Michael Backenköhler

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I am currently a postdoc at the chair of modeling and simulation. Mainly I work on novel techniques for the analysis of stochastic reaction networks with a particular focus on models exhibiting multimodal behaviour. I am also interested in epidemiological modeling. Currently, my work concentrates on data-driven drug discovery.

Bridging probabilities via lumping Bridging probabilities via lumping

Publications

  • M. Backenköhler: Analysis of Markovian Population Models. Dissertation ( online). 2022.

  • M. Backenköhler, L. Bortolussi, V. Wolf: Variance Reduction in Stochastic Reaction Networks using Control Variates. 2021. ( pre-print)

  • G. Großmann, J. Zimmerlin, M. Backenköhler, V. Wolf: GINA: Neural Relational Inference From Independent Snapshots. 2021. ( pre-print)

  • M. Backenköhler, L. Bortolussi, G. Großmann, V. Wolf: Abstraction-Guided Truncations for Stationary Distributions of Markov Population Models. 18th International Conference on Quantitative Evaluation of SysTems (QEST), Springer LNCS, 2021. ( pre-print)

  • G. Großmann, M. Backenköhler, V. Wolf: Heterogeneity matters: Contact structure and individual variation shape epidemic dynamics. PLOS ONE, 2021. ( online)

  • M. Backenköhler, L. Bortolussi, G. Großmann, V. Wolf: Analysis of Markov Jump Processes under Terminal Constraints. Tools and Algorithms for the Construction and Analysis of Systems (TACAS), Springer LNCS, 2021. ( pre-print)

  • G. Großmann, M. Backenköhler, V. Wolf: Epidemic Overdispersion Strengthens the Effectiveness of Mobility Restrictions. (HSCC 21), 2021. ( pre-print)

  • G. Großmann, M. Backenköhler, J. Klesen, V. Wolf: Learning Vaccine Allocation from Simulations. 9th International Conference on Complex Networks and their Applications, 2020. ( pre-print)

  • G. Großmann, M. Backenköhler, V. Wolf: Importance of Interaction Structure and Stochasticity for Epidemic Spreading: A COVID-19 Case Study. 17th International Conference on Quantitative Evaluation of SysTems (QEST), Springer LNCS, 2020. ( pre-print)

  • M. Backenköhler, L. Bortolussi, V. Wolf: Bounding Mean First Passage Times in Population Continuous-Time Markov Chains. 17th International Conference on Quantitative Evaluation of SysTems (QEST), Springer LNCS, 2020. ( pre-print) ( poster)

  • G. Großmann, M. Backenköhler: Poster Abstract: Birth-Death Processes Reproduce the Infection Footprint of Complex Networks, 7th International Workshop on Hybrid Systems Biology (HSB), Springer LNCS, 2020. ( pre-print)

  • M. Backenköhler, L. Bortolussi, V. Wolf: Control Variates for Stochastic Simulation of Chemical Reaction Networks. 17th International Conference on Computational Methods in Systems Biology (CMSB), Springer LNCS 11773 pp. 42-59, 2019. ( pre-print)

  • M. Backenköhler, F. Scherzinger, A. Singla, V. Wolf: Data-Driven Approach Towards a Personalized Curriculum. Proc. of the 11th International Conference on Educational Data Mining (EDM), 2018. ( download)

  • M. Backenköhler, L. Bortolussi, V. Wolf: Moment-Based Parameter Estimation for Stochastic Reaction Networks in Equilibrium. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) 15(4) pp. 1180-1192, 2018.

  • M. Backenköhler, V. Wolf: Student performance prediction and optimal course selection: An MDP approach. 6th International Symposium “From Data to Models and Back (DataMod)” (SEFM), Springer LNCS, 2017.

  • M. Backenköhler, L. Bortolussi, V. Wolf: Generalized Method of Moments for Stochastic Reaction Networks in Equilibrium. 14th International Conference on Computational Methods in Systems Biology (CMSB), Springer LNCS pp. 15-29, 2016. Best Student Paper!

Teaching

Other Work

I have reviewed for CAV 2017, CMSB 2017, MMB 2018, CONCUR 2018, CMSB 2018, ACM SIGSIM PADS 2019, EDM 2019, QEST 2019, CMSB 2019, ACM SIGSIM PADS 2020, QEST 2020, HSCC 2021, ADHS 2021, ACM SIGSIM PADS 2021, TACAS 2022, QEST 2022, HSCC 2022 and journals ACM Transactions on Modeling and Computer Simulation, Mathematical Methods in the Applied Sciences, Bioinformatics, Mathematical Biosciences, Journal of Optimization Theory and Applications.