Prof. Dr. Maximilian E. Schüle
Willkommen bei meiner Professur für Data Engineering! Wenn Sie interessiert sind, bei mir Bachelor- oder Masterarbeit zu schreiben, schicken Sie mir bitte eine E-Mail mit Ihren aktuellen Leistungsnachweisen.
Bio
Maximilian E. Schüle ist seit Oktober 2022 Professor für Data Engineering an der Universität Bamberg. Er studierte von 2011 bis 2015 Informatik im Bachelor an der TUM mit einem Austauschsemester an der Sorbonne Universität im Jahr 2013. Anschließend absolvierte er 2016 seinen Master of Science in Software Engineering an der Universität Augsburg, LMU und TUM. Danach war er als wissenschaftlicher Mitarbeiter in der Datenbankgruppe von Prof. Alfons Kemper, Ph.D. und Prof. Dr. Thomas Neumann an der TUM tätig, wo er 2022 zum Dr. rer. nat. promoviert wurde.
Lehre
| Summer 2024 | MOBI-DBS-B |
| Summer 2023 | Database Systems for modern CPU Seminars |
| Winter 2022/23: | Systems Programming in C++ Seminar: Modern Database Systems for Machine Learning and Knowledge Discovery |
| Summer 2022: | Implementation of Database Systems |
| Winter 2021: | Seminar: Techniques for implementing main memory database systems |
| Summer 2021: | Implementation of Database Systems |
| Winter 2020: | Seminar: Techniques for implementing main memory database systems |
| Summer 2020: | Implementation of Database Systems |
| Summer 2019: | Implementation of Database Systems |
| Summer 2018: | Implementation of Database Systems |
| Winter 2017: | Seminar: Techniques for implementing main memory database systems |
| Summer 2017: | Implementation of Database Systems |
| Winter 2012: | Operating-Systems and Systems Software (Tutor) |
Service
- PC member: ICDE 2025, VLDB 2025, DEEM 2024, BTW 2023, DSAA 2023, SSDBM 2023
- Journal Reviewer: JMLR 2022, TKDE 2022, TODS 2023, Information Systems 2024, MCS 2025
- Conference Organisation: BTW 2025 (General Co-Chair), SIGMOD 2025 (Proceedings Co-Chair), VLDB 2017 (Local Arrangement, Demo Track)
- Guest Editor Datenbank-Spektrum, Special Issue on "Machine Learning for Systems and Systems for Machine Learning"
Auszeichnungen
- 2023: Best Short Paper Award BTW
- 2021: Invitation to Best of BTW
- 2021: Invitation to Best of SSDBM
- CIKM 2017: Best Demo Candidate
- CIKM 2017: Travel Grant
Publikationen
Vollständige Liste auf dblp oder Google Scholar.
- Maximilian E. Schüle, Harald Lang, Maximilian Springer, Alfons Kemper, Thomas Neumann, Stephan Günnemann: Recursive SQL and GPU-support for in-database machine learning (Distributed and Parallel Databases: Scientific and Statistical Data Management in the Age of AI 2021)
- Maximilian E. Schüle: Modern SQL for Knowledge Discovery and Dataset Versioning Dissertation, Technische Universität München, Dezember 2021
- Maximilian E. Schüle, Luca Scalerandi, Alfons Kemper, Thomas Neumann: Blue Elephants Inspecting Pandas: Inspection and Execution of Machine Learning Pipelines in SQL (26th International Conference on Extending Database Technology (EDBT 2023))
- Maximilian E. Schüle, Alfons Kemper, Thomas Neumann: Recursive SQL for Data Mining (34th International Conference on Scientific and Statistical Database Management (SSDBM 2022))
- Maximilian E. Schüle, Maximilian Springer, Alfons Kemper, Thomas Neumann: LLVM Code Optimisation for Automatic Differentiation (6th Workshop on Data Management for End-to-End Machine Learning (DEEM@SIGMOD 2022))
- Josef Schmeißer, Maximilian E. Schüle, Viktor Leis, Thomas Neumann, Alfons Kemper: B²-Tree: Page-Based String Indexing in Concurrent Environments (Datenbank-Spektrum Feburary 2022, Volume 21, Issue 3)
- Maximilian E. Schüle, Tobias Götz, Alfons Kemper, Thomas Neumann: ArrayQL Integration into Code-Generating Database Systems (25th International Conference on Extending Database Technology (EDBT 2022))
- Magdalena Pröbstl, Philipp Fent, Maximilian E. Schüle, Moritz Sichert, Thomas Neumann and Alfons Kemper: One Buffer Manager to Rule Them All: Using Distributed Memory with Cache Coherence over RDMA (12th International Workshop on Accelerating Analytics and Data Management Systems (ADMS@VLDB 2021))
- Maximilian E. Schüle, Tobias Götz, Alfons Kemper, Thomas Neumann: ArrayQL for Linear Algebra within Umbra (33rd International Conference on Scientific and Statistical Database Management (SSDBM 2021))
- Maximilian E. Schüle, Harald Lang, Maximilian Springer, Alfons Kemper, Thomas Neumann, Stephan Günnemann: In-Database Machine Learning with SQL on GPUs (33rd International Conference on Scientific and Statistical Database Management (SSDBM 2021))
- Maximilian E. Schüle, Josef Schmeißer, Thomas Blum, Alfons Kemper, Thomas Neumann: TardisDB: Extending SQL to Support Versioning (ACM SIGMOD International Conference on Management of Data (SIGMOD 2021))
- Lukas Karnowski, Maximilian E. Schüle, Alfons Kemper, Thomas Neumann: Umbra as a Time Machine: Adding a Versioning Type to SQL (19th symposium of "Database systems for Business, Technology and Web" (BTW 2021))
