uni.liPersonenverzeichnis

Assoz. Prof. Dr. Johannes Schneider

Assoziierter Professor
Data Science & Artificial Intelligence
Ausbildung
2011 — 2012

PostDoc in Informationsanalyse
IBM Research

2008 — 2011

Master of Adv. Studies in Management, Technology and Innovation
ETH Zürich

2007 — 2011

Doktorat in Informatik
ETH Zürich

2000 — 2004

MSc. in Informatik
ETH Zürich

Werdegang
seit 2016

Assistenzprofessor für Wirtschaftsinformatik
Universität Liechtenstein

seit 2015

Dozent
Universität Zürich

2014 — 2016

Forscher
ABB Corporate Research

seit 2013

Datenanalyst
Zurich Versicherung

2005 — 2006

Software Ingenieur
AutoForm Engineering

Portrait
Machine Learning Lösung in hoher Qualität zur automatischen Übersetzung von gesprochenem deutschem Dialekt nach gesprochenem Hochdeutsch
Vorstudie zur Dissertation, seit Februar 2024

Im Rahmen der Forschungsarbeit soll eine Lösung auf Basis von Machine Learning und NLP - Natural Language Processing - entwickelt werden, die automatisch gesprochenen deutschen Dialekt in Hochdeutsch ... mehr

Eine Plattform zur Verfolgung, Vorhersage und Aufrechterhaltung der Gesundheit von Batterien, die IoT-Geräte antreiben
Dissertation, seit Dezember 2023

Die Dissertation konzentriert sich auf die Entwicklung einer Plattform zur Überwachung, Vorhersage und Aufrechterhaltung der Gesundheit von Batterien, die Internet of Things (IoT)-Geräte antreiben. ... mehr

Large Language Models - Autograding & Governance for businesses
FFF-Förderprojekt, September 2023 bis Juli 2025

Dieses Projekt zielt darauf ab, das Potenzial von großen Sprachmodellen (LLMs), insbesondere Chat-GPT, in zwei Bereichen zu untersuchen: Unterstützung bei der Prüfungsbewertung und Governance von ... mehr

Towards Trustworthy AI: Validating & Explaining AI Models and Decisions
FFF-Förderprojekt, November 2021 bis Dezember 2022 (abgeschlossen)

Digitalisierung und Innovation versprechen, unser tägliches Leben zu erleichtern. Beide Trends werden maßgeblich von Technologien, Modellen und Algorithmen aus dem Bereich der Künstlichen Intelligenz ... mehr

Performance Management und Bewertungen mit Process Mining und Big Data
FL Innovationscheck, April 2021 bis September 2021 (abgeschlossen)

Im Bereich Corporate Finance zeichnet sich ein zunehmender Trend zur Einbeziehung von Daten für das Performance Management und zur Unternehmensbewertung ab. Insbesondere spielen neue Verfahren zur ... mehr

Large Scale Big Data Pattern Mining
Innosuisse, Januar 2019 bis März 2021 (abgeschlossen)

Das Projektziel ist die Weiterentwicklung von neuen intelligenten Analysefunktionen aus dem Gebiet des maschinellen Lernens. Unternehmen arbeiten heute in einem komplexen Umfeld, in dem eine Vielzahl ... mehr

Virtual Reality in Architecture
FFF-Förderprojekt, Juni 2018 bis Mai 2020 (abgeschlossen)

Virtual reality allows to perceive landscapes, cities and ``space'' in general more intensely and accurately than ordinary technologies that use conventional models of buildings and landscapes shown ... mehr

Datenbasierte Unternehmensbewertung und IPO-Leistungsvorhersage
FFF-Förderprojekt, April 2018 bis März 2020 (abgeschlossen)

Eine genaue Unternehmensbewertung ist ein wichtiger Aspekt jedes Börsengangs. Etablierte Verfahren basieren ausschliesslich auf harten finanziellen Daten. Es konnte jedoch gezeigt werden, dass ... mehr

