| Peeking into the void: Digital twins for construction site logistics T Greif, N Stein, CM Flath Computers in Industry 121, 103264, 2020 | 144 | 2020 |
| Towards a data science toolbox for industrial analytics applications CM Flath, N Stein Computers in Industry 94, 16-25, 2018 | 93 | 2018 |
| Big data on the shop-floor: sensor-based decision-support for manual processes N Stein, J Meller, CM Flath Journal of Business Economics 88, 593-616, 2018 | 36 | 2018 |
| On the objectivity, reliability, and validity of deep learning enabled bioimage analyses D Segebarth, M Griebel, N Stein, CR von Collenberg, C Martin, D Fiedler, ... Elife 9, e59780, 2020 | 31 | 2020 |
| Towards Open Production: Designing a marketplace for 3D-printing capacities N Stein, B Walter, CM Flath Proceedings of the 40th International Conference on Information Systems (ICIS), 2019 | 16 | 2019 |
| Applied image recognition: guidelines for using deep learning models in practice M Griebel, A Dürr, N Stein 14th International Conference on Wirtschaftsinformatik, 2019 | 10 | 2019 |
| Applying data science for shop-floor performance prediction N Stein, CM Flath Proceedings of the 25th European Conference on Information Systems (ECIS), 2017 | 10 | 2017 |
| Augmented Intelligence for Quality Control of Manual Assembly Processes using Industrial Wearable Systems A Krenzer, N Stein, CM Flath Proceedings of the 40th International Conference on Information Systems (ICIS), 2019 | 9 | 2019 |
| Predictive end-to-end enterprise process network monitoring F Oberdorf, M Schaschek, S Weinzierl, N Stein, M Matzner, CM Flath Business & Information Systems Engineering 65 (1), 49-64, 2023 | 8 | 2023 |
| Analytics Applications in Fashion Supply Chain Management - A Review of Literature and Practice C Stahl, N Stein, CM Flath IEEE Transactions on Engineering Management, 2021 | 8 | 2021 |
| Analytics-enabled escalation management: System development and business value assessment. F Oberdorf, N Stein, CM Flath Computers in Industry, 2021 | 8 | 2021 |
| Making the Newsvendor Smart–Order Quantity Optimization with ANNs for a Bakery Chain F Seubert, N Stein, F Taigel, A Winkelmann Proceedings of the 26th Americas Conference on Information Systems (AMCIS), 2020 | 8 | 2020 |
| Deep learning-enabled segmentation of ambiguous bioimages with deepflash2 M Griebel, D Segebarth, N Stein, N Schukraft, P Tovote, R Blum, CM Flath Nature Communications 14 (1), 1679, 2023 | 6* | 2023 |
| Neural Process Mining: Multi-Headed Predictive Process Analytics in Practice F Oberdorf, M Schaschek, N Stein, C Flath Proceedings of the 29th European Conference on Information Systems (ECIS), 2021 | 6 | 2021 |
| DeepFLaSh, a deep learning pipeline for segmentation of fluorescent labels in microscopy images D Segebarth, M Griebel, A Duerr, CR von Collenberg, C Martin, D Fiedler bioRxiv, 473199, 2018 | 6 | 2018 |
| A meta-analysis of data-driven newsvendor approaches S Buttler, A Philippi, N Stein, R Pibernik ICLR 2022 Workshop ML Evaluation Standards, 2022 | 5 | 2022 |
| Predictive Analytics for Application Management Services N Stein, CM Flath, C Boehm Proceedings of the 26th European Conference on Information Systems (ECIS), 2018 | 5 | 2018 |
| ADR for Big-Data IT Artifact Development: An Escalation Management Example F Oberdorf, N Stein, N Walk, M Griebel, CM Flath Proceedings of the 41st International Conference on Information Systems (ICIS), 2020 | 3 | 2020 |
| Decision Support for Group-based Electricity Prices in Smart Grids N Stein, CM Flath Proceedings of the 22nd Americas Conference on Information Systems (AMCIS), 2016 | 3 | 2016 |
| Smart grid analytics CM Flath, N Stein Smart grid economics and management, 173-192, 2022 | 2 | 2022 |
Christoph M. FlathJulius-Maximilians-Universität WürzburgVerified email at uni-wuerzburg.de
