Felix Gündling
About Felix Gündling
Felix Gündling is a C++ Developer at Redpanda Data and a Postdoctoral Researcher at Technische Universität Darmstadt, where he has worked since 2020. He specializes in multi-criteria intermodal routing and real-time travel assistance, and has a strong background in computer science with multiple degrees from the same university.
Work at Redpanda Data
Felix Gündling has been employed as a C++ Developer at Redpanda Data since 2022. In this role, he contributes to the development of high-performance software solutions, focusing on reliability and efficiency. His expertise in C++ programming supports the company's objectives in delivering advanced data streaming technologies.
Current Research at Technische Universität Darmstadt
Felix Gündling serves as a Postdoctoral Researcher at Technische Universität Darmstadt since 2020. His research primarily involves multi-criteria intermodal routing and real-time travel assistance. This work aims to enhance transportation systems by integrating various modes of travel and providing timely information to users.
Previous Experience at DB Fernverkehr AG
Prior to his current roles, Felix Gündling worked as an External Consultant at DB Fernverkehr AG in 2019 for 11 months. His position involved providing expert advice and solutions to improve operational efficiency within the organization, leveraging his background in software development and transportation systems.
Educational Background at Technische Universität Darmstadt
Felix Gündling completed his education at Technische Universität Darmstadt, where he earned a Bachelor of Science in Computer Science from 2009 to 2012, followed by a Master of Science from 2012 to 2015. He further advanced his studies by obtaining a Doctorate in Computer Science from 2015 to 2020. His academic background laid the foundation for his research interests and professional expertise.
Involvement in the MOTIS Project
Since 2020, Felix Gündling has been the Project Lead for the MOTIS Project in Darmstadt. This initiative focuses on developing algorithms aimed at future mobility solutions. His leadership role involves coordinating research efforts and implementing innovative strategies to address challenges in transportation and mobility.