Publications of PN 7

  1. 2023

    1. X. Yu, “DC Limb Motion Guidance in Extended Reality,” in 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), in 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). Mar. 2023, pp. 967–968. doi: 10.1109/VRW58643.2023.00326.
    2. C. Yan, B. Ehinger, A. Pérez-Bellido, M. V. Peelen, and F. P. de Lange, “Humans predict the forest, not the trees : statistical learning of  spatiotemporal structure in visual scenes,” Cerebral cortex, vol. 33, no. 13, Art. no. 13, 2023, doi: 10.1093/cercor/bhad115.
    3. M. Wieland, M. Sedlmair, and T.-K. Machulla, “VR, Gaze, and Visual Impairment: An Exploratory Study of the Perception of Eye Contact across different Sensory Modalities for People with Visual Impairments in Virtual Reality,” in Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, in Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems. Hamburg, Germany: Association for Computing Machinery, Apr. 2023, pp. 1–6. doi: 10.1145/3544549.3585726.
    4. R. S. Skukies and B. Ehinger, “The effect of estimation time window length on overlap correction in EEG data,” Conference on Cognitive Computational Neuroscience, 2023, doi: 10.32470/CCN.2023.1229-0.
    5. L. R. Skreinig et al., “guitARhero: Interactive Augmented Reality Guitar Tutorials,” IEEE Transactions on Visualization and Computer Graphics, pp. 1–10, 2023, doi: 10.1109/TVCG.2023.3320266.
    6. T. Siebert et al., “Die Reflexaktivität der Halsmuskulatur bei seitlichen Fahrmanövern im Fahrsimulator,” J. E.-N. Kerstin Witte, Stefan Pastel, Ed., Steinbeis-Edition, Stuttgart, 2023.
    7. A. Schmitz-Hübsch, R. Becker, and M. Wirzberger, “Personality Traits in the Emotion-Performance-Relationship in Intelligent Tutoring Systems,” in Adaptive Instructional Systems. HCII 2023. Lecture Notes in Computer Science, in Adaptive Instructional Systems. HCII 2023. Lecture Notes in Computer Science. , Springer, 2023, pp. 60–75. doi: 10.1007/978-3-031-34735-1_5.
    8. S. Rigling, X. Yu, and M. Sedlmair, “‘In Your Face!’: Visualizing Fitness Tracker Data in Augmented Reality,” in Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, in Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems. Hamburg, Germany: Association for Computing Machinery, Apr. 2023, pp. 1–7. doi: 10.1145/3544549.3585912.
    9. J. Rettberg et al., “Replication Data for: Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar.” 2023. doi: 10.18419/darus-3248.
    10. D. Pfeifer, J. Scheid, J. Kneifl, and J. Fehr, “An improved development process of production plants using digital twins with extended dynamic behaviour in virtual commissioning and control – Simulation@Operations,” Proceedings in Applied Mathematics & Mechanics, 2023, doi: 10.1002/pamm.202300225.
    11. D. Pfeifer, A. Baumann, M. Giani, C. Scheifele, and J. Fehr, “Hybrid Digital Twins Using FMUs to Increase the Validity and Domain of Virtual Commissioning Simulations,” in Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains, in Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains. Springer, 2023. doi: 10.1007/978-3-031-27933-1_19.
    12. A. R. Nikolaev, B. V. Ehinger, R. N. Meghanathan, and C. van Leeuwen, “Planning to revisit: Neural activity in refixation precursors,” Journal of Vision, vol. 23, no. 7, Art. no. 7, Jul. 2023, doi: 10.1167/jov.23.7.2.
    13. M. Millard, F. Kempter, N. Stutzig, T. Siebert, and J. Fehr, “Improving the Accuracy of Musculotendon Models for the Simulation of Active Lengthening,” in Proceedings of the IRCOBI Conference, in Proceedings of the IRCOBI Conference. Cambridge, UK, 2023.
