I’ve started a new position as a tenured professor of computer science at the University of Bayreuth. I’m going to build up a new research group there, the Chair of Data Systems. If you’re interested in a PhD or PostDoc position, please contact me!
Our paper titled “Partitioner Selection with EASE to Optimize Distributed Graph Processing” has been accepted at IEEE International Conference on Data Engineering (ICDE 2023). It explores the use of machine learning to automate the selection of the optimal graph partitioning algorithm for a given distributed graph processing problem.
I’m a member of the program committee of several conferences in 2023. Among others, ACM International Conference on Middleware 2023, and IEEE International Conference on Fog and Edge Computing 2023.
Our paper entitled “How To Optimize My Blockchain? A Multi-Level Recommendation Approach” has been accepted for publication at the ACM SIGMOD 2023 conference!
I’m happy to announce that our project “CLOUDSTARS – Cloud Open Source Research Mobility Network” has been granted. There are in total 18 partners from industry and academia with a funding volume of 1.4 M EUR. The project allows the partners to send researchers to the corresponding partner institution to perform research together.
Our paper titled “Federated Office Plug-Load Identification for Building Management Systems” has been accepted at the Thirteenth ACM International Conference on Future Energy Systems (ACM e-Energy 2022)!
I am apointed as a mentor of the EXIST-funded startup RYVER.AI. They provide software to generate synthetic data and assess its privacy as well as quality. More information: https://ryver.ai/ Find more information on EXIST: https://www.exist.de/
Our paper “Out-of-Core Edge Partitioning at Linear Run-Time” has been accepted for publication at the IEEE International Conference on Data Engineering 2022! A preprint will soon be posted on arXiv.
I’ve been invited to the program committee of IEEE International Conference on Decentralized Applications and Infrastructures (IEEE DAPPS 2022). Paper submission deadline is on May 8th.
Our paper titled “Where is My Training Bottleneck? Hidden Trade-Offs in Deep Learning Preprocessing Pipelines” has been accepted for publication at the SIGMOD 2022 conference. In this paper, we provide an in-depth analysis of data preprocessing pipelines from four different machine learning domains. We introduce a new perspective on efficiently preparing datasets for end-to-end deepContinue reading “SIGMOD Paper Accepted!”
I’ve been invited to serve in the program committee of the ACM International Conference on Distributed and Event-Based Systems (DEBS 2022). Find more information here.
I’m happy to announce that we’ve received funding for a new research project at TUM, titled “Federated Learning for Non-Invasive Condition Monitoring”. The funding is sufficient to support one PhD student for three years (see job posting). Many thanks to the Federal Ministry for Economic Affiars and Energy (BMWi) for funding this exciting research!
Our paper titled “MDMS: Music Data Matching System for Query Variant Retrieval” has been accepted in the demos and videos program of the ACM Multimedia 2021 conference. Co-authors were Rinita Roy and Hans-Arno Jacobsen.
Ruben Mayer 