Priom Biswas

Priom Biswas received his Master’s degree in Computer Science from the Technical University of Kaiserslautern in 2022. Since 2020, he has been working at the Fraunhofer Institute for Experimental Software Engineering IESE in Kaiserslautern. Prior to joining the institute, he garnered more than three years of professional experience as a software engineer in Bangladesh. Here at Fraunhofer IESE, he has the role of a software architect and researcher in the Virtual Engineering department. Together with his team, he develops and tests solutions for the FERAL simulation framework. His research focuses on the specialized domains of software architecture, continuous engineering, and simulation. -- Priom Biswas machte 2022 seinen Masterabschluss in Informatik an der Technischen Universität Kaiserslautern. Seit 2020 arbeitet er am Fraunhofer-Institut für Experimentelles Software Engineering IESE in Kaiserslautern. Vor seiner Zeit am Institut sammelte er mehr als drei Jahre Berufserfahrung als Software Engineer in Bangladesh. Hier am Fraunhofer IESE ist er als Softwarearchitekt und wissenschaftlicher Mitarbeiter in der Abteilung Virtual Engineering tätig. Zusammen mit seinem Team entwickelt und testet er Lösungen für das Simulationsframework FERAL. Seine Forschungsschwerpunkte liegen in den Fachgebieten Softwarearchitektur, Continuous Engineering und Simulation.

FERAL testbed: Implementation of an infotainment system for validation and testing

The evolution of vehicle infotainment systems has dramatically enhanced the driving experience. This is achieved by incorporating advanced functionalities such as navigation, multimedia, and connectivity options. Therefore, meticulous testing is crucial to ensure the reliability and functionality of these sophisticated…

Simplifying Simulation Scenario Design and Execution: A Guide to Creating and Configuring FERAL Simulation Scenarios with YAML

Introduction Creating and configuring simulation scenarios is effort-intensive and time-consuming, mainly because each scenario requires a unique set of configurations, parameters, and settings, making the procedure time-consuming and error-prone. This complexity not only reduces productivity but also increases the learning…