    14. J. Kneifl, D. Rosin, O. Röhrle, and J. Fehr, “Low-dimensional Data-based Surrogate Model of a Continuum-mechanical Musculoskeletal System Based on Non-intrusive Model Order Reduction.” arXiv, 2023. doi: 10.48550/ARXIV.2302.06528.
    15. J. Kneifl, D. Rosin, O. Avci, O. Röhrle, and J. C. Fehr, “Continuum-mechanical Forward Simulation Results of a Human Upper-limb Model Under Varying Muscle Activations.” 2023. doi: 10.18419/darus-3302.
    16. J. Kneifl, D. Rosin, O. Avci, O. Röhrle, and J. Fehr, “Low-dimensional data-based surrogate model of a continuum-mechanical musculoskeletal system based on non-intrusive model order reduction,” Archive of applied mechanics, vol. 93, pp. 3637–3663, 2023, doi: 10.1007/s00419-023-02458-5.
    17. J. Kneifl and J. Fehr, “Crash Simulations of a Racing Kart’s Structural Frame Colliding against a Rigid Wall.” DaRUS, 2023. doi: 10.18419/DARUS-3789.
    18. F. Kempter, L. Lantella, N. Stutzig, J. C. Fehr, and T. Siebert, “Neck Reflex Behavior in Driving Simulator Experiments - Academic-Scale Simulator at ITM.” 2023. doi: 10.18419/darus-3000.
    19. N. Hube, M. Reinelt, K. Vidackovic, and M. Sedlmair, “Work vs. Leisure – Differences in Avatar Characteristics Depending on Social Situations,” in Proceeding of the 16th International Symposium on Visual Information Communication and Interaction (VINCI ’23), in Proceeding of the 16th International Symposium on Visual Information Communication and Interaction (VINCI ’23). Association for Computing Machinery, 2023. doi: https://doi.org/10.1145/3615522.3615537.
    20. J. Hay et al., “Application of data-driven surrogate models for active human model response prediction and restraint system optimization,” Frontiers in applied mathematics and statistics, vol. 9, pp. 1–16, 2023, doi: 10.3389/fams.2023.1156785.
    21. J. Haischt and M. Sedlmair, “What’s (Not) Tracking? Factors of Influence in Industrial Augmented Reality Tracking: A Use Case Study in an Automotive Environment,” in Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, in Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. Ingolstadt, Germany: Association for Computing Machinery, Sep. 2023, pp. 42–51. doi: 10.1145/3580585.3607156.
    22. F. Grioui and T. Blascheck, “Heart Rate Visualizations on a Virtual Smartwatch to Monitor Physical Activity Intensity,” in Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, in Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SCITEPRESS - Science and Technology Publications, 2023. doi: 10.5220/0011665500003417.
    23. P. Gebhardt et al., “Auxiliary Means to Improve Motion Guidance Memorability in Extended Reality,” in 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), in 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). Mar. 2023, pp. 689–690. doi: 10.1109/VRW58643.2023.00187.
    24. R. Frömer, M. R. Nassar, B. V. Ehinger, and A. Shenhav, “Common neural choice signals emerge artifactually amidst multiple distinct value signals,” bioRxiv, 2023, doi: 10.1101/2022.08.02.502393.
    25. N. Fahse, M. Millard, F. Kempter, S. Maier, M. Roller, and J. Fehr, “Dynamic Human Body Models in Vehicle Safety: An Overview,” GAMM-Mitteilungen, vol. 46, no. 2, Art. no. 2, 2023, doi: 10.1002/gamm.202300007.
    26. H. Bonasch and B. V. Ehinger, “Decoding accuracies as well as ERP amplitudes do not show between-task correlations,” Conference on Cognitive Computational Neuroscience, 2023, doi: 10.32470/CCN.2023.1029-0.
  2. 2022

