Sebastian Bader
Docent|Associate Professor
- Tjänstetitel: Docent
- Akademisk titel: Docent
- Telefon arbete: +46 (0)10-1428095
- E-postadress: sebastian.bader@miun.se
- Besöksadress: Holmgatan 10, Sundsvall
- Rumsnummer: S221
- Ort: Sundsvall
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- Anställd inom ämnet:
- Elektroteknik
- Elektronik
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- Forskningscentra:
- Sensible Things that Communicate, STC
Bakgrund
Sebastian Bader joined Mid Sweden University in 2008, when he started his PhD education in electronics at the Department of Electronics Design. Previous to that, Sebastian has obtained his Diplom-Ingenieur degree in Information Technology at the University of Applied Sciences in Wilhelmshaven, Germany.
Sebastian has obtained his Licentiate of Technology and Doctor of Technology degrees in 2011 and 2013, respectively. After that, he was employed as a postdoctoral research assistant and as associate senior lecturer in the periods 2013-2015 and 2015-2017, respectively. Since 2018, he is employed as a senior lecturer, and since 2021 he is an associate professor of embedded systems.
During his time at Mid Sweden University, Sebastian has been a visiting researcher at CSIRO in Australia (2011), and at the University of Southampton (2015-2017). He is also active in a number of international networks, regularly performs international teaching and research activities, and gives international talks. Sebastian is a senior member of the IEEE, a member of the PSMA Energy Harvesting Committee, Associate Editor for Sustainable Computing: Informatics and Systems, Topic Editor for the MDPI Sensors Journal, and a member of the steering committee of the IEEE Sensors Applications Symposium (SAS).
Forskning
Sebastian's current research focuses on the energy consumption and energy supply of autonomous sensor systems. With the growing demand of autonomous electronic systems in the IoT and smart world paradigms, the lifetime of these devices becomes increasingly important in order to reduce maintenance demands.
In his research, Sebastian is currently particularly interested in self-powered systems that utilise and extract ambient energy sources in order to generate the electricity required for their operation. Application scenarios include environmental monitoring applications, but have recently more focused on industrial applications and the kinetic energy sources to be found there. Sebastian also conducts research in Tiny Machine Learning, that means the implementation of machine learning algorithms on very resource limited devices.
Undervisning
Sebastian is active in the educational offerings at the Department of Computer and Electrical Engineering, where he is program manager for the Master of Science in Engineering program in Electrical Engineering (Civilingenjör i elektroteknik) and the Master of Science program in Electrical Engineering.
Sebastian's teaching is centered around education in embedded systems, with, amongst others, courses in embedded system programming, embedded machine learning and sensor networks. He is also involved in teaching activities on scientific writing and regularly supervises students in engineering and research projects, as well as BSc and MSc thesis works.
Past and current PhD students:
- Dr. Xinyu Ma (graduated Jan. 2021)
- Dr. Javier Aranda (graduated Apr. 2021)
- Dr. Ye Xu (graduated Mar. 2022)
- Mrs. Tra Phan
- Mr. Yuxuan Zhang
- Mrs. Thanh Tran
- Mrs. Jule Janke
- Mr. Veysi Adin
Övrigt
We are continuously looking for highly motivated students. If you are interested in an internship or thesis project in the research areas outlined above, and you are currently a student at one of our partner universities, I am looking forward to hearing from you.
Publikationer
Artiklar i tidskrifter
Artiklar, forskningsöversikter
Doktorsavhandlingar, sammanläggningar
Konferensbidrag
Licentiatavhandlingar, sammanläggningar
Artiklar i tidskrifter
Zhang, Y. , Pullin, R. , Oelmann, B. & Bader, S. (2025). On-Device Fault Diagnosis with Augmented Acoustic Emission Data : A Case Study on Carbon Fiber Panels. IEEE Transactions on Instrumentation and Measurement, vol. 74, ss. 1-12.
Bader, S. & Oelmann, B. (2024). Instrumentation and Measurement Systems : The Challenge of Designing Energy Harvesting Sensor Systems. IEEE Instrumentation & Measurement Magazine, vol. 27: 4, ss. 22-28.
