• Intelligente Sensorsysteme (Bachelor)
• Rechnerstrukturen und Maschinennahes Programmieren (Bachelor)
• Betriebssysteme (Bachelor)
• Autonomes Fahren und Robotik (Master)
• WP Einführung in die Robotik (Bachelor)
• WP Einführung in Computer Engineering (Bachelor)
• Algorithmen und Datenstrukturen (Bachelor)
• Master-Grund-/-Hauptseminare, Bachelor-Seminare
• Projekte: Lehr-CPU-/Lehr-BS-Entwicklung, Deep Learning, Autonome Systeme

• Intelligente Sensorik
• Sensordatenverarbeitung
• Maschinelle Lernverfahren (ML)
• Miniaturautonomie
• autonome Systeme, Robotik, Unterwasserrobotik
• Anwendungen im Verkehrs-/Automotive-Kontext, autonomes Fahren

• Mitglied in der Forschungsgruppe AutoSys :  autosys.informatik.haw-hamburg.de/authors/timtiedemann/
• Mitglied im Hochschulsenat
• Stellvertretendes Mitglied im Fakultätsrat TI
• Mitglied Ethikkommission der HAW
• Fellow des Stifterverbandes (2018)
• IEEE

• Deep Learning for Time Series Classification and Prediction on Big Crowd Sensed Automotive Data (Master-Arbeit)
• Bachelor-/Master-Arbeiten zu FPGA-basierter Implementierung maschineller Lernverfahren oder anderer spezifischer Algorithmen
• Bachelor-/Master-Arbeiten zu datengetriebener Sensordatenfusion
• Bachelor-/Master-Arbeiten zur Sensordatenverarbeitung in verschiedenen Anwendungen der Robotik
• Master-Arbeiten/Master-Projekte in den Bereichen Kooperation im autonomen Fahren, Miniaturautonomie, autonome Systeme, Robotik

[Publikationsliste nach IT-Ausfall 12/2022 verzögert]
 

2023:

• Tiedemann, Schmidt, Stricker, Fuhrmann: "First Results of a Comparison of Machine Learning Hardware Acceleration Approaches Using Field Programmable Gate Arrays in an Agricultural Mobile Robotic Application Case". Proceedings of the 16th International Symposium on Intelligent Distributed Computing (IDC 2023)
   
• Lange, Babu, Meyer, Keppner, Tiedemann, Wittmaier, Wolff, Vögele: "FIRST LESSONS LEARNED OF AN ARTIFICIAL INTELLIGENCE ROBOTIC SYSTEM FOR AUTONOMOUS COARSE WASTE RECYCLING USING MULTISPECTRAL IMAGING-BASED METHODS". Proceedings of the Sardinia Conference 2023 (+ Journal Special Issue eingeladen, in Arbeit)
   
• Schurwanz, Mietzner, De Muirier, Tiedemann, and Hoeher, "Compressed sensing based obstacle detection for future urban air mobility scenarios," IEEE Sensors Lett., vol. 7, no. 11, pp. 1 - 4, Nov. 2023.
   
• Pareigis, Tiedemann, Schönherr, Mihajlov, Denecke, Tran, Koch, Abdelkarim, Mang: "Artificial intelligence in autonomous systems : a collection of projects in six problem classes". DOI: https://doi.org/10.1007%2F978-3-031-32700-1_14
   
• Tiedemann, Lange, Meyer, Keppner: "Intermediate Results of a Multi- Spectral-Imaging-Based Ripeness and Malformed Classification on an Object- and Pixel-Basis Using Field Programmable Gate Arrays for an Autonomous Strawberry-Harvesting Robot". IEEE IROS 2023 Workshop on Agricultural Robotics for a Sustainable Future (WARS) (IROS workshop poster presentation. peer-reviewed) (winner 3rd. prize "Advancement in Robotic Farm Technology")
   
• Zach, Tiedemann: "First Results of a Low-Cost Visual Odometry Approach for Autonomous Underwater Localization and Fish Habitat
   
• Mapping". IEEE IROS 2023 2nd Advanced Marine Robotics TC Workshop (IROS workshop poster presentation. peer-reviewed)

2022:

• Tiedemann, T., Schwalb, L., Kasten, M., Grotkasten, R., & Pareigis, S. (2022). Miniature autonomy as means to find new approaches in reliable autonomous driving AI method design. Frontiers in Neurorobotics, Vol. 16, ISSN 1662-5218, URL: www.frontiersin.org/articles/10.3389/fnbot.2022.846355, doi:https://doi.org/10.3389/fnbot.2022.846355