    1. Q. Zhou, J. Fehr, D. Bestle, and X. Rui, “Simulation of generally shaped 3D elastic body dynamics with large motion using transfer matrix method incorporating model order reduction,” Multibody System Dynamics, vol. 59, no. 3, Art. no. 3, 2022, doi: 10.1007/s11044-022-09869-2.
    2. B. Weder, J. Barzen, F. Leymann, and D. Vietz, “Quantum Software Development Lifecycle,” in Quantum Software Engineering, M. A. Serrano, R. Pérez-Castillo, and M. Piattini, Eds., in Quantum Software Engineering. , Springer International Publishing, 2022, pp. 61--83. doi: 10.1007/978-3-031-05324-5_4.
    3. B. Weder, J. Barzen, M. Beisel, and F. Leymann, “Analysis and Rewrite of Quantum Workflows: Improving the Execution of Hybrid Quantum Algorithms,” in Proceedings of the 12th International Conference on Cloud Computing and Services Science (CLOSER 2022), in Proceedings of the 12th International Conference on Cloud Computing and Services Science (CLOSER 2022). SciTePress, Apr. 2022, pp. 38--50. doi: 10.5220/0011035100003200.
    4. A. Sousa Calepso, N. Hube, N. Berenguel Senn, V. Brandt, and M. Sedlmair, “cARdLearner: Using Expressive Virtual Agents when Learning Vocabulary in Augmented Reality,” in ACM Conference on Human Factors in Computing Systems Extended Abstracts (CHI-EA)), in ACM Conference on Human Factors in Computing Systems Extended Abstracts (CHI-EA)). New Orleans, LA, USA, 2022. doi: 10.1145/3491101.3519631.
    5. L. R. Skreinig et al., “AR Hero: Generating Interactive Augmented Reality Guitar Tutorials,” in 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), in 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). Mar. 2022, pp. 395–401. doi: 10.1109/VRW55335.2022.00086.
    6. J. Rettberg et al., “Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar.” 2022. doi: https://doi.org/10.48550/arXiv.2203.10061.
    7. S. Oppold and M. Herschel, “Provenance-based explanations: are they useful?,” in International Workshop on the Theory and Practice  of Provenance (TAPP), in International Workshop on the Theory and Practice  of Provenance (TAPP). 2022, pp. 2:1--2:4. doi: 10.1145/3530800.3534529.
    8. J. Nicodemus, J. Kneifl, J. Fehr, and B. Unger, “Physics-informed Neural Networks-based Model Predictive Control for Multi-link Manipulators,” IFAC-PapersOnLine, vol. 55, no. 20, Art. no. 20, 2022, doi: 10.1016/j.ifacol.2022.09.117.
    9. D. Lieb, “Advanced neural network architectures for continuum biomechanical simulation surrogates.” 2022.
    10. J. Kneifl, J. Hay, and J. Fehr, “Human Occupant Motion in Pre-Crash Scenario.” 2022. doi: 10.18419/darus-2471.
    11. N. Hube, K. Vidackovic, and M. Sedlmair, “Using Expressive Avatars to Increase Emotion Recognition: A Pilot Study,” in Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems, in Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems. New Orleans, LA, USA: Association for Computing Machinery, Apr. 2022, pp. 1–7. doi: 10.1145/3491101.3519822.
    12. N. Hube, A. Achberger, P. Liepert, J. Vogelsang, K. Vidačković, and M. Sedlmair, “Study on the Influence of Upper Limb Representations and Haptic Feedback in Virtual Reality,” in 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), in 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). Oct. 2022, pp. 802–807. doi: 10.1109/ISMAR-Adjunct57072.2022.00172.
    13. S. Hermann and J. C. Fehr, “Documenting Research Software in Engineering Science,” Research Square, 2022, doi: 10.21203/rs.3.rs-1239393/v1.
    14. A. L. Gert, B. V. Ehinger, S. Timm, T. C. Kietzmann, and P. König, “WildLab: A naturalistic free viewing experiment reveals previously unknown electroencephalography signatures of face processing,” European Journal of Neuroscience, vol. 56, no. 11, Art. no. 11, Nov. 2022, doi: 10.1111/ejn.15824.
    15. P. Gebhardt, X. Yu, A. Köhn, and M. Sedlmair, “MolecuSense: Using Force-Feedback Gloves for Creating and Interacting with Ball-and-Stick Molecules in VR,” in Proceedings of the 15th International Symposium on Visual Information Communication and Interaction, in Proceedings of the 15th International Symposium on Visual Information Communication and Interaction. Chur, Switzerland: Association for Computing Machinery, Oct. 2022, pp. 1–5. doi: 10.1145/3554944.3554956.
    16. J. Eirich, M. Münch, D. Jäckle, M. Sedlmair, J. Bonart, and T. Schreck, “RfX: A Design Study for the Interactive Exploration of a Random Forest to Enhance Testing Procedures for Electrical Engines,” Computer Graphics Forum, vol. 41, no. 6, Art. no. 6, Mar. 2022, doi: 10.1111/cgf.14452.
  3. 2021