- Josef Schmeißer, Maximilian E. Schüle, Viktor Leis, Thomas Neumann, Alfons Kemper: B²-Tree: Cache-Friendly String Indexing within B-Trees. (19th symposium of "Database systems for Business, Technology and Web" (BTW 2021))
- Maximilian E. Schüle, Alex Kulikov, Alfons Kemper, Thomas Neumann: ARTful Skyline Computation for In-Memory Database Systems (24th European Conference on Advances in Databases and Information Systems (ADBIS 2020))
- Maximilian E. Schüle, Jakob Huber, Alfons Kemper, Thomas Neumann: Freedom for the SQL-Lambda: Just-in-Time-Compiling User-Injected Functions in PostgreSQL (32nd International Conference on Scientific and Statistical Database Management (SSDBM 2020))
- Maximilian E. Schüle, Lukas Karnowski, Josef Schmeißer, Alfons Kemper, Thomas Neumann: Versioning in Main-Memory Database Systems: From MusaeusDB to TardisDB (31st International Conference on Scientific and Statistical Database Management (SSDBM 2019))
- Maximilian E. Schüle, Matthias Bungeroth, Alfons Kemper, Stephan Günnemann, Thomas Neumann: MLearn: A Declarative Machine Learning Language for Database Systems (3rd Workshop on Data Management for End-to-End Machine Learning (DEEM@SIGMOD 2019))
- Maximilian E. Schüle, Matthias Bungeroth, Dimitri Vorona, Alfons Kemper, Stephan Günnemann, Thomas Neumann: ML2SQL - Compiling a Declarative Machine Learning Language to SQL and Python (22nd International Conference on Extending Database Technology (EDBT 2019))
- Maximilian E. Schüle, Dimitri Vorona, Linnea Passing, Harald Lang, Alfons Kemper, Stephan Günnemann, Thomas Neumann: The Power of SQL Lambda Functions (22nd International Conference on Extending Database Technology (EDBT 2019))
- Maximilian E. Schüle, Frédéric Simonis, Thomas Heyenbrock, Alfons Kemper, Stephan Günnemann, Thomas Neumann: In-Database Machine Learning: Gradient Descent and Tensor Algebra for Main Memory Database Systems (18th symposium of "Database systems for Business, Technology and Web" (BTW 2019))
- Maximilian E. Schüle, Linnea Passing, Alfons Kemper, Thomas Neumann: Ja-(zu-)SQL: Evaluation einer SQL-Skriptsprache für Hauptspeicherdatenbanksysteme (18th symposium of "Database systems for Business, Technology and Web" (BTW 2019))
- Nina Hubig, Linnea Passing, Maximilian E. Schüle, Dimitri Vorona, Alfons Kemper, Thomas Neumann: HyPerInsight: Data Exploration Deep Inside HyPer (Best Demo Candidate) (The 26th ACM International Conference on Information and Knowledge Management (CIKM 2017))
- Maximilian E. Schüle, Pascal Schliski, Thomas Hutzelmann, Tobias Rosenberger, Viktor Leis, Dimitri Vorona, Alfons Kemper, Thomas Neumann: Monopedia: Staying Single is Good Enough - The HyPer Way for Web Scale Applications (43th International Conference on Very Large Databases (VLDB 2017))
- Maximilian E. Schüle: Integration eines hochperformanten Apriori-Operators in einer Hauptspeicherdatenbank, Masterarbeit, TU München, 2016
- Maximilian E. Schüle: Ein Bash-zu-SQL-Übersetzers für die in-situ Dateianalyse, Bachelorarbeit, TU München, 2015
Vorträge
Invited Talks:
- 2023, May 10, TU Graz: SQL4ML: Blue Elephants Learning from Panda
- 2023, April 27, University of Augsburg: SQL4ML: Mit blauen Elefanten lernen
- 2023, March 7, ML4Systems@BTW23: Teaching Blue Elephants the Maths for Machine Learning and Inspection
- 2022, December 6, Fachschaft WIAI (Christmas Lecture): The Life of Tux - A Christmas Carol
Paper Presentations:
- EDBT 2023: Blue Elephants Inspecting Pandas
- BTW 2023: NN2SQL
- SSDBM 2022: Recursive SQL for Data Mining
- DEEM@SIGMOD 2022: LLVM Code Optimisation for Automatic Differentiation
- EDBT 2022: ArrayQL Integration into Code-Generating Database Systems
- ADMS@VLDB 2021: One Buffer Manager to Rule Them All: Using Distributed Memory with Cache Coherence over RDMA
- SSDBM 2021: ArrayQL for Linear Algebra within Umbra
- SSDBM 2021: In-Database Machine Learning with SQL on GPUs
- SIGMOD 2021: TardisDB: Extending SQL to Support Versioning
- BTW 2021: Umbra as a Time Machine: Adding a Versioning Type to SQL
- ADBIS 2020: ARTful Skyline Computation for In-Memory Database Systems
- SSDBM 2020: Freedom for the SQL-Lambda: Just-in-Time-Compiling User-Injected Functions in PostgreSQL
- SSDBM 2019: Versioning in Main-Memory Database Systems: From MusaeusDB to TardisDB
- DEEM@SIGMOD 2019: MLearn: A Declarative Machine Learning Language for Database Systems
- BTW 2019: In-Database Machine Learning: Gradient Descent and Tensor Algebra for Main Memory Database Systems
- BTW 2019: Ja-(zu-)SQL: Evaluation einer SQL-Skriptsprache für Hauptspeicherdatenbanksysteme
BA/MA
If you are interested in writing a Bachelor's/Master's thesis, please conduct the list of available topics and send me an e-mail with your transcript of records attached and your topic wish.
