Prof. Dr. Patrick Zschech

Assistant Professorship for Intelligent Information Systems

Curriculum vitae

Patrick Zschech studied Business Informatics in the Bachelor and Master program at the Technische Universität Dresden (TUD) from 2008 to 2015. In the meantime, he spent a year abroad at the Universidad de Granada (UGR) in Andalusia from 2010 to 2011. After completing his Master’s degree, he worked until 2018 for the IT service provider Robotron Datenbank-Software GmbH as an instructor and project member to establish innovative data science qualification programs and to develop new solution concepts in the area of (Industrial) Internet of Things. At the same time, he worked as a research assistant at the Chair of Business Informatics, esp. Business Intelligence Research, at TUD, where he successfully completed his doctorate on the topic “Data Science and Analytics in Industrial Maintenance” in August 2020. In January 2021, Patrick Zschech was appointed Assistant Professor for Intelligent Information Systems at the Institute of Information Systems at FAU.

Patrick Zschech’s research focuses on business analytics, machine learning, and artificial intelligence. In particular, he is concerned with the design, analysis, and use of intelligent information systems based on methods and technologies of advanced data processing (e.g., deep learning, computer vision, natural language processing, process mining). One of the main areas of interest for conducting and applying his research is the field of industrial manufacturing. In addition, he deals with the analysis and design of data science qualification programs and he investigates approaches for increasing acceptance of AI systems from a socio-technical perspective.

2024

Bohlen L., Rosenberger J., Zschech P., Kraus M.:
Leveraging interpretable machine learning in intensive care
In: Annals of Operations Research (2024)
ISSN: 0254-5330
DOI: 10.1007/s10479-024-06226-8
Drobnitzky M., Friederich J., Egger B., Zschech P.:
Survey and systematization of 3D object detection models and methods
In: Visual Computer 40 (2024), p. 1867-1913
ISSN: 0178-2789
DOI: 10.1007/s00371-023-02891-1
Kruschel S., Hambauer N., Weinzierl S., Zilker S., Kraus M., Zschech P.:
Challenging the performance-interpretability trade-off: An evaluation of interpretable machine learning models (forthcoming)
In: Business & Information Systems Engineering (2024)
ISSN: 1867-0202
Rosenberger J., Kuhlemann S., Tiefenbeck V., Kraus M., Zschech P.:
The Impact of Transparency in AI Systems on Users’ Data-Sharing Intentions: A Scenario-Based Experiment
19. Internationale Tagung Wirtschaftsinformatik (Würzburg, 16. September 2024 - 19. September 2024)
Weinzierl S., Zilker S., Zschech P., Kraus M., Leibelt T., Matzner M.:
How risky is my AI system? A method for transparent classification of AI system descriptions by regulated AI risk categories
International Conference on Information Systems (Bangkok, Thailand)
In: Proceedings of the 45th International Conference on Information Systems 2024
URL: https://open.fau.de/bitstreams/092b306d-86fb-420d-8ba1-57172d11611a/download
Wissuchek C., Zschech P.:
Prescriptive analytics systems revised: a systematic literature review from an information systems perspective
In: Information Systems and E-Business Management (2024)
ISSN: 1617-9846
DOI: 10.1007/s10257-024-00688-w
Zilker S., Weinzierl S., Kraus M., Zschech P., Matzner M.:
A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis
In: Health Care Management Science 27 (2024), p. 136-167
ISSN: 1386-9620
DOI: 10.1007/s10729-024-09673-8
URL: https://link.springer.com/article/10.1007/s10729-024-09673-8#article-info

