Assoc. Prof. Matthias Janetschek, PhD

Senior ResearcherSoftware Engineering +43 512 2070 - 4331 matthias.janetschek@mci.edu
Assoc. Prof. Matthias Janetschek, PhD


Professional work experience
  • 09/2020 - present
    Associate Professor - Management Center Innsbruck, Austria
  • 05/2018 - 09/2020
    Lecturer - Management Center Innsbruck, Austria
  • 05/2013 - 07/2015
    Co-Founder, Senior Developer - Felix Solution UG (haftungsbeschränkt)
  • 09/2011 - 02/2018
    Research Assistant - University of Innsbruck
    Research and Teaching
  • 05/2011 - 08/2011
    student assistant - University of Innsbruck
    Research
Education
  • 10/2011 - 04/2019
    PhD - University of Innsbruck
    Computer Science
  • 10/2007 - 08/2011
    MSc - University of Innsbruck
    Computer Science
  • 10/2002 - 09/2007
    Bakk.techn. - University of Innsbruck
    Computer Science
Teaching (faculty internships etc.)
  • 05/2023 - 07/2023
    Management Center Innsbruck, Österreich
    Software Engineering II
  • 10/2020 - present
    Management Center Innsbruck, Austria
    Distributed Systems
  • 09/2020 - present
    MCI - The Entrepreneurial School, Austria
    Integrated Overall Project
  • 07/2020 - present
    Management Center Innsbruck, Austria
    Virtual Reality
  • 05/2020 - present
    Management Center Innsbruck, Austria
    Architecture of information systems
  • 04/2020 - 05/2020
    Management Center Innsbruck, Austria
    Databases II & Big Data
  • 09/2019 - present
    Management Center Innsbruck, Austria
    Data networks
  • 05/2019 - present
    Management Center Innsbruck, Austria
    Operating systems
  • 04/2019 - present
    Management Center Innsbruck, Austria
    Computer Architecture & Embedded Systems
  • 02/2019 - present
    Management Center Innsbruck, Austria
    Methods of Software Development II
  • 11/2018 - present
    Management Center Innsbruck, Austria
    Methods of Software Development I
  • 11/2018 - 12/2020
    Management Center Innsbruck, Austria
    Principles of databases
  • 11/2018 - 01/2019
    Management Center Innsbruck, Austria
    Object oriented modelling
  • 10/2018 - present
    Management Center Innsbruck, Austria
    Programming Techniques
  • 03/2012 - 02/2018
    University of Innsbruck
    Einführung in die Praktische Informatik, Studienorientierungslehrveranstaltung (1 Semesterstunden) Betriebssysteme, Proseminar (2 Semesterstunden) Verteilte Systeme, Proseminar (1 Semesterstunden)
Further education & Training
  • 2018 - 2018
    MCI - The Entrepreneurial School
    Sakai Advanced
  • 2018 - 2018
    MCI - The Entrepreneurial School
    Adobe Connect Advanced
  • 2018 - 2018
    MCI - The Entrepreneurial School
    Adobe Connect Basics
  • 2018 - 2018
    MCI - The Entrepreneurial School
    Sharepoint course
  • 2018 - 2018
    MCI - The Entrepreneurial School
    Tipps & tricks for online courses
  • 2018 - 2018
    MCI - The Entrepreneurial School
    Corporate Communication
  • MCI - The Entrepreneurial School
    Sakai Basic
Peer reviewed journal article
  • Brinkschulte, L., Schlögl, S., Monz, A., Schöttle, P., & Janetschek, M. (2022). Perspectives on Socially Intelligent Conversational Agents. Multimodal Technologies and Interaction, 6(8). https://doi.org/10.3390/mti6080062
  • Thalhammer, F., Schöttle, P., Janetschek, M., & Ploder, C. (2022). Blockchain Use Cases Against Climate Destruction. Cloud Computing and Data Science, 3(2), 22-38. https://doi.org/10.37256/ccds.3220221277
  • Matthias Janetschek, Radu Prodan, Shajulin Benedict. A Workflow Runtime Environment for Manycore Parallel Architectures. In Future Generation Computer Systems Special Issue: Workflows for Data-Driven Research, Volume 75, October 2017, Pages 330-347, Elsevier
  • Kassian Plankensteiner, Radu Prodan, Matthias Janetschek, Thomas Fahringer, Johan Montagnat, David Rogers, Ian Harvey, Ian Taylor, Ákos Balaskó, Péter Kacsuk. Fine-Grain Interoperability of Scientific Workflows in Distributed Computing Infrastructures. In Journal of Grid Computing, Page 1-27, June, 2013, Springer
Chapters in books
  • M. Janetschek, R. Prodan, and J. Barbosa. Impact of workflow enactment modes on scheduling and workflow performance. In J. Carretero, E. Jeannot, and A. Zomaya, editors, Ultrascale Computing Systems, chapter 2., January 2019.
