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Biography

I am a software research engineer and computer science Lecturer. I have several years of experience in both academia and industry. I work as a research engineer at HPE. I conducted my doctoral studies between 2016 and 2021 at the University of Basel. I got my M.sc. and B.Sc. degrees from Ain-shams University in 2014 and 2010, respectively. During my career life, I worked in different software companies as either a part-time or full-time software engineer. My primary research interests are HPC from both of the hardware and software perspectives, parallel programming paradigms, scheduling, and heterogeneous architectures.

I have always embraced the beauty of versatility and continuous learning in the ever-changing technology landscape. Technology should never be a limiting factor, but rather an invitation to expand one's skills and expertise. Throughout my career,I have demonstrated my ability to dive deep into various technologies as needed, enabling me to develop innovative solutions and stay ahead of the curve.

Selected Publications (Full List of Publications on Google Scholar)

Selected Research Projects

  • DAPHNE: Integrated Data Analysis Pipelines for Large Scale Data Management, HPC and Machine Learning
    Description: Funded (EU Horizon 2020) research project that aims to define and build an open and extensible system infrastructure for integrated data analysis pipelines, including data management and processing, high-performance computing (HPC), and machine learning (ML) training and scoring.
    My role: The work in this project is organized into nine work packages (WP). I am co-leading one of these work packages, WP 05: Scheduling and Resource Sharing. I responsible for meeting the deadlines of the work package deliverables. This responsibility includes active participation in research discussions with work package collaborators, prototyping and code development for research ideas, and writing deliverable reports and scientific publications.
    Link
  • 3BEARS: Broad Bundle of Benchmarks for Scheduling in HPC, Big Data, and ML
    Description: Funded research (Swiss Academy of Engineering Sciences (Switzerland) via the Germaine de Staël programme) project that aims develop ways to co-design parallel applications and scheduling algorithms in order to achieve high performance and optimize resource utilization.
    My role: As a researcher in this project, I participate with my colleagues in devising, implementing, and evaluating a scientific methodology to get insights from scheduling related scientific manuscripts collected from different digital libraries. I am responsible for the data acquisition, cleaning, and visualization stages.
    Link
  • MLS: Multilevel Scheduling Large-Scale High-Performance Computers
    Description: Funded research (Swiss National Science Foundation) project that aims to make a fundamental advance toward simpler use of large-scale high performance computing systems, with impacts not only in the computer science community but also in all computational science domains.
    My role: investigate and develop a multilevel scheduling (MLS) approach that allows schedulers at both, batch and application levels to cooperate and exchange information about applications' execution and resource usage. My work involved theoretical research studies, simulation, and experiments. In addition to prototyping thhe MLS approach, I was responsible for writing and publishing the research ideas in scientific venues.
    Link

    • Teaching

    Alumni Students

    Industry Experience

    Community Service

    Skills

    Open-source Contributions

    Awards and Honors