Martinez Rau, L. , Chelotti, J. O. , Giovanini, L. L. , Adin, V. , Oelmann, B. & Bader, S. (2024). On-Device Feeding Behavior Analysis of Grazing Cattle. IEEE Transactions on Instrumentation and Measurement, vol. 73
Bader, S. (2023). Instrumentation and Measurement Systems : Methods, Applications and Opportunities for Instrumentation and Measurement. IEEE Instrumentation & Measurement Magazine, vol. 26: 7, ss. 28-33.
Zhang, Y. , Adin, V. , Bader, S. & Oelmann, B. (2023). Leveraging Acoustic Emission and Machine Learning for Concrete Materials Damage Classification on Embedded Devices. IEEE Transactions on Instrumentation and Measurement, vol. 72
Zhang, Y. , Wang, W. , Xie, J. , Lei, Y. , Cao, J. , Xu, Y. , Bader, S. , Bowen, C. & et al. (2022). Enhanced variable reluctance energy harvesting for self-powered monitoring. Applied Energy, vol. 321
Phan, T. N. , Aranda, J. J. , Oelmann, B. & Bader, S. (2021). Design optimization and comparison of cylindrical electromagnetic vibration energy harvesters. Sensors, vol. 21: 23
Ma, X. , Bader, S. & Oelmann, B. (2021). On the Performance of the Two-Diode Model for Photovoltaic Cells under Indoor Artificial Lighting. IEEE Access, vol. 9, ss. 1350-1361.
Aranda, J. J. , Bader, S. & Oelmann, B. (2021). Self-powered wireless sensor using a pressure fluctuation energy harvester. Sensors, vol. 21: 4
Xu, Y. , Bader, S. , Magno, M. , Mayer, P. & Oelmann, B. (2021). System Implementation Trade-Offs for Low-Speed Rotational Variable Reluctance Energy Harvesters. Sensors, vol. 21: 18
Ying, Z. , Zhu, H. , Junyi, C. , Xu, Y. , Bader, S. & Oelmann, B. (2021). Theoretical modeling and experimental verification of rotational variable reluctance energy harvesters. Energy Conversion and Management, vol. 233
Bader, S. , Ma, X. & Oelmann, B. (2020). A Comparison of One- and Two-Diode Model Parameters at Indoor Illumination Levels. IEEE Access, vol. 8, ss. 172057-172064.
Zelenika, S. , Hadas, Z. , Bader, S. , Becker, T. , Gljušćić, P. , Hlinka, J. , Janak, L. , Kamenar, E. & et al. (2020). Energy harvesting technologies for structural health monitoring of airplane components—a review. Sensors, vol. 20: 22
Phan, T. , Bader, S. & Oelmann, B. (2020). Performance of an electromagnetic energy harvester with linear and nonlinear springs under real vibrations. Sensors, vol. 20: 19
Ma, X. , Bader, S. & Oelmann, B. (2020). Power Estimation for Indoor Light Energy Harvesting Systems. IEEE Transactions on Instrumentation and Measurement, vol. 69: 10, ss. 7513-7521.
Aranda, J. J. L. , Bader, S. & Oelmann, B. (2019). A space-coiling resonator for improved energy harvesting in fluid power systems. Sensors and Actuators A-Physical, vol. 291, ss. 58-67.
Xu, Y. , Bader, S. & Oelmann, B. (2019). Design, modeling and optimization of an m-shaped variable reluctance energy harvester for rotating applications. Energy Conversion and Management, vol. 195, ss. 1280-1294.
Bader, S. , Ma, X. & Oelmann, B. (2019). One-diode photovoltaic model parameters at indoor illumination levels – A comparison. Solar Energy, vol. 180, ss. 707-716.
Xu, Y. , Bader, S. & Oelmann, B. (2018). A Survey on Variable Reluctance Energy Harvesters in Low-Speed Rotating Applications. IEEE Sensors Journal, vol. 18: 8, ss. 3426-3435.
Aranda, J. J. L. , Bader, S. & Oelmann, B. (2018). An Apparatus For The Performance Estimation Of Pressure Fluctuation Energy Harvesters. IEEE Transactions on Instrumentation and Measurement, vol. 67: 11, ss. 2705-2713.
Ma, X. , Bader, S. & Oelmann, B. (2017). Characterization of Indoor Light Conditions by Light Source Classification. IEEE Sensors Journal, vol. 17: 12, ss. 3884-3891.