Mustererkennung in grossen Datenmengen
FL Innovationscheck, Dezember 2017 bis Juni 2018 (abgeschlossen)

Ziel des (Vor)projektes war es komplexe Datenanalyse Methoden zu evaluieren. Dies wurde anhand Zeitreihenanalyse von Sensordaten zur Vorhersage von Maschinenausfällen durchgeführt. Hierzu wurde ein ... mehr

Text Mining for Curriculum Design for Multiple Information Systems Disciplines
ERASMUS, Oktober 2017 bis September 2019 (abgeschlossen)

Curriculum-Design betrifft alle Universitäten in Europa. Traditionell wird dies manuell durch Akademiker mit jahrelanger Erfahrung im Designprozess durchgeführt. Entscheidungen darüber, welcher ... mehr

Enterprise Content Analytics
FFF-Förderprojekt, März 2015 bis Februar 2018 (abgeschlossen)

Das weltweite Datenvolumen wächst rasant, aktuellen Schätzungen zufolge wird es im Jahr 2015 bereits acht Zettabyte betragen, das ist sechsmal mehr als noch im Jahr 2010 und sogar sechzigmal mehr als ... mehr

  • Schneider, J. (in press). Correlated Initialization for Correlated Data. Neural Processing Letters.

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  • Schneider, J., Meske, C., & Kuss, P. (2024). Foundation Models. Business & Information Systems Engineering. (ABDC_2022: A; ABS_2021: 2; VHB_3: B)

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  • Schneider, J., & Apruzzese, G. (2023). Dual Adversarial Attacks: Fooling Humans and Classifiers. Journal of Information Security and Applications, 75.

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  • Meske, C., Bunde, E., Schneider, J., & Gersch, M. (2022). Explainable artificial intelligence: Objectives, stakeholders and future research opportunities. Information Systems Management, 39(1), 53-63. (ABDC_2022: B; ABS_2021: 2; VHB_3: C)

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  • Werner, F., Basalla, M., Schneider, J., Hays, D., & vom Brocke, J. (2021). Blockchain Adoption from an Interorganizational Systems Perspective - A Mixed-Methods Approach. Information Systems Management, 38(2), 135-150. (ABDC_2022: B; ABS_2021: 2; VHB_3: C)

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  • Holzwarth, V., Schneider, J., Handali, J., Gisler, J., Hirt, C., Kunz, A., & vom Brocke, J. (2021). Towards estimating affective states in Virtual Reality based on behavioral data. Virtual Reality, 25, 1139–1152.

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  • Kamm, M., Kucklick, J., Schneider, J., & vom Brocke, J. (2021). Data mining for small shops: Empowering brick-and-mortar stores through BI functionalities of a loyalty program. Information Systems Management, 38(4), 270-286. (ABDC_2022: B; ABS_2021: 2; VHB_3: C)

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  • Basalla, M., Schneider, J., Luksik, M., Jaakonmäki, R., & vom Brocke, J. (2021). On Latency of E-Commerce Platforms. Journal of Organizational Computing and Electronic Commerce, 31(1), 1 - 17. (ABDC_2022: A; ABS_2021: 1; VHB_3: C)

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  • Hacker, J., vom Brocke, J., Handali, J., Otto, M., & Schneider, J. (2020). Virtually in this together – how web-conferencing systems enabled a new virtual togetherness during the COVID-19 crisis. European Journal of Information Systems, 29(5), 563-584. (ABDC_2022: A*; ABS_2021: 4; VHB_3: A)

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  • Holzwarth, V., Schneider, J., Kunz, A., & vom Brocke, J. (2019). Data driven value creation in AEC along the building lifecycle. Journal of Physics: Conference Series, 1343(012046).

