| 2022 | GECCO | Facilitating the hybridization of parallel evolutionary algorithms in cluster computing environments. | Hatem Khalloof, Sergen Ciftci, Shadi Shahoud, Clemens Dpmeier, Kevin Frderer, Veit Hagenmeyer |
| 2020 | MEDES | A Generic Flexible and Scalable Framework for Hierarchical Parallelization of Population-Based Metaheuristics. | Hatem Khalloof, Mohammad Mohammad, Shadi Shahoud, Clemens Dpmeier, Veit Hagenmeyer |
| 2020 | MEDES | A Meta Learning Approach for Automating Model Selection in Big Data Environments using Microservice and Container Virtualization Technologies. | Shadi Shahoud, Hatem Khalloof, Moritz Winter, Clemens Dpmeier, Veit Hagenmeyer |
| 2019 | IDEAL | Superlinear Speedup of Parallel Population-Based Metaheuristics: A Microservices and Container Virtualization Approach. | Hatem Khalloof, Phil Ostheimer, Wilfried Jakob, Shadi Shahoud, Clemens Dpmeier, Veit Hagenmeyer |
| 2019 | MEDES | Facilitating and Managing Machine Learning and Data Analysis Tasks in Big Data Environments using Web and Microservice Technologies. | Shadi Shahoud, Sonja Gunnarsdottir, Hatem Khalloof, Clemens Dpmeier, Veit Hagenmeyer |
| 2019 | PPAM | A Distributed Modular Scalable and Generic Framework for Parallelizing Population-Based Metaheuristics. | Hatem Khalloof, Phil Ostheimer, Wilfried Jakob, Shadi Shahoud, Clemens Dpmeier, Veit Hagenmeyer |
| 2018 | GECCO | A generic distributed microservices and container based framework for metaheuristic optimization. | Hatem Khalloof, Wilfried Jakob, Jianlei Liu, Eric Braun, Shadi Shahoud, Clemens Dpmeier, Veit Hagenmeyer |