Bader, S. , Ma, X. & Oelmann, B. (2014). On the Modeling of Solar-Powered Wireless Sensor Nodes. Journal of Sensor and Actuator Networks, vol. 3: 3, ss. 207-223.
Bader, S. & Oelmann, B. (2011). Durable Solar Energy Harvesting from Limited Ambient Energy Income. International Journal on Advances in Networks and Services, vol. 4: 1&2, ss. 66-80.
Artiklar, forskningsöversikter
Zhang, Y. , Wang, W. , Wu, X. , Lei, Y. , Cao, J. , Bowen, C. , Bader, S. & Yang, B. (2023). A comprehensive review on self-powered smart bearings. Renewable & sustainable energy reviews, vol. 183
Xiao, H. , Pan, M. , Chu, J. Y. H. , Bowen, C. R. , Bader, S. , Aranda, J. & Zhu, M. (2022). Hydraulic Pressure Ripple Energy Harvesting : Structures, Materials, and Applications. Advanced Energy Materials, vol. 12: 9
Xu, Y. , Zhang, Y. , Bader, S. , Oelmann, B. & Cao, J. (2022). Three-phase variable reluctance energy harvesting. Energy Conversion and Management, vol. 14
Doktorsavhandlingar
Bader, S. (2013). On the lifetime and usability of environmental monitoring wireless sensor networks. Diss. (Sammanläggning) Sundsvall : Mid Sweden University, 2013 (Mid Sweden University doctoral thesis : 161)
Konferensbidrag
Phan, T. , Xu, Y. , Kanoun, O. , Oelmann, B. & Bader, S. (2024). Automated Ortho- Planar Spring Design for Vibration Energy Harvesters. I 2024 IEEE Sensors Applications Symposium, SAS 2024 - Proceedings.
Muthumala, U. , Zhang, Y. , Martinez Rau, L. & Bader, S. (2024). Comparison of Tiny Machine Learning Techniques for Embedded Acoustic Emission Analysis. I 2024 IEEE 10th World Forum on Internet of Things (WF-IoT).
Nguyen Phan, T. , Xu, Y. , Oelmann, B. & Bader, S. (2024). Electromagnetic Vibration Energy Harvester with Replaceable Ortho-planar Springs. I 2024 IEEE SENSORS.
Zhang, Y. , Martinez Rau, L. , Oelmann, B. & Bader, S. (2024). Enabling Autonomous Structural Inspections with Tiny Machine Learning on UAVs. I 2024 IEEE Sensors Applications Symposium, SAS 2024 - Proceedings.
Jansen, K. , Shallari, I. , Mourad, S. , Werheit, P. & Bader, S. (2024). Image-Based Condition Monitoring of Air-Spinning Machines with Deep Neural Networks. I 2024 IEEE Sensors Applications Symposium, SAS 2024 - Proceedings.
Wu, M. , Xu, Y. & Bader, S. (2024). Multi-Phase Variable Reluctance Energy Harvester for Smart Bearing Hub Units. I 2024 IEEE 23rd International Conference on Micro and Miniature Power Systems, Self-Powered Sensors and Energy Autonomous Devices (PowerMEMS).. S. 46--49.
Martinez Rau, L. , Zhang, Y. , Oelmann, B. & Bader, S. (2024). TinyML Anomaly Detection for Industrial Machines with Periodic Duty Cycles. I 2024 IEEE Sensors Applications Symposium, SAS 2024 - Proceedings.
Trpcheska, A. , Zevnik, F. & Bader, S. (2024). Towards Real-Time Vision-Based Sign Language Recognition on Edge Devices. I 2024 IEEE Sensors Applications Symposium, SAS 2024 - Proceedings.
Tran, T. , Bader, S. & Lundgren, J. (2023). Denoising Induction Motor Sounds Using an Autoencoder. I 2023 IEEE Sensors Applications Symposium (SAS).. S. 01--06.
Hamza, K. , Bouattour, G. , Bader, S. , Fakhfakh, A. & Kanoun, O. (2023). Fast Supercapacitor Charging for Electromagnetic Converter Systems by Self Powered Boost Circuit. I Proceedings.. S. 553--558.
Martinez Rau, L. , Adin, V. , Giovanini, L. L. , Oelmann, B. & Bader, S. (2023). Real-Time Acoustic Monitoring of Foraging Behavior of Grazing Cattle Using Low-Power Embedded Devices. I 2023 IEEE Sensors Applications Symposium (SAS).
