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Prof. Dr. Bernd Ludwig

Areas of Work

01 | Projects


Campus navigation and room search at the University of Regensburg and the OTH Regensburg

02 | Research Interests

Natural Language Processing

Our main research interest lies in the interference between syntax, semantics, and pragmatics of natural language - viewed from the perspective of automated language understanding: Reconstructing the meaning of utterances automatically requires well suited means for formally representing syntactic and semantic information entailed in these utterances. The precise meaning of an utterance in context can only be determined effectively if information about the context can be incorporated in this inference process. As a consequence, natural language understanding requires also the context to be represented formally. The challenge of this area of research obviously is to develop methods to apply knowledge about the discourse context and the activity context in which utterances are made for inferring the meaning of an utterance in this context and conclude the changes of the context resulting from the utterance.

Another aspect of this issue is the context-aware processing of speech recognizer output. Here, the challenge lies in applying pragmatic knowledge for the evaluation and disambiguation of hypotheses generated by a speech recognizer.

For devising solutions to the issues addressed above, we cover several interconnected areas of research:

  • Syntax, semantics, and pragmatics of natural language
  • Theory of discourse
  • Models of discourse representation
  • Parsing
  • Formal languages and formal logics
  • Knowledge representation and reasoning
  • Probabilistic models of natural language

Multimodal User Interfaces

NLU is of interest in our research group as a modality for users to interact with intelligent information systems. Such systems require intelligent interfaces as users and systems interact and exchange information about cooperative problem solving tasks. Intelligent interfaces have to support this highly complex multimodal discourse. To develop innovative solutions in this area, we work on

- models of cooperation
- symbolic and probabilistic planning
- modellng for actions
- task analysis
- problem solving

User Models and User Preferences

When users and information systems cooperate, systems have to react appropriately on user preferences. Understanding the preferences helps understanding the user's behavior, recognizing his current and future activities, and predicting what users could do next. In several use cases, we develop user models for activities and preferences and tackle the areas of

  • User modeling
  • User preferences
  • Recommender systems

Interactive Assistance Systems

In several research projects, we apply our concepts in order to implement and evaluate intelligent assistance and information systems. They are capable to interact in different modalities with their users and solve problems cooperatively. Currently, the focus lies on:

  • Pedestrian navigation systems (indoor and outdoor)
  • Route planning for routes with multiple means of transport
  • Route planning in indoor environments
  • Localization in indoor environments
  • User adaptive and context aware browsers (e.g. tourist guides on smartphones)
  • Personalized information systems for prevention of diseases

03 | Teaching

Action Strategies of Intelligent Virtual Agents

Summer 2017  

Advanced Methods of IR

Summer 2012 

Advanced Seminar Information Science

Summer 2012 | Winter 2012/13 | Summer 2013 | Winter 2013/14 | Summer 2014 | Winter 2014/15 | Summer 2015 | Winter 2015/16 | Summer 2016 | Winter 2016/17 | Summer 2017 | Winter 2017/18 | Summer 2018 | Winter 2018/19 | Summer 2019 | Winter 2019/20 | Summer 2020 | Summer 2022 | Summer 2023 | Summer 2024

Agent Stories - Lecture Series

Summer 2012 

AI for Computer Games

Summer 2017  

AI for Serious Games

Winter 2017/18  

Algorithms for Human-Machine Interaction

Winter 2013/14 | Summer 2015 | Winter 2016/17 | Winter 2017/18 | Winter 2018/19 | Winter 2019/20 | Winter 2020/21 | Winter 2021/22 | Winter 2022/23 | Winter 2023/24

Automatic Understanding of Spoken Language (with tutorial)

Winter 2011/12  

Case Studies

Summer 2019 | Summer 2020

Control of Autonomous, Interactive Robots

Winter 2012/13  

Corpus Linguistics (Lecture/Seminar)

Summer 2012 

Doctoral Seminar

Winter 2020/21

Foundations and Application of Machine Learning Methods

Summer 2018 | Summer 2019 | Summer 2020 | Summer 2022 | Summer 2023 | Summer 2024

Foundations of Computational Intelligence

Summer 2020 | Summer 2022 | Summer 2023 | Summer 2024

Heaven - where is the information? User and situation adaptive information systems

Winter 2012/13  

Human Activity Recognition

Summer 2012  

Human-Machine Interaction Research Seminar: Current Trends in Speech Recognition

Winter 2011/12  

Information Systems (with tutorial)

Summer 2014 | Summer 2015 | Summer 2016 | Summer 2017 | Summer 2018 | Summer 2019

The Intelligent Browser

Summer 2013  

Interaction with Virtual Agents

Summer 2018

Interactive Navigation with Landmarks

Summer 2012  

Knowledge Representation and Processing in Practice

Winter 2016/17  

Lecture Series: Digital Society

Winter 2014/15  

Lecture Series: ChatGPT & Co.

Summer 2023

Mathematical Foundations: Knowledge Representation and Processing (with Tutorial)

Winter 2011/12 | Summer 2012 | Winter 2012/13 | Summer 2013 | Winter 2013/14 | Summer 2014 | Winter 2015/16 | Winter 2016/17 | Winter 2017/18 | Winter 2018/19

Participating in Research Work

Winter 2021/22

Persuasion with Linguistic Methods

Summer 2016  

Processing of Spoken Language

Summer 2016  

Problem-oriented Programming Languages

Winter 2018/19  

Representation and Processing of Secure and Uncertain Knowledge

Winter 2019/20 | Winter 2020/21 | Winter 2021/22 | Winter 2022/23 | Winter 2023/24

Scene affordance and focus of attention - How do people perceive spatial environments?

