Dr. Christian Gruhl

Teamleiter: Self-Aware Microsystems (SAM)

Gruhl, Christian
Telefon
+49 561 804-6186
Fax
+49 561 804-6022
E-Mail
Standort
Wilhelmshöher Allee 73
34121 Kassel
Raum
WA-altes Gebäude (WA 73), ohne Raumangabe

Pu­bli­ka­tio­nen

[ 2022 ] [ 2021 ] [ 2020 ] [ 2019 ] [ 2018 ] [ 2017 ] [ 2016 ] [ 2015 ] [ 2014 ]

2022 [ nach oben ]

  • 1.
    Loeser, I., Braun, M., Gruhl, C., Menke, J.-H., Sick, B., Tomforde, S.: The Vision of Self-Management in Cognitive Organic Power Distribution Systems. Energies. 15, 881 (2022).
     
  • 2.
    Krupitzer, C., Gruhl, C., Sick, B., Tomforde, S.: Proactive hybrid learning and optimisation in self-adaptive systems: The swarm-fleet infrastructure scenario. Information and Software Technology. 145, 106826 (2022).
     

2021 [ nach oben ]

  • 1.
    Gruhl, C., Hannan, A., Huang, Z., Nivarthi, C., Vogt, S.: The Problem with Real-World Novelty Detection -- Issues in Multivariate Probabilistic Models. Workshop on Self-Improving System Integration (SISSY), ACSOS. bll. 204–209. IEEE (2021).
     
  • 2.
    Bellman, K., Botev, J., Diaconescu, A., Esterle, L., Gruhl, C., Landauer, C., Lewis, P.R., Nelson, P.R., Pournaras, E., Stein, A., Tomforde, S.: Self-improving system integration: Mastering continuous change. Future Generation Computer Systems. 117, 29–46 (2021).
     
  • 3.
    Gruhl, C., Tomforde, S.: OHODIN -- Online Anomaly Detection for Data Streams. Workshop on Self-Improving System Integration (SISSY), ACSOS. bll. 193–197. IEEE (2021).
     
  • 4.
    Gruhl, C., Sick, B., Tomforde, S.: Novelty detection in continuously changing environments. Future Generation Computer Systems. 114, 138–154 (2021).
     
  • 5.
    Heidecker, F., Gruhl, C., Sick, B.: Novelty based Driver Identification on RR Intervals from ECG Data. Workshop on Integrated Artificial Intelligence in Data Science, ICPR. bll. 407–421. IEEE, Milan, Italy (2021).
     
  • 6.
    Al-Falouji, G., Gruhl, C., Tomforde, S.: Digital Shadows in Self-Improving System Integration: A Concept Using Generative Modelling. Workshop on Self-Improving System Integration (SISSY), ACSOS. bll. 166–171. IEEE (2021).
     
  • 7.
    Hannan, A., Gruhl, C., Sick, B.: Anomaly based Resilient Network Intrusion Detection using Inferential Autoencoders. IEEE International Conference on Cyber Security and Resilience (CSR). bll. 1–7. IEEE (2021).
     

2020 [ nach oben ]

  • 1.
    Gruhl, C., Schmeißing, J., Tomforde, S., Sick, B.: Normal-Wishart clustering for novelty detection. Workshop on Self-Improving System Integration (SISSY), ACSOS. bll. 64–69. IEEE (2020).
     
  • 2.
    Pham Minh, T., Kottke, D., Tsarenko, A., Gruhl, C., Sick, B.: Improving Self-Adaptation For Multi-Sensor Activity Recognition with Active Learning. International Joint Conference on Neural Networks (IJCNN). IEEE (2020).
     
  • 3.
    Tomforde, S., Gruhl, C.: Fairness, performance, and robustness: is there a cap theorem for self-adaptive and self-organising systems?. Workshop on Self-Improving System Integration (SISSY), ACSOS. bll. 54–59. IEEE (2020).
     
  • 4.
    Tomforde, S., Gruhl, C., Sick, B.: A swarm-fleet infrastructure as a scenario for proactive, hybrid adaptation of system behaviour. Workshop on Self -Aware Computing (SeAC), ACSOS. bll. 166–169. IEEE (2020).
     

2019 [ nach oben ]

  • 1.
    Bellman, K.L., Gruhl, C., Landauer, C., Tomforde, S.: Self-Improving System Integration -- On a Definition and Characteristics of the Challenge. Workshop on Self-Improving System Integration (SISSY), FAS*W. bll. 1–3. IEEE (2019).
     
  • 2.
    Tomforde, S., Gelhausen, P., Gruhl, C., Haering, I., Sick, B.: Explicit Consideration of Resilience in Organic Computing Design Processes. International Workshop on Self-optimisation in Organic and Autonomic Computing Systems (SAOS), ARCS. bll. 1–6. VDE (2019).
     
