About Khalil

Khalil Al-Rahman Youssefi is a researcher specializing in swarm intelligence, swarm robotics, multi-agent systems, and autonomous robotics. He received his B.Eng. in Software Engineering from the University of Birjand in 2018 and his M.Eng. in Artificial Intelligence from Ferdowsi University of Mashhad in 2020. He is currently pursuing his Ph.D. in Information and Communications Engineering at Alpen-Adria-Universität Klagenfurt, where his research focuses on coverage exploration for robot swarms in complex and unknown environments.

At Lakeside Labs GmbH, he works on swarm robotics, distributed multi-agent systems, and optimization methods for industrial applications. He has also been affiliated with the Institute for Networked and Embedded Systems at Alpen-Adria-Universität Klagenfurt since 2021, contributing to research on swarm robotic systems.

His research interests include swarm robotics, distributed multi-agent systems, and optimization for autonomous and networked systems. He is particularly interested in how intelligent collective behaviors can improve the resilience and adaptability of future cyber-physical systems and Industry 4.0 applications, and how such systems can be optimized to operate efficiently and at scale. His work also includes deep learning, deep reinforcement learning, image processing, and digital signal processing.

Email: youssefi@lakeside-labs.com
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ORCID 0000-0002-8719-7699
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Selected Research Projects

Shared Charging

An FFG funded project that develops shared EV charging infrastructure integrating renewable energy for sustainable mobility. It focuses on scalable, cost efficient and accessible charging solutions for public and semi public areas.

EmbeddedAI

An Erasmus+ funded project that is creating an international Master of Science program in Embedded Artificial Intelligence aimed at embedding AI into real world systems.

BugWright2

A European-funded research project under Horizon 2020 that develops autonomous robotic inspection and maintenance systems for ship hulls.

SwarmIn

An FFG funded project that developed swarm-intelligence based optimization methods for cyber physical manufacturing. It focused on self organizing multi agent systems for Industry 4.0.

Publications

2026

Youssefi, K. A.-R., Gojković, M., Stefanutti, W., Auer, M., & Schranz, M. (2026). A grid-aware agent-based model for analyzing electric vehicle charging systems. In Proceedings of the 16th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH) (pp. 341–349). SciTePress. https://doi.org/10.5220/0015054900004094

2025

Youssefi Darmian, K. A., & Elmenreich, W. (2025). Coverage exploration of unknown obstacle-cluttered environments using a swarm of ground robots. Applied Soft Computing, 185, 113964. https://doi.org/10.1016/j.asoc.2025.113964
Youssefi Darmian, K. A., Abbaszadeh Darban, R., Kastner, G., & Elmenreich, W. (2025). A criterion for assessing obstacle-induced environmental complexity in multi-robot coverage exploration. PLoS One, 20(5), e0323112. https://doi.org/10.1371/journal.pone.0323112
Youssefi, K.A., Gojković, M., Schranz, M. (2026). Enhancing Job-Shop Scheduling Performance with a Refined Bottom-Up Variant of the Artificial Bee Colony Algorithm. In: Wagner, G., Werner, F., De Rango, F. (eds) Simulation and Modeling Methodologies, Technologies and Applications. SIMULTECH 2024. Lecture Notes in Networks and Systems, vol 1620. Springer, Cham. https://doi.org/10.1007/978-3-032-04777-9_6

2024

Youssefi, K. A., Gojković, M., & Schranz, M. (2024). Artificial Bee Colony Algorithm: Bottom-Up Variants for the Job-Shop Scheduling Problem. In SIMULTECH 2024, 103–111. https://doi.org/10.5220/0012765900003758
Youssefi, K. A.-R., Lindner, H., & Elmenreich, W. (2024). RoboTunes: A Multi-Player Learning Framework with Musical Programmable Robots. In 2024 10th International Conference on Automation, Robotics and Applications (ICARA), Athens, Greece, 334–338. https://doi.org/10.1109/ICARA60736.2024.10553175

2022

Valavi, M. H., Jaberipur, G., & Youssefi, K. A.-R. (2022). Impact of different types of input wire on defect-tolerance of QCA majority voter. European Physical Journal Plus, 137(8), 977. https://doi.org/10.1140/epjp/s13360-022-03134-3
Youssefi, K. A.-R., Rouhani, M., Mashhadi, H. R., & Elmenreich, W. (2022). A swarm intelligence-based robotic search algorithm integrated with game theory. Applied Soft Computing, 122, 108873. https://doi.org/10.1016/j.asoc.2022.108873

2021

Youssefi, K. A.-R., & Rouhani, M. (2021). Swarm intelligence based robotic search in unknown maze-like environments. Expert Systems with Applications, 178, 114907. https://doi.org/10.1016/j.eswa.2021.114907