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  • Abraham, R., Schneider, J., & vom Brocke, J. (2019). Data governance: A conceptual framework, structured review, and research agenda. International Journal of Information Management, 49(Dec), 424-438. (ABDC_2022: A*; ABS_2021: 2; VHB_3: C)

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  • vom Brocke, J., Basalla, M., Kaiser, L. F., Schneider, J., Ragtschaa, S., Batliner-Staber, F., & Dzinic, E. (2018). Own - The Case of a Blockchain Business Model Disrupting the Equity Market. CONTROLLING - Zeitschrift für erfolgsorientierte Unternehmenssteuerung, 30(5), 19-25. (VHB_3: D)

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  • Schneider, J., Bernstein, A., vom Brocke, J., Damevski, K., & Shepherd, D. C. (2018). Detecting Plagiarism Based on the Creation Process. IEEE Transactions on Learning Technologies (TLT), 11(3), 348-361.

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  • Harris, D. G., Schneider, J., & Su, H.-H. (2018). Distributed (delta 1)-Coloring in Sublogarithmic Rounds. Journal of the ACM, 65(4). (ABDC_2022: C; VHB_3: B)

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  • Schneider, J., & Caracas, A. (2017). Robust Speed Measurements with Standard Wireless Devices. IET Wireless Sensor Systems, 7(2), 35-43.

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  • Schneider, J., & Vlachos, M. (2017). Scalable Density-Based Clustering with Quality Guarantees using Random Projections. Data Mining and Knowledge Discovery (DMKD), 31(4), 972-1005.

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  • Barenboim, L., Elkin, M., Pettie, S., & Schneider, J. (2016). The Locality of Distributed Symmetry Breaking. Journal of the ACM, 63(3). (ABDC_2022: C; VHB_3: B)

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  • Damevski, K., Shepherd, D. C., Schneider, J., & Pollock, L. (2016). Mining Sequences of Developer Interactions in Visual Studio for Usage Smells. IEEE Transactions on Software Engineering (TSE), 1(1). (VHB_3: B)

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  • Vlachos, M., Schneider, J., & Vassiliadis, V. G. (2015). On Data Publishing with Clustering Preservation. ACM Transactions on Knowledge Discovery from Data (TKDD), 9(3).

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  • Estler, H., Schneider, J., Nordio, M., Furia, C., & Meyer, B. (2013). Agile vs. Structured Distributed Software Development: A Case Study. Journal on Empirical Software Engineering(EMSE).

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  • Schneider, J., Elkin, M., & Wattenhofer, R. (2012). Symmetry Breaking Depending on the Chromatic Number or the Neighborhood Growth. Journal of Theoretical Computer Science (TCS), 6(2), 70-80.

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  • Schneider, J., & Wattenhofer, R. (2010). An Optimal Maximal Independent Set Algorithm for Bounded-Independence Graphs. Journal of Distributed Computing, 15(1), 15-26.

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  • Schneider, J., & Vlachos, M. (2021). Explaining Neural Networks by Decoding Layer Activations. In P. Abreu, P. Rodrigues, A. Fernández & J. Gama (Eds.), Advances in Intelligent Data Analysis XIX. IDA 2021. (Vol. 12695, ): Springer.

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  • Apruzzese, G., Laskov, P., & Schneider, J. (2023). SoK: Pragmatic Assessment of Machine Learning for Network Intrusion Detection. Paper presented at the IEEE European Symposium on Security and Privacy (IEEE EuroS&P), Delft, Netherlands.

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  • Grisold, T., & Schneider, J. (2023). Dynamics of Human-AI Delegation in Organizational Routines. Paper presented at the Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies ICIS 2023, Hyderabad, India. (VHB_3: A)

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  • Schäfer, M., Schneider, J., Drechsler, K., & vom Brocke, J. (2022). AI Governance: Are Chief AI Officers and AI Risk Officers needed?. Paper presented at the 30th European Conference on Information Systems, Timisoara, Rumania. (VHB_3: B)

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  • Schneider, J., & Apruzzese, G. (2022). Concept-based Adversarial Attacks: Tricking Classifiers and Humans alike. Paper presented at the IEEE Symposium on Security and Privacy: Deep Learning and Security Workshop (SP DLS).

