World's Best Scientists 2026 revealed!
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Computer Science
Estonia
2025

D-Index & Metrics

Computer Science

D-Index
40
Citations
6906
World Ranking
9299
National Ranking
3

Research.com Recognitions

  • 2025 - Research.com Computer Science in Estonia Leader Award
  • 2022 - Research.com Computer Science in Estonia Leader Award
  • 2017 - ACM Senior Member

Overview

Sherif Sakr was affiliated with the University of Tartu in Estonia during their academic career. Their research primarily spanned the fields of Computer Science and Medicine, reflecting an interdisciplinary approach to their work.

The main fields of study covered by their publications included:

  • Computer Science (71 publications)
  • Medicine (20 publications)

The scientist specialized in multiple notable subfields within these areas. These subfields included:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications
  • Cardiology and Cardiovascular Medicine
  • Information Systems

The core topics covered throughout their work were:

  • Machine Learning and Data Classification
  • Advanced Database Systems and Queries
  • Data Stream Mining Techniques
  • Graph Theory and Algorithms
  • Semantic Web and Ontologies
  • Data Management and Algorithms
  • Explainable Artificial Intelligence (XAI)

Among their frequent coauthors were:

  • Radwa Elshawi
  • Radwa El Shawi
  • Emanuele Della Valle
  • Riccardo Tommasini
  • Angela Bonifati

Sakr's work was published multiple times in recognized venues, including:

  • Scientific Reports
  • arXiv (Cornell University)
  • Movebank
  • ACM Computing Surveys
  • 2022 IEEE International Conference on Data Mining Workshops (ICDMW)

Some of their recent papers included:

  • The future is big graphs, 2021, Communications of the ACM
  • Interpretability in healthcare: A comparative study of local machine learning interpretability techniques, 2020, Computational Intelligence
  • Graph Generators, 2020, ACM Computing Surveys
  • DLBench: a comprehensive experimental evaluation of deep learning frameworks, 2021, Cluster Computing
  • Exploiting time series of Sentinel-1 and Sentinel-2 to detect grassland mowing events using deep learning with reject region, 2022, Scientific Reports

In recognition of their professional contributions, Sakr was awarded the title of ACM Senior Member in 2017.

Best Publications

  • A Survey of Large Scale Data Management Approaches in Cloud Environments

    S. Sakr;A. Liu;D. M. Batista;M. Alomari

  • Predicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT) project

    Manal Alghamdi;Mouaz H Al-Mallah;Mouaz H Al-Mallah;Steven J Keteyian;Clinton Brawner

  • On the interpretability of machine learning-based model for predicting hypertension

    Radwa Elshawi;Mouaz H. Al-Mallah;Sherif Sakr

  • The family of mapreduce and large-scale data processing systems

    Sherif Sakr;Anna Liu;Ayman G. Fayoumi

  • Graph query processing using plurality of engines

    Sameh Elnikety;Yuxiong He;Sherif Sakr

  • Towards a Comprehensive Data Analytics Framework for Smart Healthcare Services

    Sherif Sakr;Amal Elgammal

  • XQuery on SQL hosts

    Torsten Grust;Sherif Sakr;Jens Teubner

  • Relational processing of RDF queries: a survey

    Sherif Sakr;Ghazi Al-Naymat

  • Interpretability in healthcare: A comparative study of local machine learning interpretability techniques

    Radwa ElShawi;Youssef Sherif;Mouaz Al‐Mallah;Sherif Sakr

  • Predictors of in-hospital length of stay among cardiac patients: A machine learning approach

    Tahani A. Daghistani;Radwa Elshawi;Sherif Sakr;Sherif Sakr;Amjad M. Ahmed

  • Automated Machine Learning: State-of-The-Art and Open Challenges.

    Radwa El Shawi;Mohamed Maher;Sherif Sakr

  • The future is big graphs: a community view on graph processing systems

    Sherif Sakr;Angela Bonifati;Hannes Voigt;Alexandru Iosup

  • Big Data Systems Meet Machine Learning Challenges: Towards Big Data Science as a Service

    Radwa Elshawi;Radwa Elshawi;Sherif Sakr;Sherif Sakr;Domenico Talia;Paolo Trunfio

  • XML compression techniques: A survey and comparison

    Sherif Sakr

  • DREAM: distributed RDF engine with adaptive query planner and minimal communication

    Mohammad Hammoud;Dania Abed Rabbou;Reza Nouri;Seyed-Mehdi-Reza Beheshti

  • Large scale graph processing systems: survey and an experimental evaluation

    Omar Batarfi;Radwa El Shawi;Ayman G. Fayoumi;Reza Nouri

  • Using machine learning on cardiorespiratory fitness data for predicting hypertension: The Henry Ford ExercIse Testing (FIT) Project.

    Sherif Sakr;Radwa Elshawi;Amjad Ahmed;Waqas T Qureshi

  • A query language for analyzing business processes execution

    Seyed-Mehdi-Reza Beheshti;Boualem Benatallah;Hamid Reza Motahari-Nezhad;Sherif Sakr

  • On understanding the economics and elasticity challenges of deploying business applications on public cloud infrastructure

    Basem Suleiman;Basem Suleiman;Sherif Sakr;Sherif Sakr;D. Ross Jeffery;D. Ross Jeffery;Anna Liu;Anna Liu

  • Handbook of Big Data Technologies

    Albert Y. Zomaya;Sherif Sakr

  • A framework for querying graph-based business process models

    Sherif Sakr;Ahmed Awad

Frequent Co-Authors

Liming Zhu
Liming Zhu Commonwealth Scientific and Industrial Research Organisation
Boualem Benatallah
Boualem Benatallah Dublin City University
Athman Bouguettaya
Athman Bouguettaya University of Sydney
Zakaria Maamar
Zakaria Maamar University of Doha for Science and Technology
Angela Bonifati
Angela Bonifati Claude Bernard University Lyon 1
Albert Y. Zomaya
Albert Y. Zomaya University of Sydney
Sameh Elnikety
Sameh Elnikety Microsoft (United States)
Jens Teubner
Jens Teubner TU Dortmund University
Mathias Weske
Mathias Weske Hasso Plattner Institute
Yuxiong He
Yuxiong He Microsoft (United States)

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