2023

Feuerriegel S., Hartmann J., Janiesch C., Zschech P.:
Generative AI
In: Business & Information Systems Engineering (2023)
ISSN: 1867-0202
DOI: 10.1007/s12599-023-00834-7
Kraus M., Tschernutter D., Weinzierl S., Zschech P.:
Interpretable generalized additive neural networks
In: European Journal of Operational Research (2023)
ISSN: 0377-2217
DOI: 10.1016/j.ejor.2023.06.032
Schoormann T., Strobel G., Möller F., Petrik D., Zschech P.:
Artificial Intelligence for Sustainability—A Systematic Review of Information Systems Literature
In: Communications of the Association for Information Systems 52 (2023), Article No.: 8
ISSN: 1529-3181
DOI: 10.17705/1cais.05209
URL: https://aisel.aisnet.org/cais/vol52/iss1/8/
Zilker S., Weinzierl S., Zschech P., Kraus M., Matzner M.:
Best of both worlds: Combining predictive power with interpretable and explainable results for patient pathway prediction
European Conference on Information Systems (Kristiansand, 13. June 2023 - 16. June 2023)
In: Proceedings of the 31st European Conference on Information Systems 2023
DOI: 10.25593/open-fau-1123
URL: https://open.fau.de/bitstreams/c8ea3d7e-7fb9-4932-9828-501af75d1f89/download
Zipfel J., Verworner F., Fischer M., Wieland U., Kraus M., Zschech P.:
Anomaly detection for industrial quality assurance: A comparative evaluation of unsupervised deep learning models
In: Computers & Industrial Engineering 177 (2023), Article No.: 109045
ISSN: 0360-8352
DOI: 10.1016/j.cie.2023.109045

2022

Graf J., Lancho G., Zschech P., Heinrich K.:
Where Was COVID-19 First Discovered? Designing a Question-Answering System for Pandemic Situations
European Conference on Information Systems (Timisoara, 18. June 2022 - 24. June 2022)
In: Proceedings of the 30th European Conference on Information Systems 2022
URL: https://aisel.aisnet.org/ecis2022_rp/104/
Harl M., Herchenbach M., Kruschel S., Hambauer N., Zschech P., Kraus M.:
A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
In: Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI) 2022
Open Access: https://aisel.aisnet.org/wi2022/student_track/student_track/33/
URL: https://aisel.aisnet.org/wi2022/student_track/student_track/33/
Sager C., Zschech P., Kühl N.:
labelCloud: A Lightweight Labeling Tool for Domain-Agnostic 3D Object Detection in Point Clouds
In: Computer-Aided Design and Applications 19 (2022), p. 1191-1206
ISSN: 1686-4360
DOI: 10.14733/cadaps.2022.1191-1206
URL: http://cad-journal.net/files/vol_19/CAD_19(6)_2022_1191-1206.pdf
Siebers P., Janiesch C., Zschech P.:
A Survey of Text Representation Methods and Their Genealogy
In: IEEE Access 10 (2022), p. 96492-96513
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2022.3205719
Zschech P.:
Beyond descriptive taxonomies in data analytics: a systematic evaluation approach for data-driven method pipelines
In: Information Systems and E-Business Management (2022)
ISSN: 1617-9846
DOI: 10.1007/s10257-022-00577-0
Zschech P.:
Beyond descriptive taxonomies in data analytics: a systematic evaluation approach for data-driven method pipelines
In: Information Systems and E-Business Management (2022)
ISSN: 1617-9846
DOI: 10.1007/s10257-022-00577-0
Zschech P., Weinzierl S., Hambauer N., Zilker S., Kraus M.:
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
European Conference on Information Systems (Timisoara, 5. July 2022 - 9. July 2022)
In: Proceedings of the 30th European Conference on Information Systems 2022

