathematical Optimization</em>, teaching master students of bioinformatics how to solve concrete problems. Throughout all my activities, I value creativity and collaborating with people from different fields to develop highly innovative ideas.</p>
<p>I am currently an assistant professor at the KERMIT &#40;knowledge-based systems&#41; and Biobix &#40;bioinformatics&#41; groups at Ghent University. Machine intelligence and living systems fascinate me. In my research, I develop intelligent techniques to understand, predict, and control biological systems, large and small. My main toolbox involves a mix of machine learning, optimization, bioinformatics, and graph theory. I use these methods to predict how plants, animals, microorganisms, and molecules interact with each other. Much of my work involves working together with others, translating biological problems as mathematical or computational ones. Every year, I try to engage students in projects and theses, doing cool things such as making a beer classifier or designing new proteins. During my years as a teaching assistant, I taught various courses on data analytics and computational intelligence, including statistics, probability theory, and machine learning. Now, I am the responsible teacher for the <em>Differential Equations</em> courses for bioscience engineers. Throughout all my activities, I value creativity and collaborating with people from different fields to develop highly innovative ideas.</p>
<div class="franklin-toc"><ol><li><a href="#education_and_work_experience">Education and work experience</a></li><li><a href="#teaching_experience">Teaching experience</a></li><li><a href="#publications">Publications</a></li></ol></div>
<h2 id="education_and_work_experience"><a href="#education_and_work_experience" class="header-anchor">Education and work experience</a></h2>
<ul>
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<p>See <a href="https://scholar.google.be/citations?user&#61;qR_LXM8AAAAJ&amp;hl&#61;en">Google Scholar</a>.</p>
<div class="page-foot">
<div class="copyright">
&copy; Michiel Stock. Last modified: February 02, 2022. Website built with <a href="https://github.com/tlienart/Franklin.jl">Franklin.jl</a> and the <a href="https://julialang.org">Julia programming language</a>.
&copy; Michiel Stock. Last modified: September 20, 2023. Website built with <a href="https://github.com/tlienart/Franklin.jl">Franklin.jl</a> and the <a href="https://julialang.org">Julia programming language</a>.
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UndefVarError: Z100 not defined
Failed to precompile Plots [91a5bcdd-55d7-5caf-9e0b-520d859cae80] to "/Users/michielstock/.julia/compiled/v1.9/Plots/jl_vLvKWF".
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4 changes: 3 additions & 1 deletion __site/blog/index.html
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Expand Up @@ -61,6 +61,8 @@ <h2 id="posts_by_tag"><a href="#posts_by_tag" class="header-anchor">Posts by tag
</li>
</ul>
<h2 id="posts_by_year"><a href="#posts_by_year" class="header-anchor">Posts by year</a></h2>
<h3 id="2023"><a href="#2023" class="header-anchor">2023</a></h3>
<p><a href="/posts/2023/2023-09-20-thinking_in_systems/">📚Thinking in Systems: A Primer</a></p>
<h3 id="2022"><a href="#2022" class="header-anchor">2022</a></h3>
<p><a href="/posts/2022/2022-02-01-mindstorms/">📚Mindstorms: Children, Computers, And Powerful Ideas</a></p>
<p><a href="/posts/2022/2022-01-07-antifragile/">📚Antifragile: Things That Gain From Disorder</a></p>
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<p><a href="/posts/2017/2017-10-7-Media-school/">Seven things I learned during the PhD Cup media school</a></p>
<div class="page-foot">
<div class="copyright">
&copy; Michiel Stock. Last modified: December 05, 2022. Website built with <a href="https://github.com/tlienart/Franklin.jl">Franklin.jl</a> and the <a href="https://julialang.org">Julia programming language</a>.
&copy; Michiel Stock. Last modified: September 20, 2023. Website built with <a href="https://github.com/tlienart/Franklin.jl">Franklin.jl</a> and the <a href="https://julialang.org">Julia programming language</a>.
