Dr. Stefan Lüdtke

Dr. Stefan Lüdtke
Postdoc
Universität Mannheim
Institut für Enterprise Systems
L 15, 1–6
L15, 1–6 – Raum 416
68161 Mannheim

Forschungs­interessen

  • Kombination von datengetriebenen und wissens­basierten KI-Methoden
  • Effiziente probabilistische Inferenz
  • Aktivitätserkennung

Lebenslauf

Seit 2021 Postdoc am Institut für Enterprise Systems
2016 – 2021 Wissenschaft­licher Mitarbeiter am Institute of Visual and Analytic Computing an der Universität Rostock
2014 – 2016 Master of Science in Informatik (Smart Computing) an der Universität Rostock
2011 – 2014 Bachelor of Science in Informatik (Robotics and Automation) an der Universität zu Lübeck

Publikationen

  • Lüdtke, S., Bartelt, C. und Stuckenschmidt, H. (2022). Exchangeability-aware sum-product networks. In , Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, Vienna, 23–29 July 2022 (S. 4864-4870). , International Joint Conferences on Artificial Intelligence Organization: Wien.
  • Wilken, N., Cohausz, L., Schaum, J., Lüdtke, S., Bartelt, C. und Stuckenschmidt, H. (2022). Leveraging planning landmarks for hybrid online goal recognition. In , International Conference on Automated Planning and Scheduling ICAPS (2022) : June 13-17, 2022, virtual (S. ). , CEUR Workshop Proceedings: Aachen.

Andere Publikationen

  • 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]
  • Stefan Lüdtke, Fernando Moya Rueda, Waqas Ahmed, Gernot A. Fink, Thomas Kirste. Human Activity Recognition using Attribute-Based Neural Networks and Context Information. 3rd International Workshop on Deep Learning for Human Activity Recognition 2021. [pdf]
  • Stefan Lüdtke. Lifted Bayesian Filtering in Multi-Entity Systems. PhD thesis. 2021. [web]
  • Iris Hochgraeber, Christiane Pinkert, Sumaiya Suravee, Stefan Lüdtke, Margareta Halek, Bernhard Holle. Wissenschafts­basierte Ontologie­entwicklung als Grundlage für KI-basierte Beratung von pflegenden Angehörigen. Einblicke in das Projekt eDEM-CONNECT. 20. deutscher Kongress für Versorgungs­forschung 2021.
  • Stefan Lüdtke, Wiebke Hermann, Thomas Kirste, Heike Benes, Stefan Teipel. An Algorithm for Actigraphy-based Sleep/Wake Scoring: Comparison with Polysomnography. Clinical Neurophysiology 2020. [web]
  • Anne Klostermann, Chimezie Amaefule, Stefan Lüdtke, Thomas Kirste, Stefan Teipel. Physiological and Gait Pattern Effects of Induced Disorientation in a 3D Virtual Environment. Alzheimer's Association International Conference (AAIC) 2020.
  • Charlotte Hinz, Chimezie Amaefule, Stefan Lüdtke, Thomas Kirste, Stefan Teipel. Assessing accelerometric, gait and physiological parameters of induced spatial orientation in people with MCI or mild dementia and older healthy cohorts. Alzheimer's Association International Conference (AAIC) 2020. [web]
  • Stefan Lüdtke, Thomas Kirste. Lifted Bayesian Filtering in Multiset Rewriting Systems. Journal of Artificial Intelligence Research (JAIR) 2020. [web]
  • Chimezie Amaefule, Stefan Lüdtke, Thomas Kirste, Stefan Teipel. Effect of Spatial Disorientation in a Virtual Environment on Gait and Vital Features in Patients with Dementia: Pilot Single-Blind Randomized Control Trial. JMIR Serious Games 2020. [web]
  • 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]