Contact

Prof. Dr.-Ing. Johannes Maucher
Media University Stuttgart
Nobelstrasse 10
70569 Stuttgart
++49 711 8923 2178
maucher(at)hdm-stuttgart.de

Lectures

Bachelor Medieninformatik (MI)

Master Computer Science and Media (CSM)

Data Science Master

Currently open Project- and Theses Offers for Students

Current Research Projects

Events

Publication on Low-Resource Text Classification using Domain-Adversarial Learning

Recently, my colleague and Ph.D.-candidate Daniel Griesshaber published our joined work with Professor Ngoc Thang Vu at the 6th Conference on Statistical Language and Speech Processing (SLSP) in Brussels. Here is the paper’s abstract: Deep learning techniques have recently shown to be successful in many natural language processing tasks forming state-of-the-art systems. They require, however, a large amount of annotated data which is often missing. This paper explores the use of domain-adversarial learning as a regularizer to avoid overfitting when training domain invariant features for deep, complex neural network in low-resource and zero-resource settings in new target domains or languages. [Read More]

HdM internal workshop on Artificial Intelligence, 25th September, 2018, Room 056

Artificial Intelligence (AI) is currently one of the hottest topics in computer science. Developments in AI are supposed to strongly influence all areas of life: The way how we communicate, move, create, work, study, … At the HdM study program Computer Science and Media Artificial Intelligence has been an integral part of teaching and research since more than 10 years. However, currently AI starts to penetrate nearly all disciplines of our university. [Read More]

IEEE Publication Symbolic Reasoning for Hearthstone

In the context of Andreas Stiegler’s Ph.D. we researched Reasoning in Game AI. Andreas particularly focused on reasoning in the card-trading game Hearthstone. Our findings have now been published in the Journal IEEE Transactions on Games - Volume: 10, Issue:2, June 2018. Many thanks to Andreas and the other co-authors Keshav P. Dahal and Daniel Livingstone. Here is the paper’s abstract: Trading-card games are an interesting problem domain for Game AI, as they feature some challenges, such as highly variable game mechanics, that are not encountered in this intensity in many other genres. [Read More]

2nd Deeplearning Day at HdM, 12th January, 2018

We are happy to announce the 2nd HdM Deeplearning Day at Friday, January 12th, 2018, room I003, Nobelstr. 8 Deep Learning is currently one of the hottest topics in computer science. The performance of existing applications such as object recognition, speech recognition or automatic translation have been revolutionized by deep neural networks. Moreover, this type of algorithms open doors for a wide range of new intelligent applications. The presentations of the 2nd Deeplearning cover current research directions, applications of deep learning in autonomous driving and architecture of complex and high-performing AI-systems. [Read More]

Publication in European Journal of Applied Physiology

Machine Learning is a quite universal science. Or better: The field of Machine Learning applications is currently growing rapidly. Right now, physiology is not a prime ML application-field, but I believe that there is much potential for intelligent algorithms to provide new insights in many medical disciplines. One proof for this believe is the fact that Machine Learners like me can publish in Physiologial Journals. Yes! This is my first publication in a Journal of Physiology: Recovery of the cardiac autonomic nervous and vascular system after maximal cardiopulmonary exercise testing in recreational athletes. [Read More]

Artificial Intelligence Hackathon Daimler TSS

The organizer’s of the hackathon are going to visit HdM at Thursday, October 19th, 9.30h, room 012. Interested students are cordially invited to attend this short informative event.

Anaconda Navigator Pic

Anaconda Navigator Pic