• Tiedemann, T.; Cordes, F.; Keppner, M. and Peters, H. (2022). Challenges of Autonomous In-field Fruit Harvesting and Concept of a Robotic Solution.  In Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics, ISBN 978-989-758-585-2, ISSN 2184-2809, pages 508-515.
• Tiedemann, T. and Thill, S. (ass. eds., chairs): The BROAD Workshop. WS at the 33rd IEEE Intelligent Vehicles Conference, June 2022, Aachen.
• Tiedemann, T.: Of Miniature Autonomy on Land, on Water and in the Air and Why IV Should Bother about It. Talk at the joined BROAD/RVT WS at the 33rd IEEE Intelligent Vehicles Conference, June 2022, Aachen.

2021: 

• Juri Zach, Christian Busse, Steffen Funk, Christian Möllmann, Bernd-Christian Renner, and Tim Tiedemann: Towards Non-invasive Fish Monitoring in Hard-to-Access Habitats
  Using Autonomous Underwater Vehicles and Machine Learning. Proceedings of the OCEANS 2021 (accepted and presented)
• Tim Tiedemann, Matthis Keppner, Tom Runge, Thomas Vögele, Martin Wittmaier and Sebastian Wolff: Concept of a Robotic System For Autonomous Coarse Waste Recycling. Proceedings of the ICINCO 2021. SCITEPRESS. (accepted and presented)
• Tiedemann, T. and Anderson, S. (ass. eds., chairs): The BROAD Workshop. WS at the 32nd IEEE Intelligent Vehicles Conference, July 2021, Nagoya. 

2020:

• Pareigis, S., Tiedemann, T., Kasten, M., Stehr, M., Schnirpel, T., Schwalb, L. and Burau, H., 2021. Künstliche Intelligenz in der Miniaturautonomie. In Echtzeit 2020 (pp. 41-50). Springer Vieweg, Wiesbaden.
• Tiedemann, T. and Anderson, S. (ass. eds., chairs): The BROAD Workshop. WS at the 31st IEEE Intelligent Vehicles Conference, November 2020, Las Vegas. 

2019:

• Tiedemann, T. (2019): Adversarial Attacks: How To Fool An Artificial Neural Network? Invited talk at the tell-me days 2019, 26.-28.06.2019. HAW Hamburg. URL: youtu.be/-ZZgws-8sXA
• Tim Tiedemann, Jonas Fuhrmann, Sebastian Paulsen, Thorben Schnirpel, Nils Schönherr, Bettina Buth, and Stephan Pareigis (2019): Miniature Autonomy as One Important Testing Means in the Development of Machine Learning Methods for Autonomous Driving: How ML-Based Autonomous Driving Could Be Realized on a 1:87 Scale. In Proceedings of the ICINCO 2019. SCITEPRESS. (accepted)
• Stephan Pareigis, Tim Tiedemann, Jonas Fuhrmann, Sebastian Paulsen, Thorben Schnirpel, Nils Schönherr. Miniaturautonomie und Echtzeitsysteme. In Tagungsband Echtzeit 2019, Springer Lecture Notes. Springer. (accepted)
• Tim Tiedemann, Jonas Fuhrmann, Sebastian Paulsen, Thorben Schnirpel, Bettina Buth, and Stephan Pareigis (2019): Miniature Autonomy as Testing Platform to Tackle Challenges of Autonomous Driving. Poster (not peer-reviewed!) at the IEEE Intelligent Vehicles Conference 2019. June 2019, Paris.
• Tiedemann, T. and Anderson, S. (ass. eds., chairs): The BROAD Workshop. WS at the 30th IEEE Intelligent Vehicles Conference, June 2019, Paris. 
• Markus Linke und Tim Tiedemann: "Individuelle online Lernwege in der Technischen Mechanik mit Maschinellen Lernverfahren" Posterbeitrag zum Fellowtreffen des Programms Innovationen in der Hochschullehre, 15 März 2019, Deutscher Stifterverband für die Deutsche Wissenschaft

2018:

• Tiedemann, T. (2018): Communication Hardware, in: Bosse, S., Lehmhus, D., Lang, W. and Busse, M. (2018)  Material-Integrated Intelligent Systems - Technology and Applications: Technology and Applications, Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany. doi: 10.1002/9783527679249.ch15

2017:

• Schenck, Horst, Tiedemann, Gaulik, Möller (2017): Comparing parallel hardware architectures for visually guided robot navigation. Concurrency Computat.: Pract. Exper., 29: pe3833, doi: 10.1002/cpe.3833
• Tiedemann, Bauer, Kirchner: Concept of Cognitively Inspired Automotive Sensor Data Fusion. Talk at IEEE Intelligent Vehicles 2017, WS on Cognitively Inspired Vehicles.
• Tiedemann, Backe, Vögele, Conradi: Automotive Ad Hoc Sensor Networks in the Project SADA: Concept and Current State. Poster presentation at the "Fachgespräche Sensornetze 2017".
• Tiedemann: Dynamic and Automatic Sensor Data Fusion in the Automotive Research Project SADA. Talk at the Int. Conf "Vehicle Intelligence", Dec. 2017, Munich. 

