Study projects in Autonomous Robotics
We announce study projects for the study program Angewandte Informatik together with all others study projects in an official event every semester.
We announce study projects for the study program Angewandte Informatik together with all others study projects in an official event every semester.
Closed-loop brain-behavior system
In this project we combine insights from state-of-the-art machine learning and modern neuroscience experiments, to study the role of spatial representations that emerge in a reinforcement learning agent when learning a biologically inspired navigation task.
The goal of this project is to identify what behavioral evidence would be necessary and sufficient to claim that a nonhuman species possesses episodic memory traces. The project requires background knowledge of memory and experience in developing philosophical analyses.
Spatial Light Modulators can be used to modulate the effective shape of light, e.g., a laser beam. They are thus useful in industrial applications like laser cutting where beam shapes need to be adapted quickly. However, generating complex shapes is time-consuming and error-prone using current algorithms based on Fourier transformations. In this work, a deep learning approach that automatically generates the correct modulations to obtain the desired shape should be explored. The Thesis is conducted in cooperation with the company LIDROTEC(https://www.lidrotec.de/).
This thesis involves integrating a new method for estimating cardinality into query engines to assess its effectiveness in improving query optimization.
A famous computational challenge is the Travelling Salesman Problem, in which a traveller needs to find the shortest route to visit a set of cities. Humans and other animals are very good at finding efficient solutions to practical tasks related to the Traveling Salesman Problem, but we do not know which strategies or algorithms they use to solve the problem. In computer science promising approaches to find an optimal solution include (deep) reinforcement learning [1]. Do humans and other animals use a strategy, similar to a reinforcement learning approach? In this project you will implement a reinforcement learning model of animal behaviour and compare the behaviour of the model with the animal behaviour to identify the underlying strategy and algorithm.
Master-Arbeit zu vergeben in Kooperation mit Prof. Stefan Herlitze, Lehrstuhl für Allgemeine Zoologie und Neurobiologie
Einfluss der Extrazellulärmatrix auf die Aktivitätsausbreitung im visuellen Kortex der Maus
"I-See" - Improving intracortical visual prostheses. Our multidisciplinary EU-funded project brings together scientists from different fields and complementary experimental and theoretical know-how. The project part of the PhD position comprises electrical stimulation in the mouse brain combined with cutting-edge (optogenetic) voltage imaging techniques (Knöpfel Lab, Imperial College London). The aim of our international consortium (Switzerland, Canada, UK, and Germany) is to improve the ability of cortical prostheses to 'mimic' the language of the brain and increase the safety and longevity of visual prosthetic devices.
Our lab participates in a new call offered by the RUB to attract students from China. This is also to strengthen existing education and research cooperation with Chinese universities and research institutions. The China Scholarship Council (CSC) offers scholarships to highly qualified Chinese candidates who wish to study and/or carry out research at the Ruhr University Bochum, Germany.
The goal of MoNN&Di is to create a focused 4 year doctoral training programme that enables scrutiny of how monoaminergic neuromodulators influence neuronal circuits and shape behavioral responses.
Reproduce results of state of the art machine learning papers from the last year as part of the official ML Reproducibility challenge.
The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.
Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany
Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210