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  • Handali, J. P., Schneider, J., Gau, M., Holzwarth, V., & vom Brocke, J. (2021). Visual Complexity and Scene Recognition: How Low Can You Go?. Paper presented at the 2021 IEEE Virtual Reality and 3D User Interfaces (VR), Online.

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  • Holzwarth, V., Steiner S., Schneider J., vom Brocke J., & Kunz A. (2021). BIM-Enabled Issue and Progress Tracking Services Using Mixed Reality. Paper presented at the Smart Services Summit. Progress in IS.

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  • Schneider, J., Hacker, J., Litvinova, J., Handali, J., & vom Brocke, J. (2021). Exploring the Use of Backgrounds in Webconferencing with Image and Text Analysis. Paper presented at the International Conference on Information Systems, Austin, Texas. (VHB_3: A)

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  • Kamm, M., Gau, M., Schneider, J., & Vom Brocke, J. (2020). Smart Waste Collection Processes-A Case Study about Smart Device Implementation. Paper presented at the Hawaii International Conference on System Sciences, Hawaii. (VHB_3: C)

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  • Kucklick, J.-P., Kamm, M., Schneider, J., & Vom Brocke, J. (2020). Extending Loyalty Programs with BI Functionalities A Case Study for Brick-and-Mortar Stores. Paper presented at the 53 rd Hawaii International Conference on System Sciences 2020, Hawaii. (VHB_3: C)

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  • Handali, J. P., Schneider, J., Dennehy, D., Hoffmeister, B., Conboy, K., & Becker, J. (2020). Industry demand for analytics: A longitudinal study. Paper presented at the 28th European Conference on Information Systems (ECIS), An Online AIS Conference. (VHB_3: B)

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  • Schneider, J. (2020). Human-to-AI Coach: Improving Human Inputs to AI Systems. Paper presented at the Advances in Intelligent Data Analysis XVIII, Online.

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  • Schneider, J. (2020). Locality-promoting representation learning. Paper presented at the 2020 25th International Conference on Pattern Recognition (ICPR), Milan, Italy.

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  • Schneider, J., & Vlachos, M. (2020). Personalization of Deep Learning. Paper presented at the 3rd International Data Science Conference - iDSC2020. Data Science – Analytics and Applications, Austria.

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  • Dennehy, D., Conboy, K., Babu, J., Schneider, J., Handali, J., vom Brocke, J., Hoffmeister, B., & Stein, A. (2020). Adopting Learning Analytics to Inform Postgraduate Curriculum Design. Paper presented at the International Working Conference on Transfer and Diffusion of IT.

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  • Schneider, J., Basalla, M., & Seidel, S. (2019). Principles of Green Data Mining. Paper presented at the Hawaii International Conference on System Sciences (HICSS), Hawaii, USA. (VHB_3: C)

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  • Schneider, J., & Handali, J. (2019). Personalized explanation for machine learning: A conceptualization. Paper presented at the 27th European Conference on Information Systems, Stockholm & Uppsala, Sweden. (VHB_3: B)

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  • Meske, C., Junglas, I., Schneider, J., & Jaakonmaeki, R. (2019). How Social is Your Social Network? Toward A Measurement Model. Paper presented at the International Conference on Information Systems (ICIS), Munich, Germany. (VHB_3: A)

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  • Schneider, J., Handali, J. P., & vom Brocke, J. (2018). Increasing Trust in (Big) Data Analytics. Paper presented at the 30th International Conference on Advanced Information Systems Engineering (CAiSE) 2018: Advanced Information Systems Engineering Workshop, Tallin, Estonia.

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  • Boesch, K., Mueller,Oliver, & Schneider, J. (2018). Emotional Contagion Through Online Newspapers. Paper presented at the European Conference on Information Systems (ECIS). (VHB_3: B)

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  • Schneider, J., & Vlachos, M. (2018). Topic Modeling based on Keywords and Context. Paper presented at the SIAM International Conference on Data Mining (SDM).

