Tarek Khaled

- Led end-to-end design and deployment of AI and optimization systems for intermodal container terminal operations, from mathematical modeling to production at scale. - Designed a Digital Twin and simulation framework to analyze bottlenecks and optimize container flow and resource allocation. - Architected production AI infrastructure on Kubernetes, implementing MLOps best practices for reproducibility, automated deployment, and monitoring. - Developed predictive and operations research models for berth planning, yard management, and equipment allocation under uncertainty. - Contributed to international research publications and industry standardization (TIC 4.0).

Teach and design courses on database management and knowledge representation, blending foundational concepts with industry-relevant tools. - Relational databases focus on SQL optimization, schema design, and query performance, while NoSQL databases such as MongoDB, Redis, and Cassandra emphasize scalability and distributed use cases. - Knowledge Graphs: Cover RDF, OWL, and graph-based data models with practical applications like ontology design and data integration.

- Design, development and deployment of clustering systems to aggregate web pages dealing with the same topic. - Contribution to the implementation of a web crawler to collect web pages relating to tourist points of interest - Contribution to the development of a search engine combining AI and the Solr tool Extracting knowledge from several million web pages dealing with tourism - Development and implementation of machine learning models to exploit data extracted from web pages on the theme of tourism - Setting up, configuring and monitoring production operations (code deployment, upgrades, system patches) on Kubernetes and GCP - Working closely with Customer Success Managers and developers to understand the various requirements and translate them into technical specifications.