Jad Alhajj
About Jad Alhajj
Jad Alhajj is a research intern at Inria in Rennes, France, where he has worked since 2021. He has a background in software engineering and technical support, with experience at companies such as Microsoft and Everteam.
Work at Inria
Currently, Jad Alhajj is engaged in a Research Internship at Inria, which he began in 2021. This position is located in Rennes, Brittany, France, and he has been involved in this role for three years. Prior to this internship, he worked at Inria as a Student Intern for three months in 2020, also in Rennes. His work at Inria focuses on research and development in computing, particularly in areas related to performance evaluation and optimization.
Previous Employment Experience
Before joining Inria, Jad Alhajj held several positions in the technology sector. He worked as a Technical Maintenance/Support professional at SAB, a software solutions provider for banks, from 2018 to 2019 in Beirut District, Lebanon. Additionally, he served as a Software Engineer at Everteam from 2014 to 2016. His experience also includes a role at Microsoft as the NEPA DX Project Coordinator from 2016 to 2017, where he contributed to project management and coordination efforts.
Education and Expertise
Jad Alhajj holds a Master's degree in Cloud and Network Infrastructure from Université de Rennes I, which he completed from 2019 to 2021. He also earned a Bachelor's degree in Computer Science from the Holy Spirit University of Kaslik (USEK) between 2010 and 2014. His educational background provides a strong foundation in computing and networking, which he applies in his research and professional roles.
Research Contributions
In his research role, Jad Alhajj has evaluated and analyzed the performance and behavior of Hadoop schedulers across various infrastructure types, including Cloud, Edge, Fog, and Grid. He has implemented several Hadoop optimizations in Java on a simulator to enhance performance. Additionally, he conducted a comprehensive study of Hadoop optimizations by reviewing over fifteen scientific articles, contributing to the understanding of performance improvements in distributed computing.