Siming Bayer
Siming Bayer, Dr. -Ing
Researcher
Martensstr. 3
91058 Erlangen
Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)
Martensstr. 3
91058 Erlangen
- Mobile phone: +49 17622520695
- Fax number: +49 9131 85 27270
- Email: siming.bayer@fau.de
- Website: https://lme.tf.fau.de/person/sbayer/
Office hours
12:00 - 17:00, Room 10.134,
- Since 11/2019:
Researcher at Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander University
- 01/2015 to 10/2019:
Researcher at Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander University in collaboration with Siemens Healthineers AG - 09/2016 to 12/2016:
Researcher at Molecular Imaging Lab, Department of Biomedical Engineering, Peking University - 10/2009 t0 09/2015:
Student at Friedrich-Alexander University (B.Sc and M.Sc Biomedical Engineering)
2021
UtilityTwin
(Third Party Funds Group – Overall project)Term: September 1, 2021 - August 31, 2024
Funding source: Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie (StMWi) (seit 2018)In the UtilityTwin research project, an intelligent digital twin for any energy or water supply network is to be researched and developed on the basis of adaptive high-resolution sensor data (down to the sub-second range) and machine learning techniques. Overall, the technology concepts BigData and AI are to be combined in an innovative way in this research project in order to make positive contributions to the implementation of the energy transition and to counteract climate change.
2016
Intraoperative brain shift compensation and point-based vascular registration
(Non-FAU Project)Term: May 1, 2016 - October 31, 2019
2022
Miscellaneous
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Effectiveness of Smart Meters and AI for Energy Transition – a Use Case for District Heating Networks
(2022)
DOI: 10.13140/RG.2.2.32873.77928
BibTeX: Download
(Working Paper)
Unpublished Publications
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Heat Demand Forecasting with Multi-Resolutional Representation of Heterogeneous Temporal Ensemble (Conference contribution, submitted)
NeurIPS 2022 Workshop Tackling Climate Change with Machine Learning (Online, December 9, 2022 - December 9, 2022)
BibTeX: Download - , :
Künstliche Intelligenz als Marktteilnehmer – Technische Möglichkeiten (Conference contribution, submitted)
BibTeX: Download
2021
Journal Articles
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Implications of Experiment Set-Ups for Residential Water End-Use Classification
In: Water 13 (2021), Article No.: 236
ISSN: 2073-4441
DOI: 10.3390/w13020236
URL: https://www.mdpi.com/2073-4441/13/2/236
BibTeX: Download
Conference Contributions
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Prediction of Household-level Heat-Consumption using PSO enhanced SVR Model
Tackling Climate Change with Machine Learning: workshop at NeurIPS 2021 (Online, December 14, 2021 - December 14, 2021)
In: Tackling Climate Change with Machine Learning: workshop at NeurIPS 2021, https://www.climatechange.ai/events/neurips2021.html#accepted-works: 2021
Open Access: https://www.climatechange.ai/papers/neurips2021/42/paper.pdf
URL: https://www.climatechange.ai/events/neurips2021.html#accepted-works
BibTeX: Download
2020
Conference Contributions
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Implications of Experiment Set-Ups for Residential Water End-Use Classification
5th International Electronic Conference on Water Sciences (, November 16, 2020 - November 30, 2020)
DOI: 10.3390/ECWS-5-08225
URL: https://sciforum.net/paper/view/conference/8225
BibTeX: Download - , , , , :
Analyzing an Imitation Learning Network for Fundus Image Registration Using a Divide-and-Conquer Approach
Bildgebung für die Medizin 2020 (Berlin, March 15, 2020 - March 17, 2020)
In: Springer (ed.): Algorithmen – Systeme – Anwendungen. Proceedings des Workshops 2020
BibTeX: Download - , , , , :
Imitation learning network for fundus image registration using a divide-and-conquer approach
International workshop on Algorithmen - Systeme - Anwendungen, 2020 (Berlin, March 15, 2020 - March 17, 2020)
In: Thomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm (ed.): Informatik aktuell 2020
DOI: 10.1007/978-3-658-29267-6_67
BibTeX: Download - , , , , , , , , , , :
An Investigation of Feature-based Nonrigid Image Registration using Gaussian Process
Bildverarbeitung für die Medizin 2020 (Berlin, March 15, 2020 - March 17, 2020)
In: Springer (ed.): Algorithmen – Systeme – Anwendungen. Proceedings des Workshops 2020
BibTeX: Download
2019
Journal Articles
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Registration of vascular structures using a hybrid mixture model
In: International Journal of Computer Assisted Radiology and Surgery (2019), p. 1–10
ISSN: 1861-6410
DOI: 10.1007/s11548-019-02007
URL: https://link.springer.com/article/10.1007/s11548-019-02007-y
BibTeX: Download - , , , :
Corrigendum to: Intraoperative imaging modalities and compensation for brain shift in tumor resection surgery (International Journal of Biomedical Imaging (2017) 2017 (6028645) DOI: 10.1155/2017/6028645)
In: International Journal of Biomedical Imaging 2019 (2019), Article No.: 9249016
ISSN: 1687-4188
DOI: 10.1155/2019/9249016
BibTeX: Download
Conference Contributions
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Local topology preservation for vascular centerline matching using a hybrid mixture model