  • 3.
    Barnes, C.M., Bellman, K., Botev, J., Diaconescu, A., Esterle, L., Gruhl, C., Landauer, C., Lewis, P.R., Nelson, P.R., Stein, A., Stewart, C., Tomforde, S.: CHARIOT -- Towards a Continuous High-Level Adaptive Runtime Integration Testbed. Workshop on Self-Improving System Integration (SISSY), FAS*W. bll. 52–55. IEEE (2019).
     

2018 [ nach oben ]

  • 1.
    Gruhl, C., Sick, B.: Novelty detection with CANDIES: a holistic technique based on probabilistic models. International Journal of Machine Learning and Cybernetics. 9, 927–945 (2018).
     
  • 2.
    Gruhl, C., Tomforde, S., Sick, B.: Aspects of Measuring and Evaluating the Integration Status of a (Sub-)System at Runtime. Workshop on Self-Improving System Integration (SISSY), FAS*W. bll. 198–203. IEEE (2018).
     

2017 [ nach oben ]

  • 1.
    Gruhl, C.: Highly Autonomous Learning in Collaborative, Technical Systems. In: Tomforde, S. en Sick, B. (reds.) Organic Computing -- Doctoral Dissertation Colloquium 2017. kassel university press, Kassel, Germany (2017).
     
  • 2.
    Gruhl, C., Beer, F., Heck, H., Sick, B., Bühler, U., Wacker, A., Tomforde, S.: A Concept for Intelligent Collaborative Network Intrusion Detection. International Workshop on Self-optimisation in Organic and Autonomic Computing Systems (SAOS), ARCS. VDE (2017).
     

2016 [ nach oben ]

  • 1.
    Heck, H., Wacker, A., Rudolph, S., Gruhl, C., Sick, B., Tomforde, S.: Towards Autonomous Self-tests at Runtime. IEEE International Workshop on Quality Assurance for Self-Adaptive, Self-Organising Systems (QA4SASO), FAS*W. bll. 98–99. IEEE (2016).
     
  • 2.
    Fisch, D., Gruhl, C., Kalkowski, E., Sick, B., Ovaska, S.J.: Towards Automation of Knowledge Understanding: An Approach for Probabilistic Generative Classifiers. Information Sciences. 370--371, 476–496 (2016).
     
  • 3.
    Gruhl, C.: Probabilistic Obsoleteness Detection for Gaussian Mixture Models. In: Tomforde, S. en Sick, B. (reds.) Organic Computing -- Doctoral Dissertation Colloquium 2016. bll. 45–56. kassel university press, Kassel, Germany (2016).
     
  • 4.
    Heck, H., Gruhl, C., Rudolph, S., Wacker, A., Sick, B., Hähner, J.: Multi-k-Resilience in Distributed Adaptive Cyber-Physical Systems. International Workshop on Self-optimisation in Organic and Autonomic Computing Systems (SAOS), ARCS. bll. 1–8. VDE, Nuremberg, Germany (2016).
     

2015 [ nach oben ]

  • 1.
    Heck, H., Edenhofer, S., Gruhl, C., Lund, A., Shuka, R., Hähner, J.: On the Application Possibilities of Organic Computing Principles in Socio-technical Systems. In: Tomforde, S. en Sick, B. (reds.) Organic Computing -- Doctoral Dissertation Colloquium 2015. bll. 165–170. kassel university press, Kassel, Germany (2015).
     
  • 2.
    Gruhl, C.: Anomalies in Generative Trajectory Models -- Discovering Suspicious Traces with Novelty Detection Methods. In: Tomforde, S. en Sick, B. (reds.) Organic Computing -- Doctoral Dissertation Colloquium 2015. bll. 95–107. kassel university press, Kassel, Germany (2015).
     
  • 3.
    Gruhl, C., Sick, B., Wacker, A., Tomforde, S., Hähner, J.: A building block for awareness in technical systems: Online novelty detection and reaction with an application in intrusion detection. IEEE International Conference on Awareness Science and Technology (iCAST). bll. 194–200. IEEE, Qinhuangdao, China (2015).
     

2014 [ nach oben ]

  • 1.
    Gruhl, C.: Self-Adapting Generative Modeling Techniques -- A Basic Building Block for Many Organic Computing Techniques. In: Tomforde, S. en Sick, B. (reds.) Organic Computing -- Doctoral Dissertation Colloquium 2014. bll. 99–109. kassel university press, Kassel, Germany (2014).
     
  • 2.
    Tomforde, S., Hähner, J., von Mammen, S., Gruhl, C., Sick, B., Geihs, K.: "Know thyself" -- Computational Self-Reflection in Intelligent Technical Systems. Workshop on Self-Improving System Integration (SISSY), SASO. IEEE, Braunschweig, Germany (2014).