2021

Heinrich K., Zschech P., Janiesch C., Bonin M.:
Process Data Properties Matter: Introducing Gated Convolutional Neural Networks (GCNN) and Key-Value-Predict Attention Networks (KVP) for Next Event Prediction with Deep Learning
In: Decision Support Systems (2021), p. 113494
ISSN: 0167-9236
DOI: 10.1016/j.dss.2021.113494
URL: https://www.sciencedirect.com/science/article/pii/S016792362100004X?via=ihub
Janiesch C., Zschech P., Heinrich K.:
Machine Learning and Deep Learning
In: Electronic Markets 31 (2021), p. 685–695
ISSN: 1019-6781
DOI: 10.1007/s12525-021-00475-2
URL: https://link.springer.com/article/10.1007/s12525-021-00475-2
Petrik D., Pantow K., Zschech P., Herzwurm G.:
Tweeting in IIoT Ecosystems – Empirical Insights from Social Media Analytics about IIoT Platforms
16th International Conference on Wirtschaftsinformatik (WI) (Duisburg-Essen, 9. March 2021 - 11. March 2021)
In: Ahlemann F., Schütte R., Stieglitz S. (ed.): Proceedings of the 16th International Conference on Wirtschaftsinformatik (WI) 2021
DOI: 10.1007/978-3-030-86800-0_32
URL: https://aisel.aisnet.org/wi2021/GFuture18/Track18/3/
Sager C., Janiesch C., Zschech P.:
A Survey of Image Labelling for Computer Vision Applications
In: Journal of Business Analytics 4 (2021), p. 91-110
ISSN: 2573-234X
DOI: 10.1080/2573234X.2021.1908861
Sager C., Zschech P., Kühl N.:
labelCloud: A Lightweight Domain-Independent Labeling Tool for 3D Object Detection in Point Clouds
International CAD Conference (Barcelona, 5. July 2021 - 7. July 2021)
In: Proceedings of CAD’21 2021
DOI: 10.14733/cadconfP.2021.319-323
Zschech P., Heinrich K., Möller B., Breithaupt L., Maresch J., Roth A.:
Deep Learning in der Landwirtschaft – Analyse eines Weinbergs
In: D'Onofrio S., Meier A. (ed.): Big Data Analytics, 2021, p. 169-194
ISBN: 9783658322359
DOI: 10.1007/978-3-658-32236-6_8
URL: https://link.springer.com/chapter/10.1007/978-3-658-32236-6_8
Zschech P., Sager C., Siebers P., Pertermann M.:
Mit Computer Vision zur automatisierten Qualitätssicherung in der industriellen Fertigung: Eine Fallstudie zur Klassifizierung von Fehlern in Solarzellen mittels Elektrolumineszenz-Bildern
In: HMD : Praxis der Wirtschaftsinformatik (2021), p. 321–342
ISSN: 1436-3011
DOI: 10.1365/s40702-020-00641-8
URL: https://link.springer.com/article/10.1365/s40702-020-00641-8
Zschech P., Walk J., Heinrich K., Vössing M., Kühl N.:
A Picture is Worth a Collaboration: Accumulating Design Knowledge for Computer-Vision-based Hybrid Intelligence Systems
29th European Conference on Information Systems (ECIS) (Virtual Conference, 14. June 2021 - 16. June 2021)
In: Proceedings of the 29th European Conference on Information Systems (ECIS) 2021
URL: https://aisel.aisnet.org/ecis2021_rp/127/

2020

Friederich J., Zschech P.:
Review and Systematization of Solutions for 3D Object Detection
15th International Conference on Wirtschaftsinformatik (WI) (Potsdam, 8. March 2020 - 11. March 2020)
In: Gronau N, Heine M, Krasnova H, Pousttchi K (ed.): Proceedings of the 15th International Conference on Wirtschaftsinformatik, Berlin: 2020
DOI: 10.30844/wi_2020_r2-friedrich
URL: https://library.gito.de/oa_wi2020-r2.html
Heinrich K., Graf J., Chen J., Laurisch J., Zschech P.:
Fool Me Once, Shame On You, Fool Me Twice, Shame On Me: A Taxonomy of Attack and Defense Patterns for AI Security
28th European Conference on Information Systems (ECIS) (Virtual Conference, 15. June 2020 - 17. June 2020)
In: Association for Information Systems (ed.): Proceedings of the 28th European Conference on Information Systems 2020
URL: https://aisel.aisnet.org/ecis2020_rp/166/
Heinrich K., Zschech P., Janiesch C., Bonin M.:
Ein Vergleich aktueller Deep-Learning-Architekturen zur Prognose von Prozessverhalten
15th International Conference on Wirtschaftsinformatik (WI) (Potsdam, 8. March 2020 - 11. March 2020)
In: Gronau N, Heine M, Krasnova H, Pousttchi K (ed.): Proceedings of the 15th International Conference on Wirtschaftsinformatik, Berlin: 2020
DOI: 10.30844/wi_2020_i1-heinrich
URL: https://library.gito.de/oa_wi2020-i1.html
Wanner J., Heinrich K., Janiesch C., Zschech P.:
How Much AI Do You Require? Decision Factors for Adopting AI Technology
41st International Conference on Information Systems (ICIS) (Virtual Conference, 13. December 2020 - 16. December 2020)
In: Association for Information Systems (ed.): Proceedings of the 41st International Conference on Information Systems 2020
URL: https://aisel.aisnet.org/icis2020/implement_adopt/implement_adopt/10/
Wanner J., Herm LV., Heinrich K., Janiesch C., Zschech P.:
White, Grey, Black: Effects of XAI Augmentation on the Confidence in AI-based Decision Support Systems
40th International Conference on Information Systems (ICIS) (Virtual Conference, 13. December 2020 - 16. December 2020)
In: Association for Information Systems (ed.): Proceedings of the 40th International Conference on Information Systems 2020
URL: https://aisel.aisnet.org/icis2020/hci_artintel/hci_artintel/14/
Zschech P.:
Data Science and Analytics in Industrial Maintenance: Selection, Evaluation, and Application of Data-Driven Methods (Dissertation, 2020)
URL: https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-723182
Zschech P., Horn R., Hoeschele D., Janiesch C., Heinrich K.:
Intelligent User Assistance for Automated Data Mining Method Selection
In: Business & Information Systems Engineering 62 (2020), p. 227-247
ISSN: 1867-0202
DOI: 10.1007/s12599-020-00642-3
URL: https://link.springer.com/article/10.1007/s12599-020-00642-3