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Expand Up @@ -70,11 +70,11 @@ <h2 id="newtons_method"><a href="#newtons_method" class="header-anchor">Newton&#
update &#61; get_map&#40;f&#41;</code></pre><pre><code class="plaintext code-output">#1 (generic function with 1 method)</code></pre>
<p>Yes&#33; We get a new function: the update map&#33; Let us try it on a value \(x=2\)</p>
<pre><code class="language-julia">update&#40;2.0&#41; # apply map once</code></pre><pre><code class="plaintext code-output">1.4166666666666665</code></pre>
<pre><code class="language-julia">update&#40;update&#40;2.0&#41;&#41; # apply map twice</code></pre><pre><code class="plaintext code-output">UndefVarError: update not defined
<pre><code class="language-julia">update&#40;update&#40;2.0&#41;&#41; # apply map twice</code></pre><pre><code class="plaintext code-output">UndefVarError: `update` not defined
</code></pre>
<pre><code class="language-julia">update&#40;update&#40;update&#40;2.0&#41;&#41;&#41; # apply map thrice</code></pre><pre><code class="plaintext code-output">UndefVarError: update not defined
<pre><code class="language-julia">update&#40;update&#40;update&#40;2.0&#41;&#41;&#41; # apply map thrice</code></pre><pre><code class="plaintext code-output">UndefVarError: `update` not defined
</code></pre>
<pre><code class="language-julia">update&#40;update&#40;update&#40;update&#40;2.0&#41;&#41;&#41;&#41; # apply map four times</code></pre><pre><code class="plaintext code-output">UndefVarError: update not defined
<pre><code class="language-julia">update&#40;update&#40;update&#40;update&#40;2.0&#41;&#41;&#41;&#41; # apply map four times</code></pre><pre><code class="plaintext code-output">UndefVarError: `update` not defined
</code></pre>
<p>We see that after a couple of steps, the Newton method converges to the root \(x=1\).</p>
<p>For our convenience, let us define a function that applies this map \(n\) times.</p>
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return x
end

applyiteratively&#40;2.0, update&#41; # apply 100 times</code></pre><pre><code class="plaintext code-output">UndefVarError: update not defined
applyiteratively&#40;2.0, update&#41; # apply 100 times</code></pre><pre><code class="plaintext code-output">UndefVarError: `update` not defined
</code></pre>
<h2 id="complex_roots"><a href="#complex_roots" class="header-anchor">Complex roots</a></h2>
<p>Astute readers might have noticed that \(x^3-1\) has three roots: one real &#40;\(x=1\)&#41; and two complex ones &#40;\(x=-1/2+\sqrt{3}i/2\) and \(x=-1/2-\sqrt{3}i/2\)&#41;. Would our method also work with complex inputs?</p>
<pre><code class="language-julia">applyiteratively&#40;-2.0 - 2.0im, update&#41;</code></pre><pre><code class="plaintext code-output">UndefVarError: update not defined
<pre><code class="language-julia">applyiteratively&#40;-2.0 - 2.0im, update&#41;</code></pre><pre><code class="plaintext code-output">UndefVarError: `update` not defined
</code></pre>
<p>We see that this converges to a different &#40;complex&#41; root&#33; Other values might converge to different roots&#33; </p>
<pre><code class="language-julia">applyiteratively&#40;2.0 &#43; 2.0im, update&#41;</code></pre><pre><code class="plaintext code-output">UndefVarError: update not defined
<pre><code class="language-julia">applyiteratively&#40;2.0 &#43; 2.0im, update&#41;</code></pre><pre><code class="plaintext code-output">UndefVarError: `update` not defined
</code></pre>
<h2 id="the_newton_fractal"><a href="#the_newton_fractal" class="header-anchor">The Newton fractal</a></h2>
<p>Imagine that we try this process for many complex numbers in an interval. Depending on the initial starting input, we end up in a different root. By colouring the results according to the root we end up in, we obtain the <em>Newton fractal</em>.</p>
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a in imag&#40;lower&#41;:step:imag&#40;upper&#41;&#93;

# apply the update 100 times
Z100 &#61; applyiteratively.&#40;Z0, update&#41;;</code></pre><pre><code class="plaintext code-output">UndefVarError: update not defined
Z100 &#61; applyiteratively.&#40;Z0, update&#41;;</code></pre><pre><code class="plaintext code-output">UndefVarError: `update` not defined
</code></pre>
<p>This results in a large complex matrix. We might define a colourmap for complex numbers as done <a href="https://vqm.uni-graz.at/pages/colormap.html">here</a>, though plotting the angle of the complex number in polar coordinates suffices.</p>
<pre><code class="language-julia">using Plots

heatmap&#40;angle.&#40;Z100&#41;, colorbar&#61;false, color&#61;:rainbow, ticks&#61;false&#41;</code></pre><pre><code class="plaintext code-output">UndefVarError: Z100 not defined
heatmap&#40;angle.&#40;Z100&#41;, colorbar&#61;false, color&#61;:rainbow, ticks&#61;false&#41;</code></pre><pre><code class="plaintext code-output">Failed to precompile Plots [91a5bcdd-55d7-5caf-9e0b-520d859cae80] to "/Users/michielstock/.julia/compiled/v1.9/Plots/jl_vLvKWF".