Summer 2024

Tutorial to Computational Intelligence

Summer 2023 | Summer 2024

Tutorial to Introduction to Information Linguistics I

Winter 2019/20 | Winter 2020/21 | Winter 2021/22 | Winter 2023/24

Tutorial to Information Linguistics II: Language- and Text Technology

Summer 2020

Tutorial to Machine Learning Methods for DH

Summer 2023 | Summer 2024

Tutorial to Representation and Processing of Secure and Uncertain Knowledge

Winter 2021/22

UR Walking

Winter 2012/13 | Summer 2013 | Winter 2013/14 | Summer 2014 | Summer 2015

Voice Recognition

Winter 2015/16  


Bernd Ludwig studied Computer Science at Friedrich-Alexander-University in Erlangen-Nuremberg from 1992-1997. His 2004 phd thesis focused on plan-based dialoge management for natural language processing applications and was supervised by Prof. Heinrich Niemann and Prof. Günther Görz, respectively. Bernd finished his habilitation at  Friedrich-Alexander-University in Erlangen-Nuremberg in 2010 (title of thesis: Plan-based HCI in multimodal recommender systems ("Planbasierte Mensch-Maschine-Interaktion in multimodalen Assistenzsystemen").

1997-2004 Bernd was a post-doctoral researcher at the knowledge processing group of the Bavarian Research Center for Knowledge-Based Systems in Erlangen. He became an assistant professor at the Chair of Artificial Intelligence (Friedrich-Alexander-University in Erlangen-Nuremberg) in 2004. In 2010, Bernd was appointed BIT guest professor und postdoc researcher at the Free University of Bozen and the Department of Information Engineering and Computer Science der Universitá degli Studi di Trento. After his return in November 2010, he was an associate professor (Privatdozent)  until March 2011. Bernd was appointed as professor of Computational Linguistics at the Chair of Information Science at University of Regensburg in August 2011.

His research focuses on the dependcies of Communicative Action in Human Computer Interaction as well as its implementation using efficient algorithms. Furthermore, he is interested in the use of mobile devices as an aid to solve complex tasks using recommender systems. Research projects (ROSE; VAMOS; NADINE) currently lead by Bernd Ludwig strongly reflect this interest.

He is co-editor of the German journal Künstliche Intelligenz and is an appointed reviewer at and organizer of several international conferences.


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Sci. Activities

PC member

  • AIA 2010, 2011, 2012, 2013 (Conference on Artificial Intelligence and Applications)
  • CaRR (Context-awareness in Retrieval and Recommendation) 2011
  • ENTER 2012, 2013, 2014, 2015
  • euroHCIR 2012 (2nd European Workshop on Human-Computer Interaction and Information Retrieval)
  • Interact 2013
  • ICAART 2010, 2011, 2012, 2013, 2014, 2015
  • ISI 2021
  • IWCS 2011 (9th International Conference on Computational Semantics)
  • Log-IC 2011 (Second International Workshop on Logic-Based Interpretation of Context: Modeling and Applications)
  • MobileHCI 2013
  • RecSys 2014, 2015, 2021
  • S4F2012 (Searching For Fun Workshop in conjunction with ECIR 2012), 2014
  • UMMS3 (User Modelling for Motivational Systems 3)
  • IIiX 2014
  • ECIR 2015

Reviews for Journals

  • UMUAI (User Modeling and User-Adapted Interaction)
  • BNSC (Journal on BioNanoScience)
  • BISE
  • German Journal of Artificial Intelligence
  • TiiS (ACM Transactions on Interactive Intelligent Systems)

(Co-)Chair of Workshops or Conferences

  • CAIA 2010, 2011 (Workshop on Context Aware Intelligent Assistance in conjunction with KI 2010, 2011)
  • CHIIR 2022 (General Co-Chair ACM Conference on Human Interaction and Information Retrieval)
  • COSIT 2019 (General Co-Chair 14th International Conference on Spatial Information Theory)
  • HealthRecSys 2016, 2017, 2018, 2019 (Workshop on Health Recommender Systems)
  • IIiX2014 (Information Interaction in Context symposium)
  • Lifestyle 2012 (Workshop on Recommender Technologies for Lifestyle Change in conjunction with RecSys 2012)

PhD Student (Co-)Supervisions




Zeitschrift für Medizinische Physik (Journal of Medical Physics)

Author Award 2022 for the best paper in the preceding year

Theresa I. Götz, Elmar W. Lang, Christian Schmidkonz, Torsten Kuwert, Bernd Ludwig for the paper "Dose Voxel Kernel Prediction With Neural Networks for Radiation Dose Estimation"


2018 - 2021


Research Grant for OPTAPEB




Most Influential Scholar Award



15th International Conference on Mobile and Ubiquitous Mul-

Nomination for Best Paper Award



KI 2010: Advances in Artificial Intelligence: 33rd Annual Ger-
man Conference on AI

Nomination for Best Paper Award




Study Award for Diploma Thesis „Partial Logics for Seman-
tics and Discourse"

  1. Homepage UR

Information Science

Prof. Dr.

Bernd Ludwig

Building PT, Room 3.0.84c
Phone +49941 943-3600

Route to Office