  • Simon Ostermann, Matthias Janetschek, Radu Prodan, Thomas Fahringer: Scientific Applications on Clouds. in Cloud Services, Networking, and Management, Pages 309 - 332, John Wiley & Sons, Inc., Hoboken, New Jersey, 2015
Peer reviewed academic/professional meeting proceedings
  • Viertler P., Schlögl S., Mayer R., Janetschek M., & Pattermann J. (2021). Show Me the Universe! Perceived Usability and Task Load of an AR Mobile-App in Secondary School Learning. In: Uden L., Liberona D. (eds) Learning Technology for Education Challenges. LTEC 2021. Communications in Computer and Information Science, vol 1428. Springer, Cham. doi: https://doi.org/10.1007/978-3-030-81350-5_4
  • Matthias Janetschek, Radu Prodan. A Compiler Transformation-based Approach to Scientific Workflow Enactment. In Proceedings of the 12th Workshop on Workflows in Support of Large-Scale Science., Denver, Colorado, November 13, 2017, ACM
  • Matthias Janetschek, Radu Prodan, Shajulin Benedict. A Workflow Runtime Environment for Manycore Parallel Architectures. In Proceedings of the 10th Workshop on Workflows in Support of Large-Scale Science., Austin, Texas, November 15, 2015, ACM
  • Matthias Janetschek, Simon Ostermann, Radu Prodan. Bringing Scientific Workflows to Amazon SWF. In Proceedings of the 39th Euromicro Conference on Software Engineering and Advanced Applications, Santander, Spain, September 4-6, 2013, Springer
  • Felix Schueller, Simon Ostermann, Matthias Janetschek, Radu Prodan, Georg Mayr. The RainCloud project: Harnessing Cloud Computing for a meteorological application at the Tyrolean Avalanche Service. In EGU General Assembly Conference Abstracts, Volume 15, Vienna, Austria, Page 9710, April 15, 2013
Supervised bachelor theses
  • Egger Philipp (2024): Automatisierte Überprüfung von ZigBee-Konfigurationen
  • Prenner Lukas (2024): Welche Schwachstellen existieren bei IoT-Geräten in Bezug auf physische Angriffe über UART-Schnittstellen, und wie können diese erkannt werden?
  • Hirschberger Julian (2024): Schnapsen mithilfe von Reinforcement Learning
  • Vural Hasan (2024): Prototyp Implementierung eines intelligenten Tutoren-Systems für die Einführung in die Programmierung
  • Zierler Dominik (2024): Configure Data Base (CDB) : Entwickelung eines Webinterfaces für das hausintern programmierte Tool zur leichteren Verwaltung der Linux-Konfigurationen
  • Moser Daniel (2024): It Doesn't Byte: Unleashing Spot's Potential in Human-Robot-Interaction
  • Huber Alexander (2024): Entwurf und Konzeption einer sensorbasierten Applikation zur Messung, Auswertung und Darstellung einer Mountainbike-/Shared-Trail-Nutzung
  • Knapp Sebastian (2023): Funktions- und Leistungstests für SIP-Dienste
  • Blaas Roman (2023): Über die Anwendung des Text Mining zur digitalen Unterstützung der Technologiefrüherkennung
  • Steinlechner Matthias (2023): Sicherheitsschwachstellen von Smart Contracts auf der Ethereum Blockchain
  • Angermair Martin (2023): Maschine Learning basierende vorausschauende Wartung für Fahrzeuge
  • Mellauner Christoph (2023): Configuration of professional audio networks
  • Perkmann Martin (2022): Die Entwicklung eines appgesteuerten mobilen Luftqualitätsmessgeräts
  • Pider Daniel (2022): Automatisierte Erkennung von Sicherheitslücken im Kontext von Internet of Things
  • Waldner Arthur (2022): Automatisierte Optimierung der Lokalisierung von IoT-Geräten über WLAN mit Maschinellem Lernen
  • Härting Sebastian (2021): Hochverfügbare Virtualisierung und Upgrade eines Prozessleitsystems in der pharmazeutischen Industrie
  • Keplinger Emanuel (2021): Machbarkeitsstudie zur Anwendbarkeit eines Algorithmus für die digitale Transformation der Stundenplanung an der "fachhochschule gesundheit"
Supervised master theses
  • Hake Malte (2020): Computer Vision at the Edge: A Performance Evaluation of Low-Power Hardware for Edge Computing Scenarios