Florian Schmidt

Florian Schmidt

Technische Universität Berlin

H-index: 11

Europe-Germany

About Florian Schmidt

Florian Schmidt, With an exceptional h-index of 11 and a recent h-index of 11 (since 2020), a distinguished researcher at Technische Universität Berlin, specializes in the field of Distributed Intelligence, Cloud computing, Machine learning, Industry 4.0.

His recent articles reflect a diverse array of research interests and contributions to the field:

Scalable and Data-driven Decision Support in the Maintenance, Repair, and Overhaul Process

Efficient runtime profiling for black-box machine learning services on sensor streams

Edgepier: P2p-based container image distribution in edge computing environments

Los: Local-optimistic scheduling of periodic model training for anomaly detection on sensor data streams in meshed edge networks

Artificial intelligence for it operations (aiops) workshop white paper

Towards a cognitive compute continuum: An architecture for ad-hoc self-managed swarms

Anomaly Detection and Levels of Automation for AI-Supported System Administration

Towards aiops in edge computing environments

Florian Schmidt Information

University

Position

___

Citations(all)

407

Citations(since 2020)

365

Cited By

161

hIndex(all)

11

hIndex(since 2020)

11

i10Index(all)

14

i10Index(since 2020)

14

Email

University Profile Page

Technische Universität Berlin

Google Scholar

View Google Scholar Profile

Florian Schmidt Skills & Research Interests

Distributed Intelligence

Cloud computing

Machine learning

Industry 4.0

Top articles of Florian Schmidt

Title

Journal

Author(s)

Publication Date

Scalable and Data-driven Decision Support in the Maintenance, Repair, and Overhaul Process

Houkun Zhu

Helena Ebel

Dominik Scheinert

Florian Schmidt

Jens Altenkirch

...

2022/12/7

Efficient runtime profiling for black-box machine learning services on sensor streams

Soeren Becker

Dominik Scheinert

Florian Schmidt

Odej Kao

2022/5/16

Edgepier: P2p-based container image distribution in edge computing environments

Soeren Becker

Florian Schmidt

Odej Kao

2021/10/29

Los: Local-optimistic scheduling of periodic model training for anomaly detection on sensor data streams in meshed edge networks

Soeren Becker

Florian Schmidt

Lauritz Thamsen

Ana Juan Ferrer

Odej Kao

2021/9/27

Artificial intelligence for it operations (aiops) workshop white paper

arXiv preprint arXiv:2101.06054

Jasmin Bogatinovski

Sasho Nedelkoski

Alexander Acker

Florian Schmidt

Thorsten Wittkopp

...

2021/1/15

Towards a cognitive compute continuum: An architecture for ad-hoc self-managed swarms

Ana Juan Ferrer

Sören Becker

Florian Schmidt

Lauritz Thamsen

Odej Kao

2021/5/10

Anomaly Detection and Levels of Automation for AI-Supported System Administration

Anton Gulenko

Odej Kao

Florian Schmidt

2020

Towards aiops in edge computing environments

Soeren Becker

Florian Schmidt

Anton Gulenko

Alexander Acker

Odej Kao

2020/12/10

Optimizing Convergence for Iterative Learning of ARIMA for Stationary Time Series

Kevin Styp-Rekowski

Florian Schmidt

Odej Kao

2020/12/10

Bitflow: An in situ stream processing framework

Anton Gulenko

Alexander Acker

Florian Schmidt

Sören Becker

Odej Kao

2020/8/17

Sensor Artificial Intelligence and its Application to Space Systems--A White Paper

arXiv preprint arXiv:2006.08368

Anko Börner

Heinz-Wilhelm Hübers

Odej Kao

Florian Schmidt

Sören Becker

...

2020/6/9

Anomaly detection in cloud computing environments

Florian Johannes Schmidt

2020

See List of Professors in Florian Schmidt University(Technische Universität Berlin)

Co-Authors

H-index: 33
Odej Kao

Odej Kao

Technische Universität Berlin

H-index: 25
Sergio Lucia

Sergio Lucia

Technische Universität Dortmund

H-index: 16
Helena Szczerbicka

Helena Szczerbicka

Leibniz Universität Hannover

H-index: 15
Lauritz Thamsen

Lauritz Thamsen

Technische Universität Berlin

H-index: 14
Thomas Renner

Thomas Renner

Technische Universität Berlin

H-index: 11
Anton Gulenko

Anton Gulenko

Technische Universität Berlin

academic-engine