2016:

• Tim Tiedemann, Christian Backe, Thomas Vögele, Peter Conradi (2016): An Automotive Distributed Mobile Sensor Data Collection with Machine Learning Based Data Fusion and Analysis on a Central Backend System. Procedia Technology, Volume 26, 2016, Pages 570-579, ISSN 2212-0173, dx.doi.org/10.1016/j.protcy.2016.08.071.
• Wendelin Feiten, Susana Alcalde Baguees, Michael Fiegert, Feihu Zhang, Dhiraj Gulati, Tim Tiedemann: A New Concept for a Cooperative Fusion Platform. Proceedings of 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems.
• Susana Alcalde Bagüés, Wendelin Feiten, Tim Tiedemann, Christian Backe, Dhiraj Gulati, Steffen Lorenz and Peter Conradi: Towards Dynamic and Flexible Sensor Fusion for Automotive Applications. Proceedings of the 20th International Forum on Advanced Microsystems for Automotive Applications (AMAA 2016).

2015:

• T. Tiedemann, T. Vögele, Mario M. Krell, Jan H. Metzen, F. Kirchner: Concept
  of a Data Thread Based Parking Space Occupancy Prediction in a Berlin Pilot
  Region. Proceedings of the AAAI Workshop on AI for Transportation (WAIT),
  2015.
• T. Köhler: Bio-Inspired Motion Detection Based on an FPGA Platform. In G.
  Cristobal et al. (Herausgeber): Biologically-Inspired Computer Vision:
  Fundamentals and Applications, Wiley-VCH, Weinheim, Kapitel 17, Okt/2015.
  ISBN: 978-3-527-41264-8. (Buchkapitel)
• T. Tiedemann, T. Vögele: Wissen, wann ein Parkplatz frei wird. In
  Internationales Verkehrswesen, DVV Media Group GmbH, volume 67, pages
  84-85, 2015. (nicht peer-reviewed)

2014:

• Tim Köhler, Elmar Berghöfer, Christian Rauch, Frank Kirchner: Sensor Fault Detection and Compensation in Lunar/Planetary Robot Missions Using Time-Series Prediction Based on Machine Learning. In Acta Futura, ESA Advanced Concepts Team, ESTEC, volume Issue 9: AI in Space Workshop at IJCAI 2013, pages 9-20, May/2014.

2013:

• Christian Rauch, Elmar Berghöfer, Tim Köhler, Frank Kirchner: Comparison of Sensor-Feedback Prediction Methods for Robust Behavior Execution. In KI 2013: From Research to Innovation and Practical Applications, (KI-13), 16.9.-20.9.2013, Koblenz, Springer, pages 200-211, Sep/2013. ISBN: 978-3-642-40941-7.
• Elmar Berghöfer, Denis Schulze, Christian Rauch, Marko Tscherepanow, Tim Köhler, Sven Wachsmuth: ART-based fusion of multi-modal perception for robots. In Neurocomputing, Elsevier, volume 107, pages 11-22, May/2013.

2012:

• Tim Köhler, Christian Rauch, Martin Schröer, Elmar Berghöfer, Frank Kirchner: Concept of a Biologically Inspired Robust Behaviour Control System. In Proceedings of International Conference on Intelligent Robotics and Applications 2012, (ICIRA-12), 03.10.-05.10.2012, Montreal, Québec, Springer Berlin / Heidelberg, pages 486-495, Oct/2012. ISBN: 978-3-642-33514-3.
• Christian Rauch, Tim Köhler, Martin Schröer, Elmar Berghöfer, Frank Kirchner: A Concept of a Reliable Three-Layer Behaviour Control System for Cooperative Autonomous Robots. In Proceedings of the German Conference on Artificial Intelligence, (KI-2012), 24.9.-27.9.2012, Saarbrücken, o.A., Sep/2012.

2009:

• Köhler, T., Röchter, F., Lindemann, J. P., & Möller, R.: Bio-inspired motion detection in an FPGA-based smart camera module. Bioinspiration & biomimetics, 4(1), 015008.