Siming Bayer

Siming Bayer, Dr. -Ing

Researcher

Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)

Room: Room 10.134
Martensstr. 3
91058 Erlangen

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

Unpublished Publications

2021

Journal Articles

Conference Contributions

2020

Conference Contributions

2019

Journal Articles

Conference Contributions

2018

Conference Contributions

2017

Journal Articles

Conference Contributions

Übung (UE)

  • Pattern Recognition Exercises

    Information regarding the online teaching will be provided in the studon course.

    • 1 SWS; Expected participants: 500; ECTS-Studium (ECTS-Credits: 1,25)
    • Termin:
      • Di 16:15-17:45, Room 02.134-113 (exclude vac) ICS

Vorlesung (VORL)

  • 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)

    • 3 SWS; Expected participants: 500; Schein; ECTS-Studium (ECTS-Credits: 3,75), Unterrichtssprache Englisch
    • Termin:
      • Mo 14:15-15:45, Room H4 (exclude vac) ICS
      • Di 08:15-09:45, Room H4 (exclude vac) ICS

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.