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<h1>Teaching</h1>
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<h1>MSc theses</h1>
<p>I'd be happy to supervise MSc students at the University of Bern who are interested in pursuing research on the following topics:

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	<!--	<h2>2026-2027</h2>-->
			<h3>Understanding music perception through neural signal analysis </h3>
			<p><ul>How does the brain make sense of music? This project investigates the neural mechanisms underlying auditory perception by combining acoustic signal processing with analysis of brain activity recordings. To understand how the brain processes music, we will apply a range of signal processing and feature extraction methods to describe and annotate music. These representations will then be used within encoding and/or decoding models to analyse iEEG data, revealing how different sound properties are processed across the brain.<br><br>The student joining this project should be comfortable programming independently in Python and have some familiarity with basic signal processing techniques and/or time-series analysis. The project will develop practical skills in neural data analysis, acoustic signal processing, and encoding/decoding models.
			</ul><br></p>

			<h3>Comparing methods for estimating intrinsic neural timescales in EEG/iEEG data </h3>
			<p><ul>Intrinsic neural timescales can be understood as the characteristic durations over which neural activity remains correlated with itself. Timescales have emerged as a key organising principle of cortical computation, yet the methods used to estimate them vary in their assumptions and sensitivity. In this project, we will implement and systematically compare several timescale estimation methods (e.g. autocorrelation function, spectral methods), assessing their reliability, validity, and sensitivity to methodological choices.<br><br>The student working on this project should be motivated to program independently in Python and to analyse EEG and/or iEEG data. The project will develop practical skills in neural data analysis, reliability metrics, and model comparison.
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If you’re interested, please send me a brief email with your background, research interests, and a CV/transcript.</p>

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	<div class="pageitem">
		<h2>2023-2024</h2>
		<p>
			<ul>
				<li>PSYC034H6 Language (UG) at Birkbeck Department of Psychological Sciences - lecture on Speech Production</li> <br>
				<li>PSYC007H7 Neuroimaging methods (PG) at Birkbeck Department of Psychological Sciences - lecture on EEG data processing and analysis</li> <br>
				<li>PSYC0046 Introduction to Statistics with R (1UG) at the UCL Psychology and Language Sciences Department – Demonstrator and Teaching Assistant (Instructor: Dr Metodi Siromahov)</li>
			</ul>
		</p>
		</div>-->

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<h1>Modules</h1>

	<div class="pageitem">
		<h2>2024-2025</h2>
		<p>
			<ul>
				<li>Mentor for <a href="https://poloniumfoundation.org">Polonium Foundation</a> global mentoring programme</li></br>
				<li>PSYC007H7 Neuroimaging methods (PG) at Birkbeck Department of Psychological Sciences - lecture on EEG data processing and analysis</li> <br>
				<li>Research design workshop tutor during <a href="https://imprs-coni.mpg.de/summer-school-2024">the International Max Planck Research School on Cognitive Neuroimaging Summer School</a> (PG) at the Faculty of Brain Sciences at University College London</li>
			</ul>
		</p>
		</div>

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		<h2>2023-2024</h2>
		<p>
			<ul>
				<li>PSYC034H6 Language (UG) at Birkbeck Department of Psychological Sciences - lecture on Speech Production</li> <br>
				<li>PSYC007H7 Neuroimaging methods (PG) at Birkbeck Department of Psychological Sciences - lecture on EEG data processing and analysis</li> <br>
				<li>PSYC0046 Introduction to Statistics with R (1UG) at the UCL Psychology and Language Sciences Department – Demonstrator and Teaching Assistant (Instructor: Dr Metodi Siromahov)</li>
			</ul>
		</p>
		</div>

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	<h2>2022-2023</h2>
	<p>
		<ul>
			<li>PSYC0046 Introduction to Statistics with R (1UG) at the UCL Psychology and Language Sciences Department – Demonstrator and Teaching Assistant (Instructor: Dr Sarah Griffiths)</li> <br>
			<li>COMP0016 Systems Engineering & Human-Computer Interaction (2UG) at the UCL Interaction Centre, Department of Computer Sciences – Teaching Assistant (Instructor: Dr Yun Fu) </li> <br>
			<li>COMP0067 App Engineering & Human-Computer Interaction (PG) at the UCL Interaction Centre, Department of Computer Sciences – Teaching Assistant (Instructor: Dr Yun Fu)</li>
		</ul>
	</p>
	</div>

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	<h2>2021-2022</h2>
	<p>
		<ul>
			<li>PSYC0012 Research Methods in Psychology (2UG) at the UCL Psychology and Language Sciences Department – Research Project Coordinator</li> <br>
			<li>PSYC0046 Introduction to Statistics with R (1UG) at the UCL Psychology and Language Sciences Department – Demonstrator and Teaching Assistant (Instructor: Dr Sarah Griffiths)</li>
		</ul>
	</p>
	</div>

	<div class="pageitem">
	<h2>2020-2021</h2>
	<p>
		<ul>
			<li>PSYC0005 Introduction to Psychological Experimentation (1UG) at the UCL Psychology and Language Sciences Department – Demonstrator (Instructor: Dr Katie Fisher)</li> <br>
			<li>PSYC0012 Research Methods in Psychology (2UG) at the UCL Psychology and Language Sciences Department – Research Project Coordinator</li> <br>
			<li>Methods for Dummies Course at Wellcome Centre for Human Neuroimaging at the UCL Institute of Neurology – Content Coordinator </li>
		</ul>
	</p>
	</div>

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	<h2>2019-2020</h2>
	<p>
		<ul>
			<li>COMP0016 Systems Engineering & Human-Computer Interaction (2UG) at the UCL Interaction Centre, Department of Computer Sciences – Teaching Assistant (Instructor: Dr Chris Evans) </li> <br>
			<li>COMP0067 App Engineering & Human-Computer Interaction (PG) at the UCL Interaction Centre, Department of Computer Sciences – Teaching Assistant (Instructor: Dr Chris Evans)</li> <br>
			<li>PSYC0005 Introduction to Psychological Experimentation at the UCL Psychology and Language Sciences Department – Demonstrator (Instructor: Dr Katie Fisher)</li> <br>
			<li>Methods for Dummies Course at Wellcome Centre for Human Neuroimaging at the UCL Institute of Neurology – Course Organizer and Content Coordinator </li>
		</ul>
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