2019 IEEE Nuclear Science Symposium (NSS) and Medical Imaging Conference (MIC) (Manchester, GB, October 26, 2019 - November 2, 2019)
In: IEEE (ed.): Conference Record IEEE 2019 NSSMIC 2019
BibTeX: Download - , , , , , , , , , :
Pediatric Patient Surface Model Atlas Generation and X-Ray Skin Dose Estimation
Bildverarbeitung für die Medizin (Lübeck, March 17, 2019 - March 19, 2019)
In: BVM 2019
DOI: 10.1007/978-3-658-25326-4_27
BibTeX: Download
2018
Conference Contributions
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MR-projection imaging with perspective distortion as in X-ray fluoroscopy for interventional X/MR-hybrid applications
12 th Interventional MRI Symposium Proceedings (12 th Interventional MRI Symposium) (Boston, USA, October 5, 2018 - October 6, 2018)
In: MR-projection imaging with perspective distortion as in X-ray fluoroscopy for interventional X/MR-hybrid applications 2018
URL: http://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2018/Lommen18-MIW.pdf
BibTeX: Download - , , , , , , , , :
An anthropomorphic deformable phantom for brain shift simulation
IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) (Sydney, Australia)
In: 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC) 2018
URL: http://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2018/Bayer18-AA.pdf
BibTeX: Download - , , , , , , , :
Intraoperative brain shift compensation using a hybrid mixture model
International Conference on Medical Image Computing and Computer-Assisted Intervention (Medical Image Computing and Computer Assisted Intervention – MICCAI 2018) (Granada, Spain, September 16, 2018 - September 20, 2018)
In: Springer, Cham (ed.): MICCAI 2018: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018, pp 116-124, Springer 2018
DOI: 10.1007/978-3-030-00931-1
BibTeX: Download - , , , , , , , :
Resolve Intraoperative Brain Shift as Imitation Game
MICCAI Challenge 2018 for Correction of Brainshift with Intra-Operative Ultrasound (CuRIOUS 2018) (Granada conference center)
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2018/Zhong18-RIB.pdf
BibTeX: Download - , , , , , , , :
Preliminary Study Investigating Brain Shift Compensation using 3D CBCT Cerebral Vascular Images
Bildverarbeitung für die Medizin 2018 (Erlangen, March 11, 2018 - March 13, 2018)
In: Bildverarbeitung für die Medizin 2018 2018
DOI: 10.1007/978-3-662-56537-7_48
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2018/Bayer18-PSI.pdf
BibTeX: Download
2017
Journal Articles
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Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery
In: International Journal of Biomedical Imaging 2017 (2017), p. 18
ISSN: 1687-4188
DOI: 10.1155/2017/6028645
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2017/Bayer17-IIM.pdf
BibTeX: Download
Conference Contributions
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Generation of synthetic Image Data for the Evaluation of Brain Shift Compensation Methods
3rd Conference on Image-Guided Interventions & Fokus Neuroradiologie (Magdeburg, April 6, 2017 - April 7, 2017)
In: 3rd Conference on Image-Guided Interventions & Fokus Neuroradiologie 2017
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2017/Bayer17-GOS.pdf
BibTeX: Download - , , , , :
SIFT Key-Points for Lung Tumor Detection in PET/CT Images
Medical Image Understanding and Analysis (MIUA) (Edinburgh)
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2017/Nitschke17-SKF-talk.pdf
BibTeX: Download
Übung (UE)
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Pattern Recognition Exercises
Information regarding the online teaching will be provided in the studon course.
Vorlesung (VORL)
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Pattern Recognition
This class will be given purely on fau.tv. Short videos will be posted on a regular schedule (not necessary the in-person time mentioned here at UnivIs)
Student Assistant / HiWi – Knowledge Graph for Utility Data
Contact person: Dr. Siming Bayer, Email: siming.bayer@fau.de
You are interested in working with time series, geographical information system, different database technology and would like to develop further in the field of machine learning?
Then have a look at our offer!
Your tasks are:
- Understand the state-of-the-art methods and technology for knowledge graph, identify various application fields in the industry
- Support the development of our framework to establish a digital twin for utility infrastructure written in Python
- Support the maintenance of graphical database for utility data deployed using Neo4j on MS AZURE environment
- Support the enrichment and expansion of the knowledge graph by utilizing ML techniques
What you bring to the table:
- You are currently enrolled as a student at Friedrich-Alexander University and studying computer science, mathematics, physics, or a related field
- Hands-on programming experience with Python and familiar with machine learning techniques
- Preferably prior experience with various database techniques, such as SQL or graphical database
- Curiosity and pro-active mind
What you can expect from us:
- An interesting application-oriented new field of research with contribution for sustainable utilization of nature resources
- Extensive scientific support
- Flexible way of working
- Friendly and open environment at the Pattern Recognition Lab.