2019

Heinrich K., Möller B., Janiesch C., Zschech P.:
Is Bigger Always Better? Lessons Learnt from the Evolution of Deep Learning Architectures for Image Classification
Pre-ICIS SIGDSA Symposium (Munich, 14. December 2019 - 15. December 2019)
In: Proceedings of the Pre-ICIS SIGDSA Symposium 2019
URL: https://aisel.aisnet.org/sigdsa2019/20/
Heinrich K., Roth A., Zschech P.:
Everything Counts: A Taxonomy of Deep Learning Approaches for Object Counting
27th European Conference on Information Systems (ECIS) (Stockholm & Uppsala, 8. June 2019 - 14. June 2019)
In: Proceedings of the 27th European Conference on Information Systems 2019
URL: https://aisel.aisnet.org/ecis2019_rp/63/
Heinrich K., Zschech P., Möller B., Breithaupt L., Maresch J.:
Objekterkennung im Weinanbau – Eine Fallstudie zur Unterstützung von Winzertätigkeiten mithilfe von Deep Learning
In: HMD : Praxis der Wirtschaftsinformatik 56 (2019), p. 964-985
ISSN: 1436-3011
DOI: 10.1365/s40702-019-00514-9
URL: https://link.springer.com/article/10.1365/s40702-019-00514-9
Heinrich K., Zschech P., Skouti T., Griebenow J., Riechert S.:
Demystifying the Black Box: A Classification Scheme for Interpretation and Visualization of Deep Intelligent Systems
25th Americas Conference on Information Systems (AMCIS) (Cancún, 15. August 2019 - 17. August 2019)
In: Proceedings of the 25th Americas Conference on Information Systems 2019
URL: https://aisel.aisnet.org/amcis2019/ai_semantic_for_intelligent_info_systems/ai_semantic_for_intelligent_info_systems/8/
Horn R., Zschech P.:
Application of Process Mining Techniques to Support Maintenance-Related Objectives
14th International Conference on Wirtschaftsinformatik (WI) (Siegen, 23. February 2019 - 27. February 2019)
In: Ludwig T, Pipek V (ed.): Proceedings of the 14th International Conference on Wirtschaftsinformatik, Siegen: 2019
DOI: 10.25819/ubsi/1016
URL: https://aisel.aisnet.org/wi2019/specialtrack01/papers/6/
Zschech P., Bernien J., Heinrich K.:
Towards a Taxonomic Benchmarking Framework for Predictive Maintenance: The Case of NASA’s Turbofan Degradation
40th International Conference on Information Systems (ICIS) (München, 15. December 2019 - 18. December 2019)
In: Proceedings of the 40th International Conference on Information Systems 2019
URL: https://aisel.aisnet.org/icis2019/data_science/data_science/4/
Zschech P., Heinrich K., Bink R., Neufeld JS.:
Prognostic Model Development with Missing Labels: A Condition-Based Maintenance Approach Using Machine Learning
In: Business & Information Systems Engineering 61 (2019), p. 327-343
ISSN: 1867-0202
DOI: 10.1007/s12599-019-00596-1
URL: https://link.springer.com/article/10.1007/s12599-019-00596-1
Zschech P., Heinrich K., Horn R., Hoeschele D.:
Towards a Text-based Recommender System for Data Mining Method Selection
25th Americas Conference on Information Systems (AMCIS) (Cancún, 15. August 2019 - 17. August 2019)
In: Proceedings of the 25th Americas Conference on Information Systems 2019
URL: https://aisel.aisnet.org/amcis2019/ai_semantic_for_intelligent_info_systems/ai_semantic_for_intelligent_info_systems/4/

