This year, I serve in many program committees of academic conferences. Among others, this is the 44th IEEE International Conference on Distributed Computing Systems, the 8th IEEE International Conference on Fog and Edge Computing, the 2024 International Joint Conference on Neural Networks, and the 18th ACM International Conference on Distributed and Event-based Systems.
Category Archives: General
Paper Accepted at VLDB!
Our paper titled “How Can We Train Deep Learning Models Across Clouds and Continents? An Experimental Study” has been accepted at PVLDB and is going to be presented at the VLDB 2024 conference! A preprint is avaibale online: https://arxiv.org/abs/2306.03163
Papers at ACM Middleware and ACM BuildSys!
Various papers have been accepted over the course of the summer: At the ACM International Conference on Middleware (Middleware ’23): At the ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys ’23): Congratulations to my successful PhD students!
Paper accepted at ACM e-Energy 2023
Our paper titled “Energy vs Privacy: Estimating the Ecological Impact of FederatedLearning” has been accepted for publication at the 14th ACM International Conference on Future Energy Systems (e-Energy 2023)!
Paper accepted at ACM Computing Surveys!
Our paper titled “The Evolution of Distributed Systems for Graph Neural Networks and their Origin in Graph Processing and Deep Learning: A Survey” has just been accepted for publication at ACM Computing Systems. In the paper, we draw parallels between distributed graph processing, deep learning and graph neural network systems. It brings together our differentContinue reading “Paper accepted at ACM Computing Surveys!”
Survey Paper accepted at IJCAI 2023!
Our paper titled “A Survey on Dataset Distillation: Approaches, Applications and Future Directions” has been accepted for publication at the 32nd International Joint Conference on Artificial Intelligence!
Paper accepted at ICDE
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.
Program Committee Memberships
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.
Startup Mentorship (EXIST)
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/
PhD Positions
I’m actively looking to recruit new PhD students in distributed systems and data management. In case you’re interested, send me an email with your CV!
Ruben Mayer 