Completed Thesis:
| Presentation | Type | Title (en) |
| 24.05.22 | BA | Code-Generation for GPU Database Systems |
| 25.01.22 | MA | Automatic Differentiation within an Open-Source Database System |
| 19.10.21 | MA | High Performant GPU Code-Generation for In-Database Machine Learning |
| 05.10.21 | BA | Lightweight Inspection of Data Preprocessing and Machine Learning using SQL |
| 24.11.22 | MA | An SQL Extension to Support Data Versioning |
| 27.10.20 | GR | Benchmarking Array Database Systems |
| 28.04.20 | BA | Machine Learning over Factorized Databases |
| 14.04.20 | BA | Integration of ArrayQL in a main memory database system |
| 26.11.19 | BA | Efficient Vectorization for Skyline Compuation |
| 19.11.19 | MA | Efficient In-Memory Index Structures for Concurrent Access beyond Main Memory for Database Systems |
| 12.11.19 | MA | Integration of Lambda Expressions in an Open-Source Database System |
| 12.11.19 | BA | Adaption of Tree-based Database Index Structures for Data Mining Algorithms |
| 05.11.19 | MA | An Efficient Memory Coherence Protocol with RDMA for Database Systems |
| 29.10.19 | GR | Improving Version Control for Database Systems |
| 29.10.19 | GR | GPU Integration for Machine Learning within Database Systems |
| 21.05.19 | BA | A Hybrid Relational and Tensor Based Database System Supporting SQL and ArrayQL |
| 21.05.19 | BA | Evaluation von Bibliotheken für Tensorberechnungen in Datenbanksystemen |
| 07.05.19 | BA | Automatic Differentiation with Backward Accumulation for Gradient Descent |
| 02.04.19 | GR | Integration of a Version Control Inside of Modern Database Systems |
| 11.12.18 | MA | Parallelized Tensor Computation for Linear Algebra in Database Systems |
| 30.10.18 | BA | High-Performance Version Controlling for Database Systems |
| 30.10.18 | BA | Parallelization of Efficient Tree Structures for Skyline Computation |
| 23.10.18 | BA | Conception of a Declarative Language for Machine Learning |
| 19.06.18 | BA | Statistical Methods for Database Systems - Adaption from R and TensorFlow |
| 08.05.18 | BA | An SQL Extension to Support Data Versioning |
| FT | Efficient statistical methods for database systems | |
| 13.02.18 | BA | Adaption of Efficient Data Mining Algorithms for Database Management Systems in Apache Spark |
| 19.12.17 | MA | In-Database Gradient Descent for Machine Learning |
Legend: BA (Bachelor's Thesis), MA (Master's Thesis), GR (Guided Research), FT (Final Thesis)
CV
Seit Okt. 2022 | Professor für Data Engineering Universität Bamberg, Deutschland |
| Feb. 2017 - Okt. 2022 | Wissenschaftlicher Mitarbeiter am Lehrstuhl für Datenbanksysteme bei Prof. Alfons Kemper, Ph.D. und Prof. Dr. Thomas Neumann TU München, Deutschland |
| Aug. 2017 - Dez. 2021 | Promotion in Informatik (Dr. rer. net.) an der TU München |
| Okt. 2014 - Dez. 2016 | M.Sc. in Software Engineering TU München, Ludwig-Maximilians-Universität and Universität Augsburg, Deutschland |
| Sep. 2013 - Jan. 2014 | Austauschsemester Sorbonne Université, Paris, Frankreich |
| Okt. 2011 - Sep. 2014 | B.Sc. in Informatik TU München, Deutschland |