Sebastian Schmidl

531 citations
6 papers · 264 indexed · 1 hit paper · h-index 4
Topics
Anomaly Detection Techniques and Applications (4 papers)Time Series Analysis and Forecasting (4 papers)Network Security and Intrusion Detection (3 papers)
Journals
Proceedings of the VLDB EndowmentThe VLDB JournalGesellschaft für Informatik (GI)
Partner nations
Germany

In The Last Decade

Sebastian Schmidl

5 papers receiving 258 citations

Hit Papers

Anomaly detection in time series2022202620232024202250100150200

Peers

Sebastian Schmidl
Comparison fields: 5 of 54
  • Artificial Intelligence 220
  • Signal Processing 153
  • Computer Networks and Communications 120
  • Control and Systems Engineering 43
  • Computer Vision and Pattern Recognition 13
Replace Dingshuo Chen with:
Dingshuo Chen China
Jihun Yi South Korea
Paulo Angelo Alves Resende Brazil
Hsiao-Chung Lin Taiwan
Sagnik Sarkar India
Claudio Mazzariello Italy
Firas Bayram Sweden
Marcos V. O. de Assis Brazil
Shaashwat Agrawal India
Chonghua Wang China
Sebastian Schmidl relative to Dingshuo Chen China Dingshuo Chen's profile →
Citations per field
00.5×1.5×
Dingshuo Chen · 1×
Citations per year

Countries citing papers authored by Sebastian Schmidl

Since Specialization
Citations

This map shows the geographic impact of Sebastian Schmidl's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sebastian Schmidl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sebastian Schmidl more than expected).

Fields of papers citing papers by Sebastian Schmidl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sebastian Schmidl. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sebastian Schmidl. The network helps show where Sebastian Schmidl may publish in the future.

Co-authorship network of co-authors of Sebastian Schmidl

This figure shows the co-authorship network connecting the top 25 collaborators of Sebastian Schmidl. A scholar is included among the top collaborators of Sebastian Schmidl based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sebastian Schmidl. Sebastian Schmidl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

6 of 6 papers shown
#WorkIndexed citations
1 1
2 5
3
Anomaly detection in time seriesbreakdown →
232
4 21
5 5
6 0

About Sebastian Schmidl

Sebastian Schmidl is a scholar working on Signal Processing, Computer Networks and Communications and Artificial Intelligence, having authored 6 papers that have together received 264 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (4 papers), Time Series Analysis and Forecasting (4 papers) and Network Security and Intrusion Detection (3 papers). The work is most often cited by research in Signal Processing (153 citations), Artificial Intelligence (220 citations) and Computer Networks and Communications (120 citations). Sebastian Schmidl has collaborated with scholars based in Germany. Frequent co-authors include Thorsten Papenbrock and Felix Naumann. Their work appears in journals such as Proceedings of the VLDB Endowment, The VLDB Journal and Gesellschaft für Informatik (GI).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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