Gamal Elkoumy

Amun project aims to protect the disclosure of DFGs extracted from business process event logs in order to strike a balance between disclosure risk and utility loss under a differential privacy model. Amun uses a mathematically proven privacy model to balance the risk correlated with publishing process models and the utility after anonymization. It uses an ε-differential-privacy mechanism to anonymize Directly-Follows Graphs (DFGs). It provides a mathematical approach to calculate the value of ε that represents the amount of noise injected a process mining model that optimizes the risk and utility measures. We conducted an emperical evaluation using 13 real world event logs.

Shareprom: A Tool for Privacy-Preserving Inter-Organizational Process Mining. Shareprom adopts secure multi-party computation protocols to enable organizations to jointly execute process mining. We conducted an emperical evaluation using real world event logs.

We implemented cardinality estimation algorithms on top of Apache Flink. We used two windowing approaches; aggregation functions and window slicing. We performed empirical evaluation of both the methodologies. The project’s result can be used as a separate package for performing stream cardinality of data streams.

In this project, I have participated in integrating multiple services of the Ministry of Interior, of one of the largest middle eastern countries. During the project, I built web services and data pipelines to integrate different services of different branches of the organization.

In this project, I participated in modeling and building the Communication Data Model for one of the largest telecommunication providers in the middle east. The project aimed to transform the call data records (CDRs) of the Ericsson IN system into a communication data model. In addition to that, I was building the staging, transformation, and analytics layer of the system.

During my PhD at the University of Tartu, I develop my skills in process mining and privacy-enhancing technologies under the supervision of Marlon Dumas. I enjoy developing my research and teaching skills at the University of Tartu, and I thoroughly learn about a healthy work-life balance.

During my master’s degree at the faculty of engineering, Tanta University, I developed my data systems and machine learning skills. I enjoyed doing research and helping bachelor students to develop their skills.

During my Bachelor’s at Tanta University, I developed my skills in building software products and automatic systems. I enjoyed developing my early career skills and my volunteering experience.

At DataGear, I learned a lot during my early career. I developed my customer experience and my development skills there. I build data management and analytics applications in the field of telecommunication. I have participated in delivering software products to the customers and performing user acceptance tests.

During working at the wireless research center, I developed my research skills, and I researched Outdoor Localization and Road Lane Detection.