about

I am currently a PhD student under the supervion of Thomas Kirste in the Mobile Multimedia Information Systems Group at the University of Rostock.

In my research I focus on efficient Bayesian filtering algorithms for systems consisting of multiple, interacting entities. Such systems can be described conveniently by Multiset Rewriting Systems (MRS), which are ubiquitously used in the Modeling and Simulation community. However, probabilistic inference in such systems is hard, due to the large number of discrete system states. I try to figure out how to use, combine and extend recent advances in Lifted Probabilistic Inference and sampling-based inference to alleviate this hardness.


key publications

  • Stefan Lüdtke, Marcel Gehrke, Tanya Braun, Ralf Möller, Thomas Kirste. Lifted Marginal Filtering for Asymmetric Models by Clustering-based Merging. Proceedings of the 24th European Conference on Artificial Intelligence (ECAI) 2020. [pdf]
  • Stefan Lüdtke, Max Schröder, Sebastian Bader, Kristian Kersting, Thomas Kirste. Lifted Filtering via Exchangeable Decomposition. Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI) 2018. [pdf]
  • Stefan Lüdtke, Max Schröder, Frank Krüger, Sebastian Bader, Thomas Kirste. State-Space Abstractions for Probabilistic Inference: A Systematic Review. Journal of Artificial Intelligence Research (JAIR) 2018. [pdf]

more publications

  • Stefan Lüdtke, Chimezie Amaefule, Thomas Kirste, Stefan Teipel. Measuring Motion Behavior to Detect Spatial Disorientation in a VR Environment. In The 13th PErvasive Technologies Related to Assistive Environments Conference (PETRA) 2020.
  • Stefan Lüdtke, Kristina Yordanova, Thomas Kirste. Human Activity and Context Recognition using Lifted Marginal Filtering. Proceedings of the 15th Workshop on Context Modeling and Recognition (CoMoRea) 2019. [pdf]
  • Stefan Lüdtke, Alejandro Molina, Kristian Kersting, Thomas Kirste. Gaussian Lifted Marginal Filtering. KI: Advances in Artificial Intelligence 2019. [pdf]
  • Fernando Moya Rueda, Stefan Lüdtke, Max Schröder, Kristina Yordanova, Thomas Kirste, Gernot Fink. Combining Symbolic Reasoning and Deep Learning for Human Activity Recognition. Proceedings of the 15th Workshop on Context Modeling and Recognition (CoMoRea) 2019. [pdf]
  • Stefan Lüdtke, Maximilian Popko, Thomas Kirste. On the Applicability of Probabilistic Programming Languages for Causal Activity Recognition. German Journal of Artificial Intelligence (Künstliche Intelligenz) 2019. [pdf]
  • Kristina Yordanova, Stefan Lüdtke, Sam Whitehouse, Frank Krüger, Adeline Paiement, Majid Mirmehdi, Ian Craddock, Thomas Kirste. Analysing Cooking Behaviour in Home Settings: Towards Health Monitoring. Sensors 2019.
  • Sarah Weschke, Stefan Lüdtke, Martin Gube, Matthias Weippert, Chimezie Amaefule, Sven Bruhn, Rainer Bader, Thomas Kirste, Stefan Teipel. Measuring Gait Characteristics of Induced Disorientation in a VR Environment. 11. Kongress der Deutschen Gesellschaft für Biomechanik (DGfB) 2019.
  • Chimezie Amaefule, Stefan Lüdtke, Sarah Weschke, Christoph Berger, Sven Bruhn, Rainer Bader, Thomas Kirste, Stefan Teipel. Assessing Gait and Physiological Characteristics of Induced Disorientation in a VR Environment - The journey so far. Deutsche Gesellschaft für Psychiatrie und Psychotherapie, Psychosomatik und Nervenheilkunde (DGPPN) Kongress 2019.
  • Stefan Lüdtke, Max Schröder, Thomas Kirste. Approximate Probabilistic Parallel Multiset Rewriting using MCMC. KI: Advances in Artificial Intelligence 2018. [pdf]
  • Sam Whitehouse, Kristina Yordanova, Stefan Lüdtke, Adeline Paiement, Majid Mirmehdi. Evaluation of cupboard door sensors for improving activity recognition in the kitchen. PerCom Workshops Proceedings (PerHealth) 2018. [pdf]
  • Stefan Lüdtke, Max Schröder, Frank Krüger, Thomas Kirste. Where are my colleagues? Tracking and Counting Multiple Persons using Lifted Marginal Filtering. Procedings of the 4th international Workshop on Sensor-based Activity Recognition and Interaction (iWOAR) 2017. [pdf]
  • Stefan Lüdtke, Albert Hein, Frank Krüger, Sebastian Bader, Thomas Kirste. Actigraphic Sleep Detection for Real-World Data of Healthy Young Adults and People with Alzheimer’s Disease. Proceedings of BIOSIGNALS 2017 (BIOSIGNALS) 2017. [pdf]
  • Max Schröder, Stefan Lüdtke, Sebastian Bader, Frank Krüger, Thomas Kirste. Abstracting from Observation-equivalent Entities in Human Behavior Modeling. AAAI Workshop: Plan, Activity, and Intent Recognition (PAIR) 2017. [pdf]
  • Max Schröder, Stefan Lüdtke, Sebastian Bader, Frank Krüger, Thomas Kirste. Sequential Lifted Bayesian Filtering in Multiset Rewriting Systems. UAI Workshop: Statistical Relational Artificial Intelligence (StarAI) 2017. [pdf]
  • Max Schröder, Stefan Lüdtke, Sebastian Bader, Frank Krüger, Thomas Kirste. LiMa: Sequential Lifted Marginal Filtering on Multiset State Descriptions. KI: Advances in Artificial Intelligence 2017. [pdf]

activities

  • Organizer of the 6th International Workshop on Sensor-Based Activity Recognition and Interaction (iWOAR), 2019
  • Guest Editor of Sensors Special Issue "Sensor-Based Activity Recognition and Interaction", 2020
  • Reviews: Computers in Biology and Medicine, Artificial Intelligence in Medicine, MDPI Entropy, Winter Simulation Conference 2018, iWOAR (2017, 2018, 2019, 2020)