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个人简介
Dr. Renz’s main research interest is Data Science with focus on scalable methods for searching and mining in very large, heterogeneous, dynamic and potentially uncertain data. He has published more than 120 papers on peer-reviewed international conferences and in international journals. His work has received considerable attention by the corresponding community with more than 2500 citations achieving an H-index of 23 and an i10-index of 51. He gave several invited tutorials, seminars, and keynotes on international conferences and in 2016, his work received the 10-Year Best Paper Award at the International Conference on Database Systems for Advanced Applications. His work has been supported by governmental research grants and industrial funding including Siemens AG, Volkswagen Group, Audi AG, and BMW AG. He has been a program committee member for several international conferences and workshops, including SIGMOD, VLDB, ICDE, and KDD. Furthermore, Dr. Renz co-organized and chaired several international conferences and workshops, including SSTD, ACM SIGSPATIAL, DASFAA, ACM SIGSPATIAL QUeST, ACM SIGMOD GeoRich, and ACM SIGSPATIAL LocalRec.
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crossref(2024)
International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Managementpp.468-476, (2023)
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Results in Control and Optimization (2023): 100204
2023 IEEE 19th International Conference on e-Science (e-Science)pp.1-2, (2023)
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ACM SIGSPATIAL International Conference on Advances in Geographic Information Systemspp.23:1-23:4, (2023)
ACM SIGSPATIAL International Conference on Advances in Geographic Information Systemspp.81:1-81:10, (2023)
PROCEEDINGS OF 2023 18TH INTERNATIONAL SYMPOSIUM ON SPATIAL AND TEMPORAL DATA, SSTD 2023pp.51-60, (2023)
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