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  • Schneider, J., Weinmann, M., Schneider, C., & vom Brocke, J. (2017). Identifying Preferences Through Mouse Cursor Movements - Preliminary Evidence. Paper presented at the 25th European Conference on Information Systems, Guimarães, Portugal. (VHB_3: B)

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  • Schneider, J., & Meske, C. (2017). Gender Differences in Enterprise Social Network Usage and Transformation over Time. Paper presented at the International Conference on Information Systems (ICIS). (VHB_3: A)

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  • Harris, D. G., Schneider, J., & Su, H.-H. (2016). Distributed (\Delta 1)-Coloring in Sublogarithmic Rounds. Paper presented at the Symposium on the Theory of Computing (STOC).

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  • Schneider, J., Bogojeska, J., & Vlachos, M. (2014). Solving Linear SVMs with Multiple 1D Projections. Paper presented at the Conference on Information and Knowledge Management (CIKM).

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  • Schneider, J., & Vlachos,M. (2014). On Randomly Projected Hierarchical Clustering with Guarantees. Paper presented at the 2014 SIAM International Conference on Data Mining (SDM).

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  • Vlachos, M., & Schneider, J. (2013). Fast Parameterless Density-Based Clustering via Random Projections. Paper presented at the Conference on Information and Knowledge Management (CIKM).

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  • Schneider, J., & Schmid, S. (2013). Optimal Bounds for Online Page Migration with Generalized Migration Costs. Paper presented at the IEEE International Conference on Computer Communications (INFOCOM).

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  • Vlachos, M., Wieczorek, A., & Schneider, J. (2012). Right-protected data publishing with hierarchical clustering preservation. Paper presented at the Conference on Information and Knowledge Management (CIKM).

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  • Barenboim, L., Elkin,M, Pettie, S., & Schneider, J. (2012). The Locality of Distributed Symmetry Breaking. Paper presented at the Symposium on Foundations of Computer Science (FOCS).

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  • Estler, H., Schneider, J., Nordio, M., Furia, C., & Meyer, B. (2012). Agile vs. Structured Distributed Software Development: A Case Study. Paper presented at the Conference on Global Software Engineering (ICGSE).

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  • Schlegel, R., Obermeier, S., & Schneider, J. (2012). Structured System Threat Modeling and Mitigation Analysis for Industrial Automation Systems. Paper presented at the Symposium on Foundations of Computer Science (FOCS).

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  • Schneider, J., & Wattenhofer, R. (2011). Trading Bit, Message, and Time Complexity of Distributed Algorithms Algorithm for Growth-Bounded Graphs. Paper presented at the Symposium on Distributed Computing (DISC).

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  • Schneider, J., & Wattenhofer, R. (2010). A New Technique For Distributed Symmetry Breaking. Paper presented at the Principles of Distributed Computing (PODC).

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  • Schneider, J., & Wattenhofer, R. (2010). What Is the Use of Collision Detection (in Wireless Networks)?. Paper presented at the Symposium on Distributed Computing (DISC).

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  • Hasenfratz, D., Schneider, J., & Wattenhofer, R. (2010). Transactional Memory: How to Perform Load Adaption in a Simple And Distributed Manner. Paper presented at the International Conference on High Performance Computing & Simulation (HPCS).

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  • Schneider, J., & Wattenhofer, R. (2009). Coloring Unstructured Multi-Hop Networks. Paper presented at the Principles of Distributed Computing (PODC).

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  • Schneider, J., & Wattenhofer, R. (2009). Bounds On Contention Management Algorithms. Paper presented at the Symposium on Algorithms and Computation (ISAAC).

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  • Schneider, J. (2009). Lean and Fast Secure Multi-Party Computation: Minimizing Communication and Local Computation Using A Helper. Paper presented at the International Conference on Security and Cryptography (SECRYPT).

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  • Schneider, J., & Wattenhofer, R. (2008). A Log-Star Distributed Maximal Independent Set Algorithm for Growth-Bounded Graphs. Paper presented at the Principles of Distributed Computing (PODC).

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