Muddsair Sharif

Akademische Mitarbeiter- Machine Learning

Muddsair Sharif
Master Software Technology
+49 711 8926 2772
  • Digitalisierung in Forschung, Lehre & Wirtschaft


  • 2023 -.....

    Researcher - Machine Learning, HfT Stuttgart, Germany

  • 2018-2022

    Researcher- High Performance Computing, HfT Stuttgart, Germany

  • 2016-2018

    Researcher IoT- Antwerpen, Belgium


M4_LAB Innovative Hochschule

HFT-lnnovationslabor für die Metropolregion 4.0

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Meeting eines Teams


Künstliche Intelligenz für die Lehre an der HFT Stuttgart

Zum Projekt


  • 2022

    ARaaS: Context-Aware Optimal Charging Distribution Using Deep Reinforcement Learning

  • 2021

    iMobilAkou: The Role of Machine Listening to Detect Vehicle using Sound Acoustics

  • 2020

    COaaS:Continuous Integration and Delivery framework for HPC using Gitlab-Runner

  • 2020

    Context-Aware optimal charging distribution using Deep Reinforcement Learning

  • 2019

    Distributed Uniform Streaming Framework: An Elastic Fog Computing Platform for Event Stream Processing and Platform Transparency

  • 2019

    Distributed Uniform Streaming Framework: Towards an Elastic Fog Computing Platform for Event Stream Processing

  • 2019

    Context-Aware Distribution In Constrained IoT Environments

  • 2019

    Demonstrating Innovative Technologies for the Flemish Asphalt Sector CyPaTs.

  • 2018

    A particle Swarm Optimization-based Heuristic for Optimal Cost Estimation in Internet of Things Environment

  • 2018

    Context-Aware Optimization of Distributed Resources in Internet of Things Using Key Performance Indicators

  • 2017

    IT in Road Construction: Recommendations for the Development of Production, Transport and Paving Data Storage in the Flemish Region

  • 2017

    Towards real-time smart road construction  through the implementation of IoT

  • 2017

    Context-aware optimization of distributed resources in IoT

  • 2006

    On fast recognition of isolated characters by constructing character signature


Autonomous Vehicle
Resource Optimality Electric Vehicle
Context Aware- Resource Optimisation in Electric Vehicle Smart2Charge.
Context-Aware- Multi-Objective Optimisation in Constraints Environment.