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About Me

Since joining TECO as a PostDoc in 2019, I have been working on methods to improve environmental sensing through statistical modeling and data-driven inference. With a background in theoretical particle physics (Dr. rer. nat., KIT), my research explores how concepts from physics can be applied to interdisciplinary domains such as air quality monitoring and environmental data analysis. My work focuses on Gaussian processes, Bayesian inference, and dispersion modeling to enhance the accuracy and interpretability of sensor-based systems.

Short CV

  • since 2019           PostDoc at TECO
  • 2018                     Dr. rer. nat. Dissertation in Theoretical Particle Physics
  • 2014 - 2018        PhD student at TTP (Institute for Theoretical Particle Physics) at KIT
  • 2014                     Graduation with Diplom (Master equivalent) from Karlsruhe Institute of Technology (KIT)
  • until 2014            Student of Physics at Karlsruhe Institute of Technology (KIT)

Research Interests

  • Environmental Sensing
  • Gaussian Processes / Bayesian Inference
  • Dispersion Modelling
  • Interdisciplinary Application of Concepts of Theoretical Physics

Dr. Paul Tremper's publications

2022
SmartAQnet 2020: A New Open Urban Air Quality Dataset from Heterogeneous PM Sensors
Li, C.; Budde, M.; Tremper, P.; Schäfer, K.; Riesterer, J.; Redelstein, J.; Petersen, E.; Khedr, M.; Liu, X.; Köpke, M.; Hussain, S.; Ernst, F.; Kowalski, M.; Pesch, M.; Werhahn, J.; Hank, M.; Philipp, A.; Cyrys, J.; Schnelle-Kreis, J.; Grimm, H.; Ziegler, V.; Peters, A.; Emeis, S.; Riedel, T.; Beigl, M.
2022. ProScience, 8. doi:10.14644/dust2021.001 VolltextVolltext der Publikation als PDF-Dokument 
2021
Hochaufgelöste Erfassung der urbanen Feinstaubbelastung mittels Messnetz aus kostengünstigen Sensoren und numerischen Simulationen
Schäfer, K.; Budde, M.; Cyrys, J.; Emeis, S.; Gratza, T.; Grimm, H.; Hank, M.; Kowalski, M.; Pesch, M.; Peters, A.; Philipp, A.; Riedel, T.; Riesterer, J.; Schnelle-Kreis, J.; Tremper, P.; Uhrner, U.; Werhahn, J.; Ziegler, V.; Beigl, M.
2021. Gefahrstoffe, Reinhaltung der Luft, 81 (9-10), 353–361 
Adaptives luftqualitätsgewichtetes Fahrradrouting mittels Land-use Regression auf Basis offener Daten
Janßen, J.; Riedel, T.; Tremper, P.
2021. Workshop: 2. Workshop Künstliche Intelligenz in der Umweltinformatik (KIUI-2021), 321–331, Gesellschaft für Informatik (GI). doi:10.18420/informatik2021-026 VolltextVolltext der Publikation als PDF-Dokument 
Spatial Interpolation of Air Quality Data with Multidimensional Gaussian Processes
Tremper, P.; Riedel, T.; Budde, M.
2021. Workshop: 2. Workshop Künstliche Intelligenz in der Umweltinformatik (KIUI-2021), 269–286, Gesellschaft für Informatik (GI). doi:10.18420/informatik2021-022 VolltextVolltext der Publikation als PDF-Dokument 
Calibration of Low-Cost Particulate Matter Sensors with Elastic Weight Consolidation (EWC) as an Incremental Deep Learning Method
Schlund, R.; Riesterer, J.; Köpke, M.; Kowalski, M.; Tremper, P.; Budde, M.; Beigl, M.
2021. Science and Technologies for Smart Cities – 6th EAI International Conference, SmartCity360°, Virtual Event, December 2-4, 2020, Proceedings. Ed.: S. Paiva, 596–614, Springer International Publishing. doi:10.1007/978-3-030-76063-2_40 
2019
Low-Cost Sensing and Data Management in SmartAQnet
Budde, M.; Riesterer, J.; Köpke, M.; Tremper, P.; Riedel, T.
2019. Mid-term and 1st International Networking Workshop of the SmartAQnet Project : December 4th and 5th 2018, Munich. Ed.: M. Budde, 3, Karlsruher Institut für Technologie (KIT) VolltextVolltext der Publikation als PDF-Dokument 
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