Program Overview

University Program Information

The Cognitive Systems Lab at the University of Bremen offers various programs and research areas in the field of mathematics and computer science.

Faculty and Team

The lab is directed by Prof. Dr.-Ing. Tanja Schultz and consists of a team of staff members, including:

• Prof. Dr.-Ing. Tanja Schultz
• Dr.-Ing. Marvin Borsdorf
• Elisa Brauße, M.Sc.
• Gabriel Ivucic
• Lily Meister, M. Sc.
• Dr. Dennis Küster
• Dr. Hui Liu
• Rinu Elizabeth Paul
• Dr. Felix Putze
• Dr.-Ing. Zhao Ren
• Anthony Richardson, M. Sc.
• Lourenço Abruhosa Rodrigues, M. Sc.
• Kevin Scheck
• Rathi Adarshi Rammohan, M.Tech.

Teaching

The lab offers various courses and teaching programs, including:

• Theses and more
• Winter semester 2024/25
• Winter semester 2022/23
  • Automatic Speech Recognition
  • Hot Topics in Sensors and Human Activity Research (03-IMS-TSHAR)
• Summer Semester 2022
  • Advanced Machine Learning (Kopie 1)
  • Biosignals and User Interfaces
  • Tutorial: Brain Pattern Recognition
• Winter semester 2021/22
  • Tutorial: Brain Pattern Recognition
• Summer Semester 2021
  • Seminar Bremen Big Data Challenge
  • Tutorial: Brain Pattern Recognition
  • Biosignals and User Interfaces
  • RobARinth
  • Advanced Machine Learning
• Winter semester 2020/21
• Summer semester 2020
  • Biosignals and User Interfaces
  • Tutorial: Brain Pattern Recognition
  • Seminar Bremen Big Data Challenge
• Winter Semester 2019/20
  • Tutorial: Brain Pattern Recognition
  • Sensordatenverarbeitung (SdV)
  • HoloAI
  • BOWSR2.0 – Build your Own Web-based Speech Recognizer
  • Automatische Spracherkennung (ASR)
• Summer Semester 2019
  • Tutorial: Brain Pattern Recognition
  • Biosignals and User Interfaces
  • Master-Projekt: "Build your Own Web-based Speech Recognizer 2.0" (BOWSR 2.0)
  • Seminar Bremen Big Data Challenge
• Winter Semester 2018/19
  • Tutorial: Brain Pattern Recognition
  • Bachelor-Projekt: "Build your Own Web-based Speech Recognizer" (BOWSR)
  • Master Project: I spy with my little eye
  • Class: Automatic Speech Recognition
• Summer Semester 2018
  • Seminar Bremen Big Data Challenge
  • Selected problems of cognitive systems
  • Biosignals and User Interfaces
  • Fundamentals of Machine Learning
  • Tutorial: Brain Pattern Recognition
• Winter Semester 2017/18
  • Class: Automatic Speech Recognition
  • Tutorial: Brain Pattern Recognition
  • Seminar: Selected problems in cognitive systems
• Summer Semester 2017
  • Biosignals and User Interfaces
  • Seminar Bremen Big Data Challenge
• Winter Semester 2016/17
  • Class: Automatic Speech Recognition
  • Bachelor Project: Biosignal-based Butler
• Summer Semester 2016
  • Biosignals and User Interfaces
  • Seminar Bremen Big Data Challenge
• Winter Semester 2015/16
  • Class: Automatic Speech Recognition

Tutorial: Brain Pattern Recognition

In Brain Pattern Recognition, students explore the steps involved in developing a brain-computer interface (BCI) that captures and automatically interprets brain activity. The course focuses on the independent practical implementation of theoretical concepts in teams. The objective is to understand the basic techniques of a BCI and implement them with modern tools. Course contents include:

• Brain and EEG
• Experiment design
• Signal processing
• Visualization
• Machine learning
• Evaluation

Before the start of the course, a Python introduction must be completed and proven by processing a homework assignment. The number of seats is limited.

Research

The lab conducts research in various areas, including:

• BiosignalsLab
• Silent Speech Communication
  • CSL-EMG_Array Corpus
• Cognitive Adaptive Interaction Systems
• Systems for People with Dementia
• Brain Activity Modeling
• Automatic Speech Recognition
• Human Activity Recognition
• sensORder: Artifact Classification during Biosignal Acquisition
• Motion Recognition
• Spoken Communication from Neural Signals

Publications

The lab publishes research in various formats, including:

• Books / Journals
• Conferences
• Doctoral Dissertations
• Final Theses