    1. B. Weder, J. Barzen, F. Leymann, M. Salm, and K. Wild, “QProv: A provenance system for quantum computing,” IET Quantum Communication, vol. 2, no. 4, Art. no. 4, Jun. 2021, doi: 10.1049/qtc2.12012.
    2. B. Weder, J. Barzen, F. Leymann, and M. Salm, “Automated Quantum Hardware Selection for Quantum Workflows,” Electronics, vol. 10, no. 8, Art. no. 8, Apr. 2021, doi: 10.3390/electronics10080984.
    3. M. Salm, J. Barzen, F. Leymann, B. Weder, and K. Wild, “Automating the Comparison of Quantum Compilers for Quantum Circuits,” in Proceedings of the 15th Symposium and Summer School on Service-Oriented Computing (SummerSOC 2021), in Proceedings of the 15th Symposium and Summer School on Service-Oriented Computing (SummerSOC 2021). Springer, 2021, pp. 64–80. doi: 10.1007/978-3-030-87568-8_4.
    4. J. Kühnert, D. Göddeke, and M. Herschel, “Provenance-integrated parameter selection and optimization in numerical simulations,” in International Workshop on the Theory and Practice of Provenance (TAPP), in International Workshop on the Theory and Practice of Provenance (TAPP). USENIX Association, 2021.
    5. K. Képes, F. Leymann, B. Weder, and K. Wild, “SiDD: The Situation-Aware Distributed Deployment System,” in Service-Oriented Computing  -- ICSOC 2020 Workshops, H. Hacid, F. Outay, H. Paik, A. Alloum, M. Petrocchi, M. R. Bouadjenek, A. Beheshti, X. Liu, and A. Maaradji, Eds., in Service-Oriented Computing  -- ICSOC 2020 Workshops. Springer International Publishing, 2021, pp. 72--76.
    6. J. Kneifl, D. Grunert, and J. Fehr, “A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning,” International Journal for Numerical Methods in Engineering, Apr. 2021, doi: 10.1002/nme.6712.
    7. J. Kneifl and J. Fehr, “Machine Learning Algorithms for Learning Nonlinear Terms of Reduced Mechanical Models in Explicit Structural Dynamics,” PAMM, vol. 20, no. S1, Art. no. S1, Mar. 2021, doi: 10.1002/pamm.202000353.
    8. F. Kempter, C. Kleinbach, M. Staudenmeyer, and J. C. Fehr, “An Active Female Human Body Model for Simulation of Rear-End Impact Scenarios,” in 91st Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), in 91st Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM). Wiley, 2021, p. e202000068. doi: 10.1002/pamm.202000068.
    9. F. Grioui and T. Blascheck, Study of Heart Rate Visualizations on a Virtual Smartwatch. in Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology. ACM, 2021. doi: https://doi.org/10.1145/3489849.3489913.
    10. J. Fehr, C. Himpe, S. Rave, and J. Saak, “Sustainable Research Software Hand-Over,” Journal of Open Research Software, vol. 9, no. 5, Art. no. 5, 2021, doi: 10.5334/jors.307.
    11. R. Diestelkämper, S. Lee, M. Herschel, and B. Glavic, “To not miss the forest for the trees - A holistic approach for explaining missing answers over nested data,” in In Proceedins of the ACM SIG Conference on the Management of Data (SIGMOD), in In Proceedins of the ACM SIG Conference on the Management of Data (SIGMOD). 2021.
    12. A. Czeszumski et al., “Coordinating With a Robot Partner Affects Neural Processing Related to Action Monitoring,” Frontiers in Neurorobotics, vol. 15, Aug. 2021, doi: 10.3389/fnbot.2021.686010.
  4. 2020