</code></pre>
<img src="/assets/posts/2021/2021-10-17-fractal/code/output/fractal.png" alt="">
<p>Below are some other examples.</p>
\[
f(x) = x^8 + 15x^4 -16
\]
<pre><code class="plaintext code-output">UndefVarError: get_map not defined
<pre><code class="plaintext code-output">UndefVarError: `get_map` not defined
</code></pre>
<img src="/assets/posts/2021/2021-10-17-fractal/code/output/fractal2.png" alt="">
\[
f(x) = \cosh(x) - 1
\]
<pre><code class="plaintext code-output">UndefVarError: get_map not defined
<pre><code class="plaintext code-output">UndefVarError: `get_map` not defined
</code></pre>
<img src="/assets/posts/2021/2021-10-17-fractal/code/output/fractal3.png" alt="">
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<h1 id="thinking_in_systems_a_primer"><a href="#thinking_in_systems_a_primer" class="header-anchor">Thinking in Systems: A Primer</a></h1>
<p>author: Donella Meadows</p>
<p>related books: <a href="/posts/2022/2022-03-20-how_the_world_really_works/">How the World Really Works</a>, <a href="/posts/2022/2022-01-07-antifragile/">Antifragile: Things That Gain From Disorder</a></p>
<p><img src="https://images-na.ssl-images-amazon.com/images/S/compressed.photo.goodreads.com/books/1390169859i/3828902.jpg" alt="" /></p>
<h2 id="the_main_take-away"><a href="#the_main_take-away" class="header-anchor">The main take-away</a></h2>
<p>A system is a set of interconnected things in such a way that they produce their own behaviour. Outside forces can influence it, though internal feedback is more likely to drive it — a living cell, a forest or a city are good examples of systems. If we want to understand and manage such systems, it is better to act on the system rather than on external disturbances and perturbations. For example, to keep your garden free from pests, it is better to create enough diversity to provide niches for predators such as ladybugs rather than to try to eradicate them using pesticides directly. </p>
<p>Systems that work well &#40;strong economy, good farmland, productive research group&#41; usually have the following properties:</p>
<ol>
<li><p>they are resilient and robust to changes;</p>
</li>
<li><p>they show a high degree of self-organization;</p>
</li>
<li><p>they are hierarchically organized.</p>
</li>
</ol>
<p>When systems fail, there is usually also a system solution. For example, when dealing with the tragedy of the commons, you can change incentives by educating, regulating or privatizing.</p>
<h2 id="who_is_this_for"><a href="#who_is_this_for" class="header-anchor">Who is this for?</a></h2>
<p>For all scientists and engineers, the book gives new mental tools to understand the world around you. It is even helpful for investing, policy-making and management. It uses virtually no mathematics, so it is accessible to everyone. A gem&#33;</p>
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&copy; Michiel Stock. Last modified: September 20, 2023. Website built with <a href="https://github.com/tlienart/Franklin.jl">Franklin.jl</a> and the <a href="https://julialang.org">Julia programming language</a>.
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