Xu, Y. , Bader, S. & Oelmann, B. (2023). Self-powered RPM Sensor using a Single-Anchor Variable Reluctance Energy Harvester with Pendulum Effects. I ENSsys '23: Proceedings of the 11th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems. Istanbul Turkiye : . S. 72--78.
Adin, V. , Zhang, Y. , Oelmann, B. & Bader, S. (2023). Tiny Machine Learning for Damage Classification in Concrete Using Acoustic Emission Signals. I 2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).
Adin, V. , Zhang, Y. , Ando, B. , Oelmann, B. & Bader, S. (2023). Tiny Machine Learning for Real-Time Postural Stability Analysis. I 2023 IEEE Sensors Applications Symposium (SAS).
Zhang, Y. , Bader, S. & Oelmann, B. (2022). A Lightweight Convolutional Neural Network Model for Concrete Damage Classification using Acoustic Emissions. I 2022 IEEE Sensors Applications Symposium, SAS 2022 - Proceedings.
Bader, S. , Grandien, C. & Jaldemark, J. (2022). A tentative model for sustainable pedagogical digital competence development : Exploring networked learning in an educational development project. I Proceedings for the Thirteenth International Conference on Networked Learning 2022. Aalborg : . S. 1--7.
Tran, T. , Bader, S. & Lundgren, J. (2022). An artificial neural network-based system for detecting machine failures using a tiny sound dataset : A case study. I Proceedings - 2022 IEEE International Symposium on Multimedia, ISM 2022.. S. 163--168.
Mozelius, P. , Bader, S. , Jaldemark, J. , Urbansson, P. & Engström, A. (2022). Educational development - Challenges, opportunities, tools and techniques. I Proceedings of the 21st European Conference on e-Learning - ECEL 2022. Reading, UK : . S. 264--271.
Phan, T. , Oelmann, B. & Bader, S. (2022). Towards Automated Design Optimization of Electromagnetic Energy Harvesting Transducers. I SenSys '22 : Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.. S. 871--877.
Bader, S. , Ma, X. & Oelmann, B. (2020). Distributed Measurement of Light Conditions for Indoor Photovoltaic Applications. I Proceedings of IEEE Sensors.
Ma, X. , Bader, S. & Oelmann, B. (2020). Estimating Harvestable Energy in Time-Varying Indoor Light Conditions. I ENSsys 2020 - Proceedings of the 8th International Workshop on Energy Harvesting and Energy-Neutral Sensing Systems.. S. 71--76.
Ma, X. , Bader, S. & Oelmann, B. (2019). A Scalable, Data-driven Approach for Power Estimation of Photovoltaic Devices under Indoor Conditions. I ENSsys'19 Proceedings of the 7th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems. New York, USA : . S. 29--34.
Xu, Y. , Bader, S. , Magno, M. , Mayer, P. & Oelmann, B. (2019). Energy-autonomous On-rotor RPM Sensor Using Variable Reluctance Energy Harvesting. I 2019 IEEE 8th International Workshop on Advances in Sensors and Interfaces (IWASI).. S. 175--180.
Krug, S. , Bader, S. , Oelmann, B. & O'Nils, M. (2019). Suitability of Communication Technologies for Harvester-Powered IoT-Nodes. I IEEE International Workshop on Factory Communication Systems - Proceedings, WFCS.
Rusu, C. , Bader, S. , Oelmann, B. , Alvandpour, A. , Enoksson, P. , Braun, T. , Tiedke, S. , Molin, R. D. & et al. (2018). Challenges for Miniaturised Energy Harvesting Sensor Systems. I 2018 10th International Conference on Advanced Infocomm Technology (ICAIT).. S. 214--217.
Aranda, J. J. L. , Bader, S. & Oelmann, B. (2018). Force Transmission Interfaces for Pressure Fluctuation Energy Harvesters. I IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society. (IEEE Industrial Electronics Conference). S. 4230--4235.
Bader, S. & Oelmann, B. (2017). A concept for remotely reconfigurable solar energy harvesting testbeds. I Proceedings of IEEE Sensors. (IEEE Sensors). S. 837--839.