2018

Bink R., Zschech P.:
Predictive Maintenance in der industriellen Praxis: Entwicklung eines Prognoseansatzes unter eingeschränkter Informationslage
In: HMD : Praxis der Wirtschaftsinformatik 55 (2018), p. 552-565
ISSN: 1436-3011
DOI: 10.1365/s40702-017-0378-2
URL: https://link.springer.com/article/10.1365/s40702-017-0378-2
Könning M., Heinrich K., Zschech P., Leyh C.:
Analyzing Influences on Pivotal ITO Contract Features: A Quantitative Multi-Study Design with Evidence from Western Europe
24th Americas Conference on Information Systems (AMCIS) (New Orleans, 16. August 2018 - 18. August 2018)
In: Proceedings of the 24th Americas Conference on Information Systems 2018
URL: https://aisel.aisnet.org/amcis2018/OrgTrasfm/Presentations/17/
Stefani K., Zschech P.:
Constituent Elements for Prescriptive Analytics Systems
26th European Conference on Information Systems (ECIS) (Portsmouth, 23. June 2018 - 28. June 2018)
In: Proceedings of the 26th European Conference on Information Systems 2018
URL: https://aisel.aisnet.org/ecis2018_rp/39/
Zschech P.:
A Taxonomy of Recurring Data Analysis Problems in Maintenance Analytics
26th European Conference on Information Systems (ECIS) (Portsmouth, 23. June 2018 - 28. June 2018)
In: Proceedings of the 26th European Conference on Information Systems 2018
URL: https://aisel.aisnet.org/ecis2018_rp/197/
Zschech P., Fleißner V., Baumgärtel N., Hilbert A.:
Data Science Skills and Enabling Enterprise Systems: Eine Erhebung von Kompetenzanforderungen und Weiterbildungsangeboten
In: HMD : Praxis der Wirtschaftsinformatik 55 (2018), p. 163-181
ISSN: 1436-3011
DOI: 10.1365/s40702-017-0376-4
URL: https://link.springer.com/article/10.1365/s40702-017-0376-4

2017

Zschech P., Heinrich K., Pfitzner M., Hilbert A.:
Are You Up for the Challenge? Towards the Development of a Big Data Capability Assessment Model
25th European Conference on Information Systems (ECIS) (Guimarães, 5. June 2017 - 10. June 2017)
In: Proceedings of the 25th European Conference on Information Systems 2017
URL: https://aisel.aisnet.org/ecis2017_rip/14/
Zschech P., Pfitzner M., Hilbert A.:
Vom Controller zum Prozessanalysten
In: Controlling & Management Review 61 (2017), p. 24-33
ISSN: 2195-8262
DOI: 10.1007/s12176-017-0031-5

2016

Hilbert A., Zschech P.:
Process Analytics
In: Das Wirtschaftsstudium 45 (2016), p. 942 - 948
ISSN: 0340-3084
Schumann C., Zschech P., Hilbert A.:
Das aufstrebende Berufsbild des Data Scientist: Vom Kompetenzwirrwarr zu spezifischen Anforderungsprofilen
In: HMD : Praxis der Wirtschaftsinformatik 53 (2016), p. 453-466
ISSN: 1436-3011
DOI: 10.1365/s40702-016-0214-0
URL: https://link.springer.com/article/10.1365/s40702-016-0214-0