My research interests deal with designing and developing distributed data processing engines using modern hardware for scalable data management and machine learning. Currently, I am investigating distributed protocols for dealing with large distributed state in stream processing engines.
Before joining TU Berlin and DFKI, I received my MSc degree from University of Salerno in collaboration with the Distributed and Parallel Systems Group, Innsbruck under supervision of Radu Prodan and Vittorio Scarano. I developed my Master's thesis while partecipating to an Erasmus+ program.
- Efficient Migration of Very Large Distributed State for Scalable Stream Processing. Bonaventura Del Monte, in Proceedings of the VLDB 2017 PhD Workshop. International Conference on Very Large Data Bases (VLDB-2017), located at co-located with the 43rd International Conference on Very Large Databases (VLDB 2017), August 28, München, Germany, 2017.
- PROTEUS: Scalable Online Machine Learning for Predictive Analytics and Real-Time Interactive Visualization. Bonaventura Del Monte, Jeyhun Karimov, Alireza Rezaei Mahdiraji, Tilmann Rabl, Volker Markl, in Proceedings of the Workshops of the EDBT/ICDT 2017 Joint Conference (EDBT/ICDT 2017). International Workshop on Big Data Management in European Projects (EuroPro), 1st, located at Joint Conference EDBT/ICDT, March 21, Venice, Italy, 2017.
- A scalable GPU-enabled framework for training deep neural networks. Bonaventura Del Monte, Radu Prodan, in the 2nd IEEE Int. Conf. on Green High Performance Computing (ICGHPC'16), Nagercoil, India, February 26-27, 2016.
I am currently involved into the following EU funded projects:
- VLDB 2019, external reviewer
- SIGMOD 2018, external reviewer
- Big Data Analytics Project, WS 2018-2019, TU Berlin
- Information Management Seminar, SS 2018, TU Berlin
- Big Data Analytics Project, WS 2017-2018, TU Berlin
- Big Data Analytics Project, SS 2017, TU Berlin
- Information Management Seminar, SS 2017, TU Berlin
Mentored Master's Theses
- Thao Ha, Spatial Analytics using the Apache Flink Platform, defended Aug 2017
- Adrian Bartnik, Runtime Modifications of a Flink Jobgraph, defended Apr 2018
- Dominik Schröck, Building an optimizer for Dynamic Rescaling of Distributed Stream Processing Engines, defended Jul 2018