Aranda, J. J. L. , Oelmann, B. & Bader, S. (2017). Fluid coupling interfaces for hydraulic pressure energy harvesters. I 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM). (IEEE ASME International Conference on Advanced Intelligent Mechatronics). S. 1556--1562.
Fabre, A. , Martinez, K. , Bragg, G. , Basford, P. , Hart, J. , Bader, S. & Bragg, O. (2016). Deploying a 6LoWPAN, CoAP, low power, wireless sensor network : Poster Abstract. I Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems CD-ROM.. S. 362--363.
Ma, X. , Bader, S. & Oelmann, B. (2016). Solar panel modelling for low illuminance indoor conditions. I 2016 2ND IEEE NORDIC CIRCUITS AND SYSTEMS CONFERENCE (NORCAS).
Gebben, F. , Bader, S. & Oelmann, B. (2015). Configuring artificial neural networks for the prediction of available energy in solar-powered sensor nodes. I 2015 IEEE SENSORS - Proceedings.. S. 354--357.
Bader, S. , Krämer, M. , Lawal, N. , O'Nils, M. & Oelmann, B. (2014). Remote image capturing with low-cost and low-power wireless camera nodes. I Proceedings of IEEE Sensors. (Procedings of IEEE Sensors). S. 730--733.
Bader, S. , Krämer, M. & Oelmann, B. (2013). A Domain-Specific Platform for Research in Environmental Wireless Sensor Networks. I SENSORCOMM 2013, The Seventh International Conference on Sensor Technologies and Applications.. S. 200--207.
Bader, S. & Oelmann, B. (2013). Concealing the complexity of node programming in wireless sensor networks. I Proceedings of the 2013 IEEE 8th International Conference on Intelligent Sensors, Sensor Networks and Information Processing: Sensing the Future, ISSNIP 2013.. S. 177--182.
Krämer, M. , Bader, S. & Oelmann, B. (2013). Implementing Wireless Sensor Network applications using hierarchical finite state machines. I Networking, Sensing and Control (ICNSC), 2013 10th IEEE International Conference on. (IEEE International Conference on Networking Sensing and Control). S. 124--129.
Bader, S. & Oelmann, B. (2013). Short-term energy storage for wireless sensor networks using solar energy harvesting. I Networking, Sensing and Control (ICNSC), 2013 10th IEEE International Conference on. (IEEE International Conference on Networking Sensing and Control). S. 71--76.
Bader, S. , Oelmann, B. & Brunig, M. (2012). Challenges for RF two-way time-of-flight ranging in wireless sensor networks. I Proceedings - Conference on Local Computer Networks, LCN. (Proceedings - Conference on Local Computer Networks, LCN). S. 908--916.
Bader, S. , Anneken, M. , Goldbeck, M. & Oelmann, B. (2011). SAQnet: Experiences from the Design of an Air Pollution Monitoring System Based on Off-the-Shelf Equipment. I Proceedings of the 2011 7th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2011.. S. 223--228.
Bader, S. , Schölzel, T. & Oelmann, B. (2010). A Method for Dimensioning Micro-Scale Solar Energy HarvestingSystems Based on Energy Level Simulations. I Proceedings - IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, EUC 2010.. S. 372--379.
Bader, S. & Oelmann, B. (2010). Enabling battery-less wireless sensor operation using solar energy harvesting at locations with limited solar radiation. I Proceedings - 4th International Conference on Sensor Technologies and Applications, SENSORCOMM 2010.. S. 602--608.
Bader, S. & Oelmann, B. (2009). Adaptive synchronization for duty-cycling in environmental wireless sensor networks. I ISSNIP 2009 - Proceedings of 2009 5th International Conference on Intelligent Sensors, Sensor Networks and Information Processing.. S. 49--54.
Licentiatavhandlingar
Bader, S. (2011). Enabling autonomous envionmental measurement systems with low-power wireless sensor networks. Lic.-avh. (Sammanläggning) Sundsvall : Mittuniversitetet, 2011 (Mid Sweden University licentiate thesis : 54)
Manuskript
Bader, S. , Krämer, M. & Oelmann, B. A Testbed for the Evaluation of Solar Energy Harvesting Architectures.
Aranda, J. J. L. , Bader, S. & Oelmann, B. Power conditioning for pressure fluctuation energy harvesters using piezoelectric stacks under low excitation.