Markus Endler

PeerJ Editor, Author & Reviewer

Summary

Markus Endler obtained his Dr. rer. nat. in Computer Science from the Technical University of Berlin (1992), and the Professor Livre-docente title (Habilitation) from the University of São Paulo (2001). From 1989 to 1993 he worked as a researcher at the GMD Research Institute Karlsruhe (Germany), and from 1994 to 2000 as an Assistant Professor at the Institute of Mathematics and Statistics of the University of São Paulo (USP). In 2001 he joined the Department of Informatics of the Pontifícia Universidade Católica in Rio de Janeiro (PUC-Rio), where he is currently Associate Professor. His main research interests include Mobile and Pervasive Computing, IoT Middleware Architectures. Distributed Algorithms for Cooperation and Consensus, Online Data Analytics, and Data Stream Processing. As of 2020, he has supervised 13 PhD thesis and 30+ M.Sc. dissertations.

Autonomous Systems Computer Networks & Communications Distributed & Parallel Computing Emerging Technologies Mobile & Ubiquitous Computing

Editorial Board Member

PeerJ Computer Science

Work details

Associate Professor and Department Director

PUC-Rio

March 2001

Departamento de Informática

He joined the Department of Informatics of PUC-Rio in 2001, where he does undergraduate and graduate level teaching, does research and thesis supervision, executes administrative tasks and leads projects with the industry. In addition, he leads the Laboratory for Advanced Collaboration (LAC) - www.lac.inf.puc-rio.br, an applied research lab that does R&D in middleware for mobile/pervasive systems and internet of Things, and distributed stream processing. In LAC work several post-docs, Doctoral and master students, as well as several undergraduate students. Since July 2020 he also serves as the Director of the Department of Informatics, with a 2 year mandate and one possible extension.

Websites

PeerJ Contributions

Edited 2

Academic Editor on

January 2, 2024

An autonomous mixed data oversampling method for AIOT-based churn recognition and personalized recommendations using behavioral segmentation

Ghulam Fatima, Salabat Khan, Farhan Aadil, Do Hyuen Kim, Ghada Atteia, Maali Alabdulhafith

https://doi.org/10.7717/peerj-cs.1756

July 5, 2021

FogFrame: a framework for IoT application execution in the fog

Olena Skarlat, Stefan Schulte

https://doi.org/10.7717/peerj-cs.588