    1. M. Zimmermann, U. Breitenbücher, K. Képes, F. Leymann, and B. Weder, “Data Flow Dependent Component Placement of Data Processing Cloud Applications,” in 2020 IEEE International Conference on Cloud Engineering (IC2E), in 2020 IEEE International Conference on Cloud Engineering (IC2E). Apr. 2020, pp. 83–94. doi: 10.1109/IC2E48712.2020.00016.
    2. X. Yu, K. Angerbauer, P. Mohr, D. Kalkofen, and M. Sedlmair, “Perspective Matters: Design Implications for Motion Guidance in Mixed Reality,” in Proceedings of the IEEE 19th International Symposium on Mixed and Augmented Reality, in Proceedings of the IEEE 19th International Symposium on Mixed and Augmented Reality. 2020.
    3. K. Wild, U. Breitenbücher, K. Képes, F. Leymann, and B. Weder, “Decentralized Cross-Organizational Application Deployment Automation: An Approach for Generating Deployment Choreographies Based on Declarative Deployment Models,” in Proceedings of the 32nd Conference on Advanced Information Systems Engineering (CAiSE 2020), in Proceedings of the 32nd Conference on Advanced Information Systems Engineering (CAiSE 2020), vol. 12127. Springer International Publishing, Jun. 2020, pp. 20--35. doi: 10.1007/978-3-030-49435-3_2.
    4. B. Weder, U. Breitenbücher, K. Képes, F. Leymann, and M. Zimmermann, “Deployable Self-Contained Workflow Models,” in Proceedings of the 8th European Conference on Service-Oriented and Cloud Computing (ESOCC 2020), in Proceedings of the 8th European Conference on Service-Oriented and Cloud Computing (ESOCC 2020). Springer International Publishing, Mar. 2020, pp. 85--96. doi: 10.1007/978-3-030-44769-4_7.
    5. B. Weder, J. Barzen, F. Leymann, M. Salm, and D. Vietz, “The Quantum Software Lifecycle,” in Proceedings of the 1st ACM SIGSOFT International Workshop on Architectures and Paradigms for Engineering Quantum Software (APEQS 2020), in Proceedings of the 1st ACM SIGSOFT International Workshop on Architectures and Paradigms for Engineering Quantum Software (APEQS 2020). ACM, Nov. 2020, pp. 2--9. doi: 10.1145/3412451.3428497.
    6. B. Weder, U. Breitenbücher, F. Leymann, and K. Wild, “Integrating Quantum Computing into Workflow Modeling and Execution,” in 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC), in 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC). Dec. 2020, pp. 279–291. doi: 10.1109/UCC48980.2020.00046.
    7. E. Sood, S. Tannert, P. Mueller, and A. Bulling, “Improving Natural Language Processing Tasks with Human Gaze-Guided Neural Attention,” in Advances in Neural Information Processing Systems, H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, and H. Lin, Eds., in Advances in Neural Information Processing Systems, vol. 33. Curran Associates, Inc., 2020, pp. 6327--6341. [Online]. Available: https://proceedings.neurips.cc/paper/2020/file/460191c72f67e90150a093b4585e7eb4-Paper.pdf
    8. E. Sood, S. Tannert, D. Frassinelli, A. Bulling, and N. T. Vu, “Interpreting Attention Models with Human Visual Attention in Machine Reading Comprehension,” in Proceedings of the 24th Conference on Computational Natural Language Learning, in Proceedings of the 24th Conference on Computational Natural Language Learning. Online: Association for Computational Linguistics, Nov. 2020, pp. 12--25. doi: 10.18653/v1/2020.conll-1.2.
    9. M. Salm, J. Barzen, F. Leymann, and B. Weder, “About a Criterion of Successfully Executing a Circuit in the NISQ Era: What $wd 1/\epsilon_eff$ Really Means,” in Proceedings of the 1st ACM SIGSOFT International Workshop on Architectures and Paradigms for Engineering Quantum Software, in Proceedings of the 1st ACM SIGSOFT International Workshop on Architectures and Paradigms for Engineering Quantum Software. ACM, Nov. 2020. doi: 10.1145/3412451.3428498.
    10. M. Salm, J. Barzen, U. Breitenbücher, F. Leymann, B. Weder, and K. Wild, “The NISQ Analyzer: Automating the Selection of Quantum Computers for Quantum Algorithms,” in Proceedings of the 14th Symposium and Summer School on Service-Oriented Computing (SummerSOC 2020), in Proceedings of the 14th Symposium and Summer School on Service-Oriented Computing (SummerSOC 2020). Springer International Publishing, Dec. 2020, pp. 66--85. doi: 10.1007/978-3-030-64846-6_5.
    11. P. Müller, E. Sood, and A. Bulling, “Anticipating Averted Gaze in Dyadic Interactions,” in ACM Symposium on Eye Tracking Research and Applications, in ACM Symposium on Eye Tracking Research and Applications. Stuttgart, Germany: Association for Computing Machinery, Jun. 2020, pp. 1–10. doi: 10.1145/3379155.3391332.
    12. J. Kneifl and J. Fehr, “Machine Learning Algorithms for Learning Nonlinear Terms of Reduced Mechanical Models in Explicit Structural Dynamics,” Proceedings in Applied Mathematics and Mechanics, 2020, doi: 10.1002/pamm.202000353.
    13. F. Kempter, F. Bechler, and J. Fehr, “Calibration Approach for Muscle Activated Human Models in Pre-Crash Maneuvers with a Driver-in-the-Loop Simulator,” in Proceedings in 6th Digital Human Modeling Symposium, in Proceedings in 6th Digital Human Modeling Symposium. Skövde, Sweden, 2020. doi: 10.3233/ATDE200029.
    14. R. Diestelkämper and M. Herschel, “Tracing nested data with structural provenance for big data analytics,” in Proceedings of the International Conference on Extending Database Technology (EDBT), in Proceedings of the International Conference on Extending Database Technology (EDBT). 2020, pp. 253–264. doi: 10.5441/002/edbt.2020.23.
    15. R. Diestelkämper and M. Herschel, “Distributed Tree-Pattern Matching in Big Data Analytics Systems,” in In Proceedings of the Conference on Advances in Databases and Information Systems (ADBIS), in In Proceedings of the Conference on Advances in Databases and Information Systems (ADBIS). Springer, 2020, pp. 171–186. doi: https://doi.org/10.1007/978-3-030-54832-2_14.
  5. 2019

    1. L. Harzenetter, U. Breitenbücher, F. Leymann, K. Saatkamp, B. Weder, and M. Wurster, “Automated Generation of Management Workflows for Applications Based on Deployment Models,” in 2019 IEEE 23rd International Enterprise Distributed Object Computing Conference (EDOC), in 2019 IEEE 23rd International Enterprise Distributed Object Computing Conference (EDOC). Oct. 2019, pp. 216–225. doi: 10.1109/EDOC.2019.00034.

Project Network Coordinators

This image shows Melanie Herschel

Melanie Herschel

Prof. Dr. rer. nat.

Data Engineering

This image shows Michael Sedlmair

Michael Sedlmair

Prof. Dr.

Virtual Reality and Augmented Reality

[Photo: SimTech/Max Kovalenko]

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