Master

Focus modules:

1. Computational Linguistics
2. Neuroinformatics
3. Study Project: Product identification from Images and Videos

Winter 2020/21

• Spanish B1
• Introduction to Technical Computer Science
  • An overview from logic gates and boolean algebra over circuit design and automaton theory through programming micro processors. Dealt also with ISA, interfacing, cost efficient design, and other relevant topics.
• Accompanying Seminar to the Study Project: Multi-agent communication in a multi-task visual world

Summer 2020

• Teaching: Scientific Programming in Python
• Decoding Neuronal Activity

Winter 2019/20

• The C++ Programming Language (Lecture)
  • Introduction to C and C++ programming. Contents included pointer-arithmetic, memory allocation, language properties, std-libraries. Also an overview over common libraries like STL/boost/freeglut was part of the course.
• The C++ Programming Language (Internship)
• Rule-based models
• Introduction to Ethics
• Conversational Agents and Speech Interfaces for Learning
• Political Theory of Cognitive Science
• Time Series Analysis and Forecasting
• Ethics and Climate Change

Summer 2019

• Teaching: Scientific Programming in Python
• Neurodynamics
• Introduction to political Philosophy
  • This philosophy lecture introduced the different approaches to theory of states, highlighting the difference in their priorities - from Hobbes’ Leviathan to the current philosophies for values such as liberalism and communitarism.
• Molecular genetic and neuroendocrine bases of behaviour (Lecture & Seminar)

Winter 2018/19

• Quantum Machine Learning
• Advanced Algorithms
• Spanish A2
• Prospects and Risks of Artificial Intelligence
  • In this seminar, we discussed both the risks of AI in far-future superintelligence scenarios as put forward by eg. Nick Bostrom, but also the current and concrete dangers such as reward hacking, proliferating biases and our continual dependance on AI.

Summer 2018

• Teaching: Scientific programming in Python
• Study Project: Product identification from images and videos (Part II)

Winter 2017/18

• Study Project: Product identification from images and videos (Part I)
• Natural Language Processing
  • This seminar dealt with all sub-categories of modern natural language processing, such as sentiment detection, translation, textual entailment, text summarization and much more, as well es the theory of the underlying embeddings.
• Selected Topics in Nature-inspired Algorithms
• Speech dialogue systems and embodied conversational agents
• Operating Systems and Computer Networks

Bachelor

Focus modules:

1. Neuroinformatics
2. Computer Science
3. Neurobiology
4. Artificial Intelligence
5. Computational Linguistics

Summer 2017

• Tutor: Introduction to Computational Linguistics
• The neuroscientific study of altered states of consciousness
• Conceptual Spaces - Applications and Learning
  • An introduction to Gärdenfors’ framework of conceptual spaces, discussing state of the art research. This course inspired me for my master’s thesis, where I improve upon one of the papers discussed in this course.

Winter 2016/17

• Introduction to Social Psychology
• Language Evolution
  • A seminar open for Cognitive Science, Philosophy and Anglistics students which covers the history of language of evolution as well as modern theories. To understand language evolution, human language is compared to primate and other communication systems.
• Rational Reasoning in MultiAgent Systems
• Workshop: Learning- and Memory-Training
• Artificial General Intelligence: Aspects and Approaches
• Implementing Artificial Neural Networks with TensorFlow
  • While learning about different architectures of Artifical Neural Networks (ANNs) and their applications, this class also introduced practical implementations with TensorFlow.
• Advanced Machine Learning
• Conference: Interdisciplinary College 2017: Creativity and Intelligence in Brains and Machines - From Individuals to Societies

Summer 2016

• Computer Science 4: Introduction to Theoretical Computer Science
  • Introduction to formal languages and finite-state machines, how to solve problems with those tools and other things related to theoretical computer science, e.g. Big O notation. The second half dealt with computational complexity: NP-completeness, computationalibity, etc.
• Spanish A1
• Advanced Computer Vision
  • Seminar discussing modern approaches in Computer Vision. In each session we discussed a chapter from Moeslund, Hilton, Krüger, and Sigal: Visual Analysis of Humans, Springer, 2011.
• Computer Graphics
  • Introduction to mathematics of computer graphics (affine transformations, model/view/projection, …), usage of OpenGL’s programmable pipeline (VS and FS) with the modern VBO approach.
  • Course Website here (german)
• Computer Science Programming Lab [Computergrafikpraktikum]
  • Usage of the methods learned in Computer Graphics in small groups working together on a game.
  • Course Website here (german)
  • Our Project is listed on my website
  • Report of our project on gitbooks
• Tutor: Introduction to Computational Linguistics
• Concepts and Applications of Neural Networks

Winter 2015/16

• Internship abroad: Universiti Teknologi MARA, Malaysia

Summer 2015

• Machine Learning
• Probabilistic Modeling of Perception and Cognition
  • This course mainly deals with probability theory, taking a Bayesian approach where probabilities are seen as a measurement of beliefs rather than relative frequencies. The course focuses on explaining the math, why it is the same for both approaches and when which approach should be applied – and why.
• Linguistic Theory and Cognition
• Neural Mechanisms of Illusory Perception
• Action and Cognition II
• Music and the Brain
• Personality Psychology
• Tutor: Introduction to Computational Linguistics

Winter 2014/15

• Information Technology: texts and data
• Neuroinformatics
  • Probabilistic methods to model neuronal activity. The main focus of the course was regression and tests for fitness.
• Methods of Artificial Intelligence
  • More advanced topics in AI: among others were different calculi, NP completeness, semantic gap, search problems, constraints, and heuristic approaches. The term project focused on general gameplaying: not only a game had to be defined, also a general gameplayer who could deal with any game.
• Computer Vision
  • This course focused on image processing with certain filter kernels, kernel design, image enhancements, segmentation and labeling, feature extraction (e.g. SIFT, canny edges, …) and similar topics.
• Introduction to analysis of linguistic data with R
  • During this class the programming language R is introduced by applying it to various statistical test procedures on linguistic data, e.g. the null hypothesis significance test or the t-test.
• Action and Cognition I
• Applied Cognitive Science and Cognitive Engineering
  • This seminar showcased Areas, where incorporating lessons from Cognitive Science can lead to better solutions to common problems or products, such as easy-to-understand interfaces for quick-glance overviews or less emotionally demanding telephone bots.
• Certificate for qualification as tutor
• Workshop: Presentation and Moderation
• Tutor: Computer Science 1: Algorithms
  • As tutor for this class, I corrected the homework assignments and held attestation with the students, letting them explain and demonstrate their solutions.
• Conference: Interdisciplinary College 2015: From Neuron to Person: Assembling Behavior and Cognition
• Word meaning: From logic to natural language

Summer 2014

• Cognitive Psychology / Neuropsychology
  • A detailed introduction to different topics in neuropsychology: Learning, problem solving, language, attention. Additionally covered: research methods in neuropsychology (measurement, statistics,…)
• Sensory Physiology
  • Deeper dive into the human sensory system, covering olfactory and auditory cortex, but primarily the human and rodent visual system.
• Siri, Watson, Skynet: An Introduction to Artificial General Intelligence
  • Seminar, in which many modern approaches to general artificial intelligence were presented and discussed, such as the chess engine Deep Blue, IBMs Watson, Conversational Agents and many others.
• Computer Science 2: Software Development Fundamentals
  • Introduction to common Gang-of-4 design patterns, ontop of the bare-bone algorithms. Furthermore deeper introduction into the Java-API, including threading, GUIs, generics, object orientation etc.
  • Course Website here
• Introduction to Artificial Intelligence and Logic Programming
  • Overview over AI topics from the “good old-fashined AI” perspective, which is the symbolistic, search-based logical approach to Artificial Intelligence. This includes turing tests, knowledge representation, searches and NP completeness. All of this was done using the PROLOG programming language, which was rigorously introduced.
• Introduction to Computational Linguistics
  • Introduction to all topics of psycholingustics, theoretical linguistics and computerlinguistics. Overview over topics in syntax and semantics. Introduction to formal languages and the Chomsky-Hierachy, as well as other linguistic phenomena like universal grammar, ambiguity, language acquisition, gardenpath effect, truth values, and similar topics concerning utterances.
• Introduction to the Philosophy of Mind
  • Overview over all areas regarding the philosophy of mind - from “Cogito, ergo sum” to modern questions such as Qualia, Free Will, Mental Causation, strong AI and much else, covering all positions from What it’s like to be a bat to the Chinese Room and much else.

Winter 2013/14

• Computer Science 1: Algorithms [Informatik A (Algorithmen und Datenstrukturen)]
  • First introduction to computer science, dealing with datastructures like heaps, stacks and lists and corresponding search or sort algorithms, in the Java programming language.
  • Course-Website here (german).
• Mathematics for natural sciences [Mathematik für Anwender I]
  • Detailed introduction to analysis and linear algebra.
• Statistics and Data Analysis I [Statistik und Datenanalyse I]
  • Introduction to different statistical techniques: Experimental design, evaluation of results, common mistakes, false-positives, types of statistics, types of variables and values.
• Foundations of Logic
  • Introduction to propositional- and predicate logic and handling calculus proofs. Definition of valid- and soundness and also well-formed formulae.
• Introduction to Neurobiology
  • Overview over different nerve cells and their functions, with a focus on the human visual cortex.
• Foundations of Cognitive Science
  